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Long term effects of increasing albedo in urban areas

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Climate and Dynamics

Authors

Peter J. Irvine,

Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK
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Andy Ridgwell,

Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK
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Daniel J. Lunt

Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK
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Abstract

[1] Various surface albedo modification geoengineering schemes such as those involving desert, urban, or agricultural areas have been proposed as potential strategies for helping counteract the warming caused by greenhouse gas emissions. However, such schemes tend to be inherently limited in their potential and would create a much more heterogeneous radiative forcing than propositions for space-based "reflectors" and enhanced stratospheric aerosol concentrations. Here we present results of a series of atmosphere-ocean general circulation model (GCM) simulations to compare three surface albedo geoengineering proposals: urban, cropland, and desert albedo enhancement. We find that the cooling effect of surface albedo modification is strongly seasonal and mostly confined to the areas of application. For urban and cropland geoengineering, the global effects are minor but, because of being colocated with areas of human activity, they may provide some regional benefits. Global desert geoengineering, which is associated with significant global-scale changes in circulation and the hydrological cycle, causes a smaller reduction in global precipitation per degree of cooling than sunshade geoengineering, 1.1% K −1 and 2.0% K −1 respectively, but a far greater reduction in the precipitation over land, 3.9% K −1 compared with 1.0% K −1. Desert geoengineering also causes large regional-scale changes in precipitation with a large reduction in the intensity of the Indian and African monsoons in particular. None of the schemes studied reverse the climate changes associated with a doubling of CO ₂, with desert geoengineering profoundly altering the climate and with urban and cropland geoengineering providing only some regional amelioration at most.

1. Introduction

[2] The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report concluded that the global temperature change by 2100 would likely range from 1.1°C to 6.4°C, depending on the climate sensitivity of the Earth and on the emissions pathway followed [Intergovernmental Panel on Climate Change (IPCC), 2007]. To limit global warming to 2°C or less, a target proposed by the European Union [Commission of European Communities, 2007], some authors predict that emissions reductions of 90% by 2050 would be required [Weaver et al., 2007]. However, efforts to mitigate carbon emissions so far have been relatively ineffectual; global emissions of greenhouse gases increased by 29% between 2000 and 2008 to 8.7 Pg C yr −1, reduced in 2009 by 1.3% as a result of the economic crisis and are projected to have grown during 2010 by more than 3% [Friedlingstein et al., 2010; Le Quéré et al., 2009].

[3] Solar radiation management (SRM) geoengineering, or "climate engineering," a proposed means to tackle future climate change [Shepherd et al., 2009], involves increasing the upward (toward space) reflection of sunlight and reducing the fraction of shortwave radiation absorbed at the surface, hence cooling the climate and potentially countering the warming effects of increased CO ₂ (and other greenhouse gases). Increasing the outgoing shortwave radiation can, in theory, be achieved through increasing the albedo at a number of different heights in the atmosphere, at the surface, or even in space. This flexibility over which mediums could be modified and over which areas the modification could be applied has led to a wide variety of SRM schemes being proposed, such as of the creation of a sunshade in space [Angel, 2006], cloud albedo modification [Salter et al., 2008], and stratospheric injection of sulfate aerosols [Crutzen, 2006], together with a number of surface albedo geoengineering schemes, including crop albedo enhancement [Ridgwell et al., 2009], urban albedo enhancement [Akbari et al., 2009], and desert albedo geoengineering [Gaskill, 2004].

[4] Most attention to date has been on cloud and aerosol SRM schemes because of their potential to be deployed on a quasi-global scale and to exert sufficient forcing to cancel anthropogenic greenhouse warming of up to a doubling of CO ₂ [Shepherd et al., 2009]. Space-based reflectors also fall into this category, but because of the high cost and very long deployment time scale [Angel, 2006] they have attracted less serious consideration. In contrast, surface albedo modification (SAM) geoengineering schemes would generally be deployed rather more heterogeneously across the Earth's surface and, because of their more limited potential for global impact [Shepherd et al., 2009], have been less well studied. In this paper we address the climate consequences of the three principal SAM schemes: urban areas, croplands, and deserts.

[5] In the rest of section 1 we outline the three land SAM schemes that are the focus of this paper. We do not investigate whether the schemes outlined are economically or technologically feasible options for geoengineering; rather we adopt the schemes as they are described in the literature and then simulate the effects that these schemes have on the climate of an atmospheric-ocean general circulation model (AOGCM).

1.1. Urban Albedo Geoengineering

[6] The idea of urban albedo geoengineering has been considered for a number of years in the guise of reducing the heat island effect and helping improve air quality in cities [Pomerantz et al., 1999; Taha et al., 1999]. Urban albedo geoengineering involves enhancing the albedo of urban areas by replacing standard building materials, for roofs and paving, etc., with alternative more reflective (higher-albedo) materials or by adding a more reflective coating [Akbari et al., 2009; Bretz et al., 1998]. Achievable increases in the albedo of roofing and paving of 0.1-0.4 and 0.15-0.25, respectively, have been estimated, equivalent to an average increase in urban albedo of 0.1 [Akbari et al., 2009]. An alternative estimate of the potential increase in albedo of 0.15 was made by Hamwey [2007], which remains within the range considered by Akbari et al. [2009]. There is a larger range for the estimates of the fraction of the Earth's surface that is covered by suitable urban areas. Hamwey [2007] estimates the suitable urban area at 0.64% of the Earth's surface, from an assumed urban area per capita; Akbari et al. [2009]estimate 0.29% on the basis of the Global Rural-Urban Mapping Project (GRUMP) urban extent data set [Global Rural-Urban Mapping Project (GRUMP), 2005]; however, Lenton and Vaughan [2009] caution that other satellite data indicated the urban area could be as low as 0.051% [Hansen et al., 2000; Loveland et al., 2000]. We take the estimates of potential albedo increase and urban extent from Akbari et al. [2009] as the basis for our simulations because of the availability of the GRUMP data set and the moderate estimate of potential albedo increase.

1.2. Crop Albedo Geoengineering

[7] Biogeoengineering or crop albedo geoengineering would involve growing crop plant varieties with a higher albedo than currently grown as a means to produce a cooling of the planet. Crop albedo is often higher than the albedo of natural vegetation, for example, barley, at European latitudes, has a higher albedo (0.23) than deciduous (0.18) or coniferous (0.16) woodland [Monteith and Unsworth, 1990]. Hence the spread of agriculture has historically led to a modification of the albedo properties of the Earth's surface [Betts et al., 2007; Costa et al., 2007], which has cooled the Earth by an estimated 0.17°C [Matthews et al., 2003]. The albedo of different varieties of a single crop species also differs, depending on, for example, the properties of the leaf wax, the "hairiness" of the leaves and the morphology of the leaf canopy [Febrero et al., 1998; Hatfield and Carlson, 1979; Holmes and Keiller, 2002]. It has been proposed that these properties could be managed to increase the overall albedo of both grassland (pasture) [Hamwey, 2007] and cropland [Ridgwell et al., 2009], although recent analysis of a sample of soybean isolines concluded that existing variability may not be as great as previously assumed [Doughty et al., 2011].

[8] There are various proposals for the types of areas suitable for crop albedo modification and a range of estimates for the potential increase in albedo. Hamwey [2007] suggests that all grassland (cropland, pasture, and wild grassland) could be modified and that the albedo could be increased by 25% (+0.0425), Lenton and Vaughan [2009] calculated that when applied to all grassland (∼7.5% of the Earth's surface) a radiative forcing of −0.51 W m −2 would be achieved. Ridgwell et al. [2009] and Doughty et al. [2011] propose only albedo increases to cropland and suggest albedo increases with ranges of 0.02-0.08 and 0.05-0.15, respectively. We adopt the range of Ridgwell et al. [2009] as it represents a midsized scheme and uses a similar model.

1.3. Desert Albedo Geoengineering

[9] Finally, desert albedo geoengineering involves the laying of highly reflective material across the extensive desert areas of the world to increase the average planetary albedo [Gaskill, 2004]. Suggestions for achieving this include laying and cleaning some form of reinforced plastic sheeting by automated vehicles, covering an estimated 11.7 million km ² of suitable desert [Gaskill, 2004]. The area of deserts that could be suitable for this type of geoengineering cover ∼2% of the Earth's surface, and the albedo increase proposed is from ∼0.36 to ∼0.8. This scheme would produce the greatest radiative forcing and cooling of the different surface albedo schemes compared in this paper [Lenton and Vaughan, 2009]. We adopt this scheme for desert albedo geoengineering, which represents the most extreme example of localized surface albedo modification suggested.

1.4. Summary and Paper Outline

[10] The three different proposals for surface albedo modification (SAM) geoengineering schemes considered here have been previously compared using zero-dimensional (0-D) or one-dimensional (1-D) radiative forcing calculations [for example,Lenton and Vaughan, 2009 and Hamwey, 2007]. However, unlike other climate engineering schemes, SAM geoengineering schemes would be deployed heterogeneously across the Earth's surface. Hence, one would expect important regional-scale impacts and potential side effects that may not be revealed by annual and global-scale averaging. While there have been several general circulation model (GCM) analyses made for urban albedo enhancement [Oleson et al., 2010] and crop albedo enhancement [Ridgwell et al., 2009; Singarayer et al., 2009], these were made using different models and used different experimental and analysis methodologies (e.g., integration time), preventing direct comparison of their projections.

[11] To address this, we have carried out a GCM analysis of all three main SAM schemes, using the same model and the same methodology, presenting GCM results for desert geoengineering for the first time. This allows us to directly compare the three schemes side by side and to explore the relative seasonal and regional impacts that will be very important for these spatially heterogeneous schemes.

[12] To compare the different schemes we analyze the global, local, and remote climate effects of regional surface albedo modification and assess the extent and "quality" of the climate change amelioration achieved. For an initial comparison we conduct an analysis of the effects of the schemes on precipitation and temperature at the global scale. To analyze the local cooling effect we focus on Europe, a region with large urban and crop areas, which is located near to the Sahara (and hence may be expected to be cooled significantly by desert albedo geoengineering). We also analyze the effect of the schemes on regional precipitation, focusing particularly on monsoon regions and analyzing some of the changes in circulation. For remote effects we focus on Arctic snow and sea-ice changes; the Arctic is a region remote from any of the regions affected by SAM but one that has been a focus for previous climate engineering studies [Caldeira and Wood, 2008; Irvine et al., 2009; Robock et al., 2008]. It must be noted that, while the results presented here are illustrative of the types of changes that could be expected, GCM models do not, in general, simulate precipitation or regional climate changes well [Cox et al., 2000; IPCC, 2007].

[13] This paper continues with a methodology, results section, and a discussion and conclusion section. Section 3 is split into global effects, European summer changes, monsoon changes, and Arctic changes. The discussion and conclusion will deal with the implications of the results presented.

2. Methodology

[15] The horizontal resolution of the atmospheric model is 2.5° in latitude by 3.75° in longitude, with 19 vertical layers. The atmospheric model has a time step of 30 min and includes many parameterizations representing subgrid-scale effects, such as convection [Gregory and Rowntree, 1990] and boundary layer mixing [Smith, 1993]. The land surface scheme includes the representation of the freezing and melting of soil moisture. The spatial resolution in the ocean is 1.25° × 1.25°, with 20 vertical layers. The ocean model component uses the Gent and McWilliams [1990]mixing scheme, and there is no explicit horizontal tracer diffusion. The sea-ice model uses a simple thermodynamic scheme and contains parameterizations of sea-ice drift and leads [Cattle and Crossley, 1995]. HadCM3 has a climate sensitivity of 3.3°C for a doubling of CO ₂, which falls in the midrange of the estimate of the likely climate sensitivity reported in the IPCC AR4 (2.0°C-4.5°C) [Solomon et al., 2007].

[16] We employ the MOSES 1 land surface scheme [Cox et al., 1999], which accounts for terrestrial surface fluxes of temperature, moisture, and radiation. Although later versions of MOSES are available, for example Essery et al. [2003], the combination of HadCM3 with MOSES 1 is the most widely used and is the most robustly tested [Gordon et al., 2000; Johns et al., 2003; Martin et al., 2006] and for this reason we employ this combination. MOSES includes four soil layers, recording temperature, moisture and phase changes, a canopy layer, and a representation of snow cover. The representation of evaporation includes the dependence of stomatal resistance on temperature, vapor pressure, and CO ₂ concentration [Cox et al., 1999]. Each grid cell has surface properties; roughness length, snow-free albedo, etc., that reflect the vegetation cover present, as derived from the Wilson and Henderson-Sellers data set [Wilson and Henderson-Sellers, 1985].

[17] In the simulations presented here we modified the albedo properties in MOSES, i.e., snow-free albedo and deep-snow albedo, in areas that would be affected by the different surface albedo geoengineering schemes considered. All other surface properties were left fixed at preindustrial conditions for all experiments. We carried out 11 different model simulations using HadCM3: a preindustrial simulation, a simulation with doubled preindustrial CO ₂ concentration (2 × CO ₂), plus nine simulations with increased surface albedo and doubled CO ₂, consisting of three simulations with increased albedo for each of the three geoengineering schemes (urban, crop, and desert albedo geoengineering). An additional simulation, with 2 × CO ₂ and a reduction in incoming solar radiation sufficient to return global average temperature to preindustrial levels (referred to as sunshade geoengineering), was run for comparison. This sunshade geoengineering was achieved by reducing the solar constant by a fraction sufficient to return the global average temperature to the preindustrial value; in our case a 2.1% reduction in incoming sunlight was required (this is the same method implemented by Lunt et al. [2008] and Irvine et al. [2009]).

[18] The regions over which the increases in albedo were applied for each of the schemes are shown in Figure 1. The area for the urban and crop albedo schemes remained the same for each simulation, with the degree of albedo increase varying. For the desert geoengineering simulations, the albedo increase remained the same for all simulations but the areas modified were varied ( Figure 1). Table 1 summarizes the albedo modifications and area coverage of all the different geoengineering scenarios considered here. In most of our analysis we focus on the maximum implementation of each scheme. We do not suggest that these are the most feasible or likely implementations, but were chosen to give the strongest and hence most statistically significant change in order to help identify any subtle effects. All model runs were initialized from a preindustrial spin-up totaling more than 1000 years with each simulation being run for a total of 400 years, using the final 100 years for averaging.

2.1. Urban Albedo Modification

[19] Urban albedo geoengineering has the smallest potential radiative forcing of the three different SRM interventions considered here, and in a previous GCM analysis no statistically significant changes in the climate were recorded [Oleson et al., 2010]. To test whether any feasible implementation of urban albedo enhancement would even be observable (let alone provide significant climate mitigation) and to allow us to fully elucidate the characteristics of the resulting changes in climate, we assumed an upper estimate of the area to which increased albedo could be applied. In this, we used the Global Rural-Urban Mapping Project (GRUMP) data set of urban extent [GRUMP, 2005] to determine the fraction of each model grid cell that is "urban." The total urban area recorded in the GRUMP urban extent map is 3.5 × 10 ⁶ km ², or 0.68% of the Earth's area, which, after regridding onto the HadCM3 land grid ( Figure 1b), becomes 2.8 × 10 ⁶ km ², or 0.56% of the Earth's area (and 1.9% of total land area). The difference is a consequence of the relatively low resolution of HadCM3 and consequent loss of some coastal urban areas in the gridding process.

[20] We followed the methodology of Akbari et al. [2009], assuming 35% of the urban area is paved and 25% is roofing, and applied albedo enhancement to these two surfaces, leaving the other 40% unchanged. From the estimates of Akbari et al. [2009], we tested three levels of albedo increases to roofing and paving (which on average have an albedo estimated at around 0.2 and 0.1, respectively): (1) a maximum increase of 0.35 and 0.25, respectively, (2) a moderate increase of 0.25 and 0.15, respectively, and (3) a small increase of 0.15 and 0.1, respectively. The overall increase in snow-free albedo applied is shown in Table 1. Urban areas at higher latitudes are often snow covered in winter months and so a change to the deep-snow albedo in the model was also applied ( Table 1). The effect of albedo increases in urban areas will affect the deep-snow albedo but only insofar as the underlying surface is exposed. Although the MOSES 1 land surface scheme [Cox et al., 1999] used here does not have an urban land type, MOSES 2.2 does [Essery et al., 2003]. We hence used the values for snow-free and deep-snow albedo from MOSES 2.2 to calculate the exposed fraction:

where α usis the recorded deep-snow albedo of urban areas, f is the fraction of exposed urban surface, 1 − f is the fraction of snow coverage, α uis the snow-free urban albedo, and α sis the deep-snow albedo in the open. In MOSES 1, deep-snow α s has an albedo of 0.8, and the urban albedo values from MOSES 2.2 are 0.4 for α us and 0.18 for α u [Wiscombe and Warren, 1980]. On this basis, fwas found to be 0.645, and so the deep-snow albedo increase applied to urban areas is f(Δ α u); the full list of albedo modifications can be found in Table 1.

2.2. Crop Albedo Modification

[21] Crop albedo geoengineering has been tested in HadCM3 by Ridgwell et al. [2009] and Singarayer et al. [2009] and in CAM 3.0 by Doughty et al. [2011]. We follow a methodology similar to that of both Ridgwell et al. [2009] and Singarayer et al. [2009], apart from using the MOSES 1 land surface scheme rather than MOSES 2.1, used in these studies, in order to provide consistency with the other simulations presented in this paper. We adopt the same definition of crop extent, with the crop area being defined as C3 or C4 grasses that are within human-controlled or disturbed areas as defined by theWilson and Henderson-Sellers [1985]land-type data set. The total area covered by crops is 15.7 × 10 ⁶ km ², 3.1% of the Earth's surface area or 10.6% of the land area ( Figure 1a). To these areas we apply an increase in snow-free albedo dependent on the fractional crop coverage in the grid cell.

[22] We test the same albedo increases as Ridgwell et al. [2009] did, +0.02, +0.04, +0.08, to provide a point of direct comparison. Ridgwell et al. [2009] argue that these levels span the range of changes of what could be possible within existing intervariety albedo variability. This range is consistent with measurements of the leaf albedo of wheat and sorghum that exhibit variations of 0.05 and 0.16, respectively, between varieties [Grant et al., 2003; Uddin and Marshall, 1988]. An average canopy albedo increase of 0.04 in commercially grown varieties may thus be at least partially achievable using traditional plant-breeding techniques. However, in the analysis of a number of soybean isolines,Doughty et al. [2011]found differences in albedo no greater than our lowest tested assumption (+0.02). The deep-snow albedo was not modified as crop coverage is at very low levels in snowy conditions, assuming that either crop plants are not present (or exist as planted seeds) or have minimal canopy during the winter months.

2.3. Desert Albedo Modification

[23] Desert geoengineering represents the most extreme local albedo modification of the surface albedo modification schemes considered, and we explore the effects of different spatial extents instead of exploring different levels (intensities) of implementation. In an account of a U.S. Department of Energy (DOE) meeting on geoengineering, Gaskill [2004] estimates a possible albedo of 0.8 for commercially available coverings and that an estimated 11.7 × 10 ⁶ km ² would be suitable for this application. We take these estimates as the basis for our extreme case of what is possible for desert geoengineering.

[24] We generated a definition for desert areas, based on a combination of observed precipitation and fractional vegetation cover at the resolution of HadCM3, designed to roughly match the estimated total area of that given by Gaskill [2004]. If a grid cell receives on average precipitation of less than 250 mm yr −1, as calculated from the CRU (Climate Research Unit, University of East Anglia) reanalysis data for the period 1961-1990, then it is classed as desert. We also specified that a grid cell must be less than 50% covered in vegetation, as defined by the Wilson and Henderson-Sellers land-type data set [Wilson and Henderson-Sellers, 1985], before it was considered suitable for desert geoengineering ( Figure 1c). This simple method does not capture all desert regions (notably, no deserts are identified in North America) but our method does produce a total area (9.1 million km ²) close to the estimate (11.7 million km ²) of Gaskill [2004]. The albedos of the desert grid cells are adjusted to

where the albedo α is dependent on the vegetated fraction f, α ois the original albedo of the grid cell, and 0.8 is the albedo of the reflective covering. The deep-snow albedo was not changed as the properties of snow deposited on a reflective coating would be similar to those of snow on desert regions.

[25] Three experiments were run to explore the effect of applying desert albedo geoengineering in different regions (see Figure 1c): (1) in which all desert regions were modified ("Global"), (2) modification of only the Sahara desert ("Sahara"), (3) in which only Asian deserts, i.e., from Saudi Arabia and the Middle East eastward, are modified ("Asian").

3. Results

[26] We present results of the global, local, and remote climate effects of SAM geoengineering, splitting the results into four parts: global effects ( section 3.1), European summertime changes ( section 3.2), monsoon system changes ( section 3.3), and Arctic changes ( section 3.4). The global effects section gives an overview of the major changes in temperature and precipitation that arise because of the different geoengineering schemes.

[27] In addition to this global assessment of climate effects, a number of specific changes are investigated: Europe is an illustrative region as there is a high crop and urban density in the region and it is also relatively close to the Sahara, suggesting that we might expect some effect on European climate from each of the SAM geoengineering schemes. Monsoon systems are associated with seasonal atmospheric overturning circulations driven by land-sea temperature differences and play a central role in continental hydrology [Trenberth et al., 2000]. We can expect that SAM geoengineering will change the seasonal land-sea temperature difference that plays a key role in monsoon circulations, making this an essential part of our analysis. Climate change in the Arctic is expected to be greater than elsewhere because of the action of local positive climate feedbacks, e.g., the melting of snow and ice and the consequent albedo decrease [IPCC, 2007]; we examine the effect of SAM geoengineering schemes on the Arctic to assess their effectiveness at reversing the amplified climate change there. All values reported in the text have passed a 5% student t-test significance test unless otherwise stated.

[28] Throughout the results sections we focus on a common subset of the simulations, i.e., the simulations with largest albedo modifications for each surface albedo geoengineering scheme. This is because the weaker crop and urban geoengineering schemes induce relatively small changes in climate that can be difficult to distinguish from the model's internal variability. However, in focusing on the extreme urban and crop geoengineering implementations, we do not claim that these changes in climate would necessarily be linear with respect to the magnitude of SAM albedo increase. For desert geoengineering the global implementation is shown in all figures, and the Asian and Saharan implementations are shown if space allows.

[29] In this study we mostly calculate climate anomalies relative to the 2 × CO ₂simulation rather than to the preindustrial ("Pre-ind") simulation. This makes it easy to see the small changes in climate brought about by urban and crop geoengineering, without their being dwarfed by the changes from 2 × CO ₂ to preindustrial. For desert and sunshade geoengineering, we also compare with preindustrial, as the climate changes that these schemes can cause are large enough to reverse the effects of doubling CO ₂ in some cases.

3.1. Global Effects

[30] The impacts on global and land-averaged temperatures and precipitation for each geoengineering scheme, as well as the effect of unmitigated global warming, are summarized in Table 2. At doubled CO ₂ there is a global average increase in surface air temperature of +3.0°C and an increase in precipitation of +4.0%. On land, the annual average temperature change is amplified (+4.2°C) whereas the precipitation enhancement is reduced (down to +1.8%). Global-average warming is not completely reversed by any SAM scheme, with urban geoengineering having the potential to cool on a global annual average basis by a maximum of 0.11°C, crop geoengineering by 0.23°C, and (global) desert geoengineering by 1.12°C, with the amount of cooling determined by the assumed degree of geoengineering intervention.

Urban Low, 2 × CO ₂

−0.05

−0.04
−0.10
0.20

Crops Low, 2 × CO ₂

−0.05

0.01
−0.11
0.12

[31] Changes in the radiative forcing of the planet affect the hydrological cycle in two ways: There is a "slow" or temperature-driven component that does not depend on the details of the radiative forcing mechanism, and there is a "fast" atmospheric adjustment component that differs between radiative forcing mechanisms [Andrews et al., 2010]. The slow temperature response has been found to cause around a 2%-3% change in precipitation for every degree Kelvin of temperature change, with precipitation increasing with rising temperatures [Lambert and Webb, 2008]. Our simulations show that sunshade geoengineering caused a 2.0% K −1 reduction in precipitation, whereas global desert geoengineering caused only a 1.1% K −1 reduction (we exclude urban and crop geoengineering as a statistically significant change in global average precipitation was not found). For comparison, a study on cloud albedo geoengineering (which increases albedo over ocean areas only) caused a 2.5% K −1 reduction in global average precipitation [Bala et al., 2010]. The different global precipitation responses of these geoengineering schemes are a result of the differing availability of moisture for evaporation in the regions affected, i.e., ocean regions have an infinite supply of water for evaporation whereas the continents do not. Thus, the effect of a reduction in incoming sunlight on the surface energy budget of the ocean will consist of a change in the latent and sensible heat fluxes, leading to a large reduction in evaporation, whereas over the land this will consist mainly of a change in sensible heat flux, with a smaller reduction in global evaporation.

[32] However, the change in continental precipitation shows an opposite result to this global picture; desert geoengineering has the largest reduction at 3.9% K −1, sunshade geoengineering shows 1% K −1, and cloud albedo geoengineering shows 0.9% K −1. This difference in continental precipitation arises from changes in circulation that redistribute the precipitation. This change in distribution has a greater effect on continental precipitation than does the change in the atmospheric moisture availability that controls global precipitation.

[33] The patterns of annual mean surface temperature change are shown in Figure 2. For unmitigated climate change ( Figure 2a), warming occurs everywhere, with greater warming toward the poles and over the land areas. As one would expect, SAM geoengineering does not produce a uniform cooling. Furthermore, in some areas, statistically significant warming (in addition to the impact of 2 × CO ₂) occurs under each of the different geoengineering interventions, probably as a result of changes in circulation patterns, i.e., diverting warm currents of air to high-latitude areas. An example of this is the Southern Ocean around Tasmania, which is warmer for all three SAM geoengineering schemes. In contrast, sunshade geoengineering produces a relatively uniform cooling across the world compared with the surface albedo geoengineering schemes, with land areas and high-latitude areas cooled more than others, reversing most of the warming from 2 × CO ₂.

[34] For urban geoengineering, we find a statistically significant cooling across most continental areas. This is in contrast to the results of Oleson et al. [2010], who did not find any statistically significant cooling as a result of a global reduction in urban albedo. This difference is likely to be partly due to the more extreme implementation we have assumed (and focused on the results of), together with the greater urban coverage assumed in our data set. We have also employed a longer averaging period: 100 years here compared with 58 years in the simulations of Oleson et al. [2010], and hence we are better able to identify small changes in climate against the background of modeled interannual variability. We find the largest cooling in Europe, North America, and in the Arctic, a consequence of the relatively large urban coverage of both Europe and North America ( Figure 1b). This regional cooling is amplified by positive cryospheric feedbacks operating in the high latitudes, particularly because of changes in sea-ice extent (see section 3.4).

[35] Crop albedo geoengineering exhibits a pattern of cooling ( Figure 2c) to a first order similar to urban geoengineering ( Figure 2b), with most of the cooling occurring in the Northern Hemisphere. This similarity between crop and urban albedo is due to the coexistence of greatest crop cover and urban fraction (population) in most regions ( Figures 1a and 1b). Consistent with the results of Singarayer et al. [2009], our results show that crop albedo geoengineering results in the greatest cooling across Eurasia and North America. We also find less cooling than may be expected in South and East Asia, an area with significant crop coverage, a result of an associated reduction in cloud cover in the region [Doughty et al., 2011; Singarayer et al., 2009]. Some warm anomalies are also induced, for example in the Barents Sea, but are not found consistently in the moderate or weak implementations of crop geoengineering and are therefore perhaps a result of long-term climate variability.

[36] Although global desert geoengineering has the potential to generate the largest global average cooling effect, this average masks the fact that most of the 1.12°C cooling is highly concentrated over the desert regions where the albedo increase is applied (compare Figures 2d and 1c). For example, global desert geoengineering causes some areas of the Sahara to be greater than 10°C cooler than in the preindustrial ( Figure 2f). A pronounced general cooling of most continental areas, of between 1.5°C and 2°C over most of Eurasia and North America also occurs, with the notable exception being India, which becomes slightly warmer despite being proximal to a number of desert areas. This warming in India can be explained by cloud feedbacks with an ∼10% reduction in cloud cover in the region (not shown). As with crop and urban geoengineering, the Northern Hemisphere tends to be cooled more than the Southern Hemisphere, a simple consequence of the presence of much greater land coverage in the north.

[37] Sunshade geoengineering produces a much more uniform cooling than the SAM schemes, with noticeably greater cooling in the Northern Hemisphere and the Arctic ( Figure 2e), but does not reproduce the preindustrial temperature distribution; with the low latitudes cooler than in the preindustrial and the high latitudes warmer ( Figure 2g). This difference in temperature is due to the greenhouse forcing acting to slow the loss of heat, which warms the Arctic more, and the reduced solar forcing, which has a greater role in the energy budget at low latitudes, acting to cool the tropics.

[38] In contrast to the response of surface air temperature, which is strongest at the sites of SAM geoengineering, changes in precipitation are much more heterogeneous ( Figure 3). Doubling CO ₂ leads to large regional changes in precipitation, with some areas becoming much drier, e.g., the Amazon, South Africa, and Australia, and others becoming much wetter, e.g., South Asia and equatorial Africa, but with an overall increase in precipitation (see Figure 3a and Table 2). For both urban and crop albedo geoengineering, only minimal shifts in precipitation occur, with the exception of equatorial Pacific regions ( Figures 3b and 3c), whereas desert geoengineering induces quite extreme changes in precipitation patterns throughout the tropics and subtropics ( Figure 3d).

[39] Urban and crop albedo techniques generally induce only small changes in precipitation, with few areas that exhibit a statistically significant change ( Figures 3b and 3c). The changes in precipitation that do occur are consistent with a small southward shift of the (Intertropical Convergence Zone (ITCZ), which is induced by an unequal change in the temperature between the Northern and Southern Hemispheres. Both schemes also result in slightly altered precipitation patterns around southeast Asia, the Indian Ocean, and Australasia, changes that are more marked with crop albedo geoengineering than urban. These changes in precipitation are due to changes in evaporation that occur locally and changes in circulation that redistribute rainfall.

[40] Our prescribed enhancement of desert albedo induces shifts in precipitation patterns ( Figure 3d) of comparable magnitude to those that arise from doubling CO ₂ levels alone (i.e., unmitigated climate change) ( Figure 3a). The most prominent changes occur in monsoonal regions such as sub-Saharan Africa, Southeast Asia, and Australia, where the decrease in rainfall leaves these regions drier than in the preindustrial simulation ( Figure 3f). Northern South America and Central America experience increases in precipitation that are sufficient to reverse the drying caused by doubling CO ₂.

[41] In comparison, sunshade geoengineering produces a reduction in precipitation in most regions relative to 2 × CO ₂, with some large positive and negative anomalies in the tropics ( Figure 3e). When compared with preindustrial areas, few regions experience statistically different precipitation, with exceptions occurring mostly in the tropics ( Figure 3g).

[42] The climatology of the HadCM3 model employed here reproduces many of the first-order features of the global climate system but, as with all models, is not perfect, and HadCM3 has some specific deficiencies that should be borne in mind when considering the results presented here:

[43] Although HadCM3 reproduces the global patterns of surface air temperature, it exhibits a cold bias at high latitudes in the Northern Hemisphere, which is particularly pronounced in Russia, east of Scandinavia, and the coarse-resolution orography leads to local and remote biases [Gordon et al., 2000]. The performance for precipitation is generally less good; the observed global patterns are captured, but significant biases exist: The South Pacific Convergence Zone extends farther and in a more easterly direction than observed (the "double ITCZ" problem), there is a strong wet bias around the maritime continent, and there is a dry bias in India and the northern Amazon region [Solomon et al., 2007].

[44] HadCM3, as with other GCMs, also fails to reproduce the temporal structure of observed"para42" precipitation, with simulated precipitation occurring too frequently and at lower intensity than observed.

3.2. European Summertime Changes

[45] Europe is a highly urbanized region with significant areas of agricultural land. It is also a region that experiences periodic damaging heat waves, with the 2003 heat wave causing an estimated 70,000 deaths [Robine et al., 2008]. Climate model projections suggest that average European summer temperatures as warm as in 2003 may become the mean state by the end of the 21st century, with significant implications for human health, energy consumption (air conditioning), and agriculture in the region [Stott et al., 2004]. Thus, Europe is one of the regions that may potentially benefit most from the application of land albedo geoengineering [Singarayer et al., 2009], with the strongest cooling effect tending to be exerted over the summer months, which should ameliorate some of the effects of extremely warm summers. Because of the relatively large fraction of the land occupied by urban areas and cropland, Europe will experience a cooling significantly greater than the global average [e.g., Ridgwell et al., 2009] under these albedo modification schemes.

[46] To examine the effect of SAM geoengineering on the climate of Europe, we examine results for interannual variability in average annual and summer (June, July, and August (JJA)) temperatures across the region of Western Europe (defined as in Figure 4e). Table 3 summarizes the annual and summer temperature anomalies for the different geoengineering schemes for this region. At 2 × CO ₂ there is an increase of 4.18°C in the annual temperature across the region, with a larger increase in summer (5.03°C).

[47] Against the greenhouse warming of 2 × CO ₂, urban geoengineering produces a cooling of 0.50°C annually and 0.57°C in summer for maximum deployment. For urban geoengineering there is a larger cooling for the lowest deployment than for a moderate deployment, which is likely a result of internal variability in the model. Crop albedo geoengineering is more effective than urban geoengineering in Europe, with a maximum deployment cooling by 0.83°C annually and 1.26°C in summer. Desert albedo geoengineering, applied globally, exerts a cooling of 1.55°C annually and 1.53°C in summer across the region.

[48] Rather counterintuitively, desert geoengineering restricted to the Sahara has less of a cooling effect in Europe than when it is restricted to Asia, the consequence of large changes in circulation that occur (see Figure 6). Desert geoengineering cools air locally but this air does not simply diffuse from the desert regions; instead, it is advected in a complicated manner by the patterns of circulation, which are also modified by desert geoengineering.

[49] Figure 4 shows how the frequency distribution of summer average temperatures over western Europe is affected by SAM geoengineering. At 2 × CO ₂ there is a much warmer summer (∼5°C warmer than the preindustrial on average), and during the 100 year period analyzed, all summers were warmer than the warmest preindustrial summer. A number of particularly warm summers also occur; four times with an average temperature above 23°C and once with an average temperature between 24°C and 25°C. High urban geoengineering ( Figure 4a) lowers the average summer temperature by ∼0.6°C, reducing the number of extremely warm summers. Crop albedo geoengineering ( Figure 4b) is more effective, and the greatest intervention lowers average summer temperatures by 1.3°C. With global desert geoengineering ( Figure 4c) there is a cooling in the summer of 1.5°C and a reduction in the number of extremely warm summers.

[50] The simulation of European surface air temperature in HadCM3 suffers from a cold bias of around 1°C-2°C in this region. Stott et al. [2004]found that internal variability in European summer temperatures in HadCM3 is similar to observed values, but the model might overestimate variability somewhat (note, however, that the region they defined differs from ours). In simulations of European climate with Regional climate models driven by HadAM3H (a high-resolution atmosphere-only version of HadCM3), it was found that higher resolution orography could improve the spatial patterns of surface air temperature but that problems with land surface schemes and the driving GCM's representation of blocking highs affected the surface air temperature variability [Jacob et al., 2007]. These problems with the land surface schemes and with blocking highs affect our model and hence our results. However, despite these problems, these results reveal the important local and seasonal effects of these SAM geoengineering schemes.

3.3. Monsoon Changes

[51] As was noted earlier, global desert geoengineering may cause large changes in precipitation patterns around the world, particularly in monsoon regions such as India, sub-Saharan Africa, and Australia, because of the mechanism that drives monsoon circulations: seasonal land-sea temperature differences. In the normal sequence of events, during the summer months continental areas warm faster than ocean areas, creating a pressure difference: this causes air to circulate, with warm, dry air rising over the continents being replaced by cooler, moist air from the ocean. In winter the opposite occurs as the oceans retain the heat collected over the summer for longer than the land does. With desert geoengineering, there is a large change in albedo of the continental land surface, resulting in cooler summer temperatures, which reduce monsoon circulation locally and lead to significant changes in regional precipitation patterns and also changes in global circulation patterns.

[52] Figure 5a shows the difference between June, July, August (JJA) and December, January, February (DJF) rainfall for the preindustrial. The monsoon systems have a positive difference in precipitation in the north and a negative difference in the south, i.e., greater rainfall in the summer relative to the winter in their respective hemispheres. Figure 5b shows the changes in precipitation seasonality between 2 × CO ₂ and preindustrial; there is an intensification of the seasonality of rainfall in Southeast Asia and Indonesia and a reduction in the Amazon region and around the Caribbean. For both urban and crop geoengineering, we find few statistically significant changes in the seasonality of rainfall and so these results are not shown here. For global desert geoengineering, there is a large reduction in monsoonal rains in areas neighboring the modified desert areas ( Figures 5c-5e). Global desert geoengineering reduces the intensity of the Indian, East Asian, North African, and Australian monsoons but intensifies seasonal rains in Central and South America relative to 2 × CO ₂ ( Figure 5c). On the whole there is a large reduction in summer continental rainfall across the tropics compared with that of the preindustrial ( Figure 5g).

[53] Restricting desert albedo modification to the Sahara ( Figure 5f) reduces the intensity of the North African monsoon and to a lesser extent the Asian monsoon, whereas Asian desert geoengineering ( Figure 5g) reduces the intensity of the Asian monsoon and, perhaps surprisingly, strengthens the North African monsoon, and both schemes increase summer rainfall over Central and South America.

[54] In comparison, sunshade geoengineering reverses most of the effects that doubling CO ₂ has on precipitation seasonality ( Figure 5f), returning the seasonality of precipitation very close to the preindustrial precipitation, with few statistically significant changes ( Figure 5h).

[55] In Figure 6 we show the seasonal changes in 850 hPa winds for global desert geoengineering alongside the changes in precipitation. Desert geoengineering profoundly changes the atmospheric circulation ( Figures 6a and 6b), with the most extreme changes occurring in the Northern Hemisphere summer, when the desert albedo changes have their greatest effect (compare Figures 6a and 6b). The altered patterns of precipitation ( Figures 6c and 6d) correlate well with changes in 850 hPa wind, i.e., there are changes in moisture advection driven by the changes in the winds. This can be seen, for example, along the Ivory Coast, where a large reduction in JJA rainfall coincides with a seaward wind anomaly (i.e., a reduction in monsoonal, landward winds), and in Central America, where the increase in JJA rainfall coincides with an increase in Pacific to Atlantic winds over the isthmus ( Figures 6a and 6c). In Australia, where there are reductions in precipitation, an anticyclonic anomaly in 850 hPa wind during the Austral summer (DJF) acts to reduce the advection of moisture into the north of the continent ( Figures 6b and 6d). In general, desert albedo geoengineering leads to a disruption of precipitation locally and remotely through changes in circulation and therefore in moisture advection.

[56] We identify six different areas of interest that may be affected significantly by desert geoengineering ( Figure 7g). The percentages of change in average annual precipitation for each of these six regions under different geoengineering scenarios are summarized in Table 4. Brazil experiences a large decrease in precipitation at 2 × CO ₂ compared to preindustrial, and all the geoengineering schemes increase precipitation in Brazil, with global desert geoengineering returning precipitation to just above the preindustrial value.

Urban High, 2 × CO ₂
4.6
0.7

−0.2
−3.8
−1.7

4.7

Crops High, 2 × CO ₂
6.8
0.5

−0.4
−9.8 −2.3
2.3

Sahara Desert, 2 × CO ₂
10.8 −33.4 −19.1 −12.5 −4.8
−2.8

[57] In the two African regions considered there are small increases in precipitation at 2 × CO ₂, and for crop and urban geoengineering there is little effect on average precipitation. Global and Saharan desert geoengineering causes large decreases in precipitation in the Sahel and Ivory Coast regions, whereas Asian desert geoengineering causes a large increase in the Sahel band.

[58] In India and Southeast Asia there are moderate increases in precipitation at 2 × CO ₂; both crops and urban geoengineering reduce rainfall in these regions, particularly in India, although it remains above the preindustrial value. Global desert geoengineering decreases rainfall in India significantly and in Southeast Asia to some extent, with a 37% reduction in rainfall, relative to preindustrial in India, and a 6% decrease in Southeast Asia.

[59] Australia experiences a reduction in precipitation at 2 × CO ₂, and most geoengineering schemes considered increase precipitation in Australia, whereas global desert geoengineering (which includes an Australian component) produces an 18% reduction in rainfall compared with the preindustrial.

[60] Variability in monsoon rainfall is also an important indicator of change; Figure 7 shows frequency plots for annual precipitation over India (in Figure 7g the Indian region is shaded blue). The rainfall distribution changes from preindustrial to 2 × CO ₂ with average rainfall up 15% and fewer dry years. Figure 7a shows that urban geoengineering reduces the rainfall over India slightly, returning the distribution somewhat closer to its preindustrial state. Crop geoengineering has a larger impact, returning the mean rainfall over India close to preindustrial values but broadening the distribution ( Figure 7b).

[61] The desert geoengineering schemes applied globally, in the Sahara, and in Asia, all reduce Indian rainfall, resulting in a 37% reduction, no statistically significant change, and an 18% reduction relative to the preindustrial, respectively ( Figures 7c-7e). For global desert geoengineering the wettest years are below the preindustrial mean and, in the driest years, India receives less than 300 mm of rain, down from more than 500 mm in the preindustrial. Asian desert geoengineering has a significant drying effect, whereas Sahara desert geoengineering returns the distribution close to that of the preindustrial state.

[62] Dabang et al. [2005]assessed some of the models used in the Coupled Model Intercomparison Project 3 (CMIP3) for their performance in reproducing the East Asian monsoon and found that all models had difficulties reproducing the observed behavior but that HadCM3 was one of the better models. They found that while HadCM3 overestimated precipitation in all seasons, the distribution of precipitation was similar to that of observations, and although the winter was too cold, the surface air temperature was well reproduced. These problems and others affect the quality of the monsoon results shown, and so the details of the results must be viewed with caution. However, because of desert geoengineering directly affecting the seasonal land-sea temperature difference, the driver of monsoon circulation, the general result of reduced rainfall near modified desert regions is likely to be robust.

3.4. Arctic Changes

[63] The Arctic is a region that is warming faster than the rest of the world, as a result of global warming [IPCC, 2007]. Although the exact mechanisms are uncertain, retreating sea ice and, to a lesser extent, changes in snow cover are likely to be involved [Screen and Simmonds, 2010]. The Arctic is home to large reservoirs of stored carbon, as decayed plant matter in permafrost and methane reserves in hydrates, which could provide an additional (carbon cycle) positive feedback [Archer, 2007]. We focus on the Arctic here for these reasons as well as the fact that it is remote from all the SAM schemes and hence illustrates the potential for nonlocal impacts (and teleconnections) arising from land albedo geoengineering.

[64] Figure 8shows the simulated preindustrial sea-ice and snow coverage for the Northern Hemisphere and the effects of doubling CO ₂ and geoengineering on sea ice and snow. Comparing Figures 8a and 8b, it can be seen that the sea-ice extent and thickness are reduced at 2 × CO ₂compared to preindustrial, with minimum sea-ice cover (September average) reduced by 71% ( Figure 8c). The change in snow depth is more spatially heterogeneous, with snow loss at midlatitudes but an increase in snow depth at high latitudes. At high latitudes the increase in snow accumulation outweighs the increased losses that are due to higher temperatures, and with a greater fraction of the Arctic Ocean ice free there will be more evaporation and consequently greater snowfall (the increase in precipitation is shown in Figure 3a). The snow depth projections for Greenland are omitted as the model does not include an ice sheet module and so cannot simulate changes in this region reasonably.

[65] Figures 8c and 8dshow that urban and cropland geoengineering induce a slight recovery of annual mean sea-ice thickness, with 13% and 20% increases, respectively, in minimum sea-ice cover (September average) relative to 2 × CO ₂and a very small effect on snow depth. Desert geoengineering exerts a more substantial effect on annual mean sea-ice thickness, with a 65% increase in minimum sea-ice cover relative to 2 × CO ₂, which remains 53% lower than the preindustrial coverage. Desert geoengineering also has a large impact on snow depth, with almost the opposite spatial pattern to that of 2 × CO ₂; i.e., desert geoengineering cools and dries the Northern Hemisphere, partly reversing the trend induced by global warming.

[66] Again, projections of effects of geoengineering on climate must be viewed in the context of the degree of fidelity of the climate model used: HadCM3 has a number of biases in the climate state of high northern latitudes that will affect the results shown in this section, the most important of which is a cold bias [Gregory et al., 2002]. HadCM3 also has a wet bias at high latitudes that will affect the quality of the snow cover results [Solomon et al., 2007]. There are problems in the sea-ice climatology of HadCM3 but the model does roughly reproduce the 20th-century trend in sea ice [Gregory et al., 2002] and matches the projections of other AOGCMs, predicting a large decline in summer sea-ice extent over the course of the 21st century [Johannessen et al., 2004]. However, the results shown are consistent with the cooling of the SAM schemes being concentrated in the Northern Hemisphere and show that SAM geoengineering may help to reduce Arctic climate change somewhat.

4. Discussion and Conclusion

[67] Global average measures of climate change alone are insufficient in the assessment of the effectiveness and, particularly, side effects of surface albedo geoengineering. Analyses of regional and seasonal changes in temperature, precipitation, and other variables are critical to elucidating whether any particular proposed geoengineering scheme may be a suitable means to ameliorate climate change. In this study we have used a fully coupled general circulation model (GCM) to project the climatic effects of different surface albedo modification (SAM) geoengineering schemes. However, GCMs are far from perfect representations of the Earth's climate, and, although they perform relatively well on the large scale, they do not match observations well on small spatial and temporal scales [IPCC, 2007]. GCMs are particularly poor at reproducing regional precipitation observations, and so any specific patterns of precipitation change should be viewed with caution [IPCC, 2007]. In addition to these considerations, and as well as deficiencies specific to the HadCM3 model discussed in earlier sections, the MOSES 1 land surface scheme we use assumes fixed vegetation and so does not allow adjustments to changed climatological conditions. Vegetation feedbacks will hence not be captured in our simulations.

[68] Our treatment of surface albedo geoengineering is relatively simplistic, and there are no explicit urban, cropland, or desert surface land types in the MOSES 1 land surface scheme [Cox et al., 1999] we employ here. Areas to which we applied surface albedo geoengineering could also have been alternatively defined. For instance, our definition of desert was based on grid-scale-sized areas, excluding smaller deserts, and hence our distribution of desert geoengineering could be revised. Given the extreme nature of desert albedo modification, a different distribution of modified desert would likely produce a significantly different regional response, which can be seen by comparing the very different responses from our three different areas of application. The assumed magnitudes of geoengineering we deployed for each scheme and in particular for urban geoengineering are generally at the upper end of estimates and do not necessarily represent "realistic" scenarios. We chose to mostly test relatively large-magnitude albedo modifications in order to obtain a sufficient signal-to-noise ratio and thus to enable us to more fully explore the potential climatic consequences of highly concentrated changes in albedo. Overall, however, we believe the distributions we used capture the essential properties of these schemes, and at a minimum our study provides a unique sensitivity test for the climate impacts of the three main proposals for surface albedo geoengineering.

[69] Surface albedo modification (SAM) geoengineering gives rise to both near-field and far-field changes in climate. We find small to insignificant changes in global average temperatures from urban and crop geoengineering, consistent with other studies [Lenton and Vaughan, 2009; Ridgwell et al., 2009], and a more significant cooling with desert geoengineering. For all the SAM schemes we find a local cooling around the region with modified albedo, which is greatest in summer, although we found this effect can be reduced somewhat by changes in cloud feedbacks and advection, as has been found in other studies of SAM geoengineering [Doughty et al., 2011; Ridgwell et al., 2009].

[70] On a global scale we find that the cooling effect of the SAM geoengineering schemes is greater over land and in the Northern Hemisphere because of the greater fraction of suitable regions being in the Northern Hemisphere. We find that the Arctic is cooled somewhat by all schemes, despite being remote from any areas of application, and there is some recovery of sea ice and snow cover, but even desert geoengineering is insufficient to return the Arctic sea ice and snow to their preindustrial conditions.

[71] We find that very large changes in precipitation patterns can occur for desert geoengineering, with much smaller changes for urban and crop geoengineering. We compared desert geoengineering with sunshade geoengineering and with the results of a cloud albedo study and found that although desert geoengineering produces a smaller reduction in global average precipitation per change in temperature, it causes a much greater reduction in the land-average precipitation [Bala et al., 2010]. This is consistent with, but opposite to, the results found in the cloud albedo study of Bala et al. [2010], in which they found a large reduction in global average precipitation but a much smaller reduction in land-average precipitation. This is explained in their study by the warmer region (the land in their case or ocean in ours) having an increase in upward motion in the atmosphere, giving rise to increased precipitation, with the opposite being true for the colder region [Bala et al., 2010]. Similarly we find for urban and crop geoengineering that the relative cooling of the Northern Hemisphere leads to a slight southward shift of the ITCZ that for desert geoengineering is hard to distinguish because of the dramatic changes in circulation arising from the extreme local cooling.

[72] Desert geoengineering causes large changes to continental rainfall in regions neighboring deserts and more broadly causes significant changes in tropical rainfall patterns. These changes arise, in part, because of the seasonal nature of the cooling exerted by SAM geoengineering, with the greatest cooling occurring in summer, when the air over the continents would normally warm faster than the ocean, creating an updraft, which draws in moist air from the oceans bringing seasonal rainfall. This monsoon circulation is reduced by desert geoengineering, leading to a reduction in precipitation across a wide area. We find that precipitation across the tropics is radically shifted, with some areas becoming much drier than in the preindustrial, particularly India, and others becoming wetter.

[73] SAM geoengineering schemes do not offer anything like a full solution to the problems arising from rising greenhouse gas concentrations, and desert geoengineering, in particular, may prove to be detrimental. Our simulations show that urban and crop geoengineering may have little effect on global climates and primarily offer only local ameliorations of some climate change effects. Desert geoengineering, on the other hand, produces strong local cooling in desert regions and results in large changes in circulation and precipitation worldwide. Not only are land albedo geoengineering schemes unable to correct fully for greenhouse-gas-induced climate changes (as is the case for all SRM schemes investigated so far [e.g.,Lunt et al., 2008; Irvine et al., 2010; Jones et al., 2011; Ban-Weiss and Caldeira, 2010]), they would not address ocean acidification [Cao and Caldeira, 2008; Matthews et al., 2009]. Only mitigation of CO ₂ emissions or removal of CO ₂ from the atmosphere by some carbon dioxide removal scheme [Shepherd et al., 2009] would provide a correction for both the climatic and ocean chemistry impacts of elevated CO ₂ concentrations. Future work on SAM geoengineering could look in more detail at the impacts of these schemes with a higher-resolution GCM or a regional climate model or consider combinations of surface albedo modification and other climate engineering schemes as a way to "optimize" the climate modification.

Acknowledgments

[74] P.I. is funded on a NERC Ph.D. studentship. A.R. acknowledges support from the Royal Society in the form of a university research fellowship. D.L. acknowledges funding from the RCUK in the form of a research fellowship. A.R. also acknowledges EPSRC grant EP/I014721/1.

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Keywords

climate change;

climate engineering;

crop albedo;

desert albedo;

geoengineering;

urban albedo

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Authors

Peter J. Irvine,

Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK
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Andy Ridgwell,

Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK
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Daniel J. Lunt

Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK
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Abstract

[1] Various surface albedo modification geoengineering schemes such as those involving desert, urban, or agricultural areas have been proposed as potential strategies for helping counteract the warming caused by greenhouse gas emissions. However, such schemes tend to be inherently limited in their potential and would create a much more heterogeneous radiative forcing than propositions for space-based "reflectors" and enhanced stratospheric aerosol concentrations. Here we present results of a series of atmosphere-ocean general circulation model (GCM) simulations to compare three surface albedo geoengineering proposals: urban, cropland, and desert albedo enhancement. We find that the cooling effect of surface albedo modification is strongly seasonal and mostly confined to the areas of application. For urban and cropland geoengineering, the global effects are minor but, because of being colocated with areas of human activity, they may provide some regional benefits. Global desert geoengineering, which is associated with significant global-scale changes in circulation and the hydrological cycle, causes a smaller reduction in global precipitation per degree of cooling than sunshade geoengineering, 1.1% K −1 and 2.0% K −1 respectively, but a far greater reduction in the precipitation over land, 3.9% K −1 compared with 1.0% K −1. Desert geoengineering also causes large regional-scale changes in precipitation with a large reduction in the intensity of the Indian and African monsoons in particular. None of the schemes studied reverse the climate changes associated with a doubling of CO ₂, with desert geoengineering profoundly altering the climate and with urban and cropland geoengineering providing only some regional amelioration at most.

1.1. Urban Albedo Geoengineering

[6] The idea of urban albedo geoengineering has been considered for a number of years in the guise of reducing the heat island effect and helping improve air quality in cities [Pomerantz et al., 1999; Taha et al., 1999]. Urban albedo geoengineering involves enhancing the albedo of urban areas by replacing standard building materials, for roofs and paving, etc., with alternative more reflective (higher-albedo) materials or by adding a more reflective coating [Akbari et al., 2009; Bretz et al., 1998]. Achievable increases in the albedo of roofing and paving of 0.1-0.4 and 0.15-0.25, respectively, have been estimated, equivalent to an average increase in urban albedo of 0.1 [Akbari et al., 2009]. An alternative estimate of the potential increase in albedo of 0.15 was made by Hamwey [2007], which remains within the range considered by Akbari et al. [2009]. There is a larger range for the estimates of the fraction of the Earth's surface that is covered by suitable urban areas. Hamwey [2007] estimates the suitable urban area at 0.64% of the Earth's surface, from an assumed urban area per capita; Akbari et al. [2009]estimate 0.29% on the basis of the Global Rural-Urban Mapping Project (GRUMP) urban extent data set [Global Rural-Urban Mapping Project (GRUMP), 2005]; however, Lenton and Vaughan [2009] caution that other satellite data indicated the urban area could be as low as 0.051% [Hansen et al., 2000; Loveland et al., 2000]. We take the estimates of potential albedo increase and urban extent from Akbari et al. [2009] as the basis for our simulations because of the availability of the GRUMP data set and the moderate estimate of potential albedo increase.

1.2. Crop Albedo Geoengineering

[7] Biogeoengineering or crop albedo geoengineering would involve growing crop plant varieties with a higher albedo than currently grown as a means to produce a cooling of the planet. Crop albedo is often higher than the albedo of natural vegetation, for example, barley, at European latitudes, has a higher albedo (0.23) than deciduous (0.18) or coniferous (0.16) woodland [Monteith and Unsworth, 1990]. Hence the spread of agriculture has historically led to a modification of the albedo properties of the Earth's surface [Betts et al., 2007; Costa et al., 2007], which has cooled the Earth by an estimated 0.17°C [Matthews et al., 2003]. The albedo of different varieties of a single crop species also differs, depending on, for example, the properties of the leaf wax, the "hairiness" of the leaves and the morphology of the leaf canopy [Febrero et al., 1998; Hatfield and Carlson, 1979; Holmes and Keiller, 2002]. It has been proposed that these properties could be managed to increase the overall albedo of both grassland (pasture) [Hamwey, 2007] and cropland [Ridgwell et al., 2009], although recent analysis of a sample of soybean isolines concluded that existing variability may not be as great as previously assumed [Doughty et al., 2011].

[8] There are various proposals for the types of areas suitable for crop albedo modification and a range of estimates for the potential increase in albedo. Hamwey [2007] suggests that all grassland (cropland, pasture, and wild grassland) could be modified and that the albedo could be increased by 25% (+0.0425), Lenton and Vaughan [2009] calculated that when applied to all grassland (∼7.5% of the Earth's surface) a radiative forcing of −0.51 W m −2 would be achieved. Ridgwell et al. [2009] and Doughty et al. [2011] propose only albedo increases to cropland and suggest albedo increases with ranges of 0.02-0.08 and 0.05-0.15, respectively. We adopt the range of Ridgwell et al. [2009] as it represents a midsized scheme and uses a similar model.

1.3. Desert Albedo Geoengineering

[9] Finally, desert albedo geoengineering involves the laying of highly reflective material across the extensive desert areas of the world to increase the average planetary albedo [Gaskill, 2004]. Suggestions for achieving this include laying and cleaning some form of reinforced plastic sheeting by automated vehicles, covering an estimated 11.7 million km ² of suitable desert [Gaskill, 2004]. The area of deserts that could be suitable for this type of geoengineering cover ∼2% of the Earth's surface, and the albedo increase proposed is from ∼0.36 to ∼0.8. This scheme would produce the greatest radiative forcing and cooling of the different surface albedo schemes compared in this paper [Lenton and Vaughan, 2009]. We adopt this scheme for desert albedo geoengineering, which represents the most extreme example of localized surface albedo modification suggested.

1.4. Summary and Paper Outline

[11] To address this, we have carried out a GCM analysis of all three main SAM schemes, using the same model and the same methodology, presenting GCM results for desert geoengineering for the first time. This allows us to directly compare the three schemes side by side and to explore the relative seasonal and regional impacts that will be very important for these spatially heterogeneous schemes.

[13] This paper continues with a methodology, results section, and a discussion and conclusion section. Section 3 is split into global effects, European summer changes, monsoon changes, and Arctic changes. The discussion and conclusion will deal with the implications of the results presented.

2.1. Urban Albedo Modification

[19] Urban albedo geoengineering has the smallest potential radiative forcing of the three different SRM interventions considered here, and in a previous GCM analysis no statistically significant changes in the climate were recorded [Oleson et al., 2010]. To test whether any feasible implementation of urban albedo enhancement would even be observable (let alone provide significant climate mitigation) and to allow us to fully elucidate the characteristics of the resulting changes in climate, we assumed an upper estimate of the area to which increased albedo could be applied. In this, we used the Global Rural-Urban Mapping Project (GRUMP) data set of urban extent [GRUMP, 2005] to determine the fraction of each model grid cell that is "urban." The total urban area recorded in the GRUMP urban extent map is 3.5 × 10 ⁶ km ², or 0.68% of the Earth's area, which, after regridding onto the HadCM3 land grid ( Figure 1b), becomes 2.8 × 10 ⁶ km ², or 0.56% of the Earth's area (and 1.9% of total land area). The difference is a consequence of the relatively low resolution of HadCM3 and consequent loss of some coastal urban areas in the gridding process.

[20] We followed the methodology of Akbari et al. [2009], assuming 35% of the urban area is paved and 25% is roofing, and applied albedo enhancement to these two surfaces, leaving the other 40% unchanged. From the estimates of Akbari et al. [2009], we tested three levels of albedo increases to roofing and paving (which on average have an albedo estimated at around 0.2 and 0.1, respectively): (1) a maximum increase of 0.35 and 0.25, respectively, (2) a moderate increase of 0.25 and 0.15, respectively, and (3) a small increase of 0.15 and 0.1, respectively. The overall increase in snow-free albedo applied is shown in Table 1. Urban areas at higher latitudes are often snow covered in winter months and so a change to the deep-snow albedo in the model was also applied ( Table 1). The effect of albedo increases in urban areas will affect the deep-snow albedo but only insofar as the underlying surface is exposed. Although the MOSES 1 land surface scheme [Cox et al., 1999] used here does not have an urban land type, MOSES 2.2 does [Essery et al., 2003]. We hence used the values for snow-free and deep-snow albedo from MOSES 2.2 to calculate the exposed fraction:

where α usis the recorded deep-snow albedo of urban areas, f is the fraction of exposed urban surface, 1 − f is the fraction of snow coverage, α uis the snow-free urban albedo, and α sis the deep-snow albedo in the open. In MOSES 1, deep-snow α s has an albedo of 0.8, and the urban albedo values from MOSES 2.2 are 0.4 for α us and 0.18 for α u [Wiscombe and Warren, 1980]. On this basis, fwas found to be 0.645, and so the deep-snow albedo increase applied to urban areas is f(Δ α u); the full list of albedo modifications can be found in Table 1.

2.2. Crop Albedo Modification

[21] Crop albedo geoengineering has been tested in HadCM3 by Ridgwell et al. [2009] and Singarayer et al. [2009] and in CAM 3.0 by Doughty et al. [2011]. We follow a methodology similar to that of both Ridgwell et al. [2009] and Singarayer et al. [2009], apart from using the MOSES 1 land surface scheme rather than MOSES 2.1, used in these studies, in order to provide consistency with the other simulations presented in this paper. We adopt the same definition of crop extent, with the crop area being defined as C3 or C4 grasses that are within human-controlled or disturbed areas as defined by theWilson and Henderson-Sellers [1985]land-type data set. The total area covered by crops is 15.7 × 10 ⁶ km ², 3.1% of the Earth's surface area or 10.6% of the land area ( Figure 1a). To these areas we apply an increase in snow-free albedo dependent on the fractional crop coverage in the grid cell.

2.3. Desert Albedo Modification

[23] Desert geoengineering represents the most extreme local albedo modification of the surface albedo modification schemes considered, and we explore the effects of different spatial extents instead of exploring different levels (intensities) of implementation. In an account of a U.S. Department of Energy (DOE) meeting on geoengineering, Gaskill [2004] estimates a possible albedo of 0.8 for commercially available coverings and that an estimated 11.7 × 10 ⁶ km ² would be suitable for this application. We take these estimates as the basis for our extreme case of what is possible for desert geoengineering.

[24] We generated a definition for desert areas, based on a combination of observed precipitation and fractional vegetation cover at the resolution of HadCM3, designed to roughly match the estimated total area of that given by Gaskill [2004]. If a grid cell receives on average precipitation of less than 250 mm yr −1, as calculated from the CRU (Climate Research Unit, University of East Anglia) reanalysis data for the period 1961-1990, then it is classed as desert. We also specified that a grid cell must be less than 50% covered in vegetation, as defined by the Wilson and Henderson-Sellers land-type data set [Wilson and Henderson-Sellers, 1985], before it was considered suitable for desert geoengineering ( Figure 1c). This simple method does not capture all desert regions (notably, no deserts are identified in North America) but our method does produce a total area (9.1 million km ²) close to the estimate (11.7 million km ²) of Gaskill [2004]. The albedos of the desert grid cells are adjusted to

where the albedo α is dependent on the vegetated fraction f, α ois the original albedo of the grid cell, and 0.8 is the albedo of the reflective covering. The deep-snow albedo was not changed as the properties of snow deposited on a reflective coating would be similar to those of snow on desert regions.

[25] Three experiments were run to explore the effect of applying desert albedo geoengineering in different regions (see Figure 1c): (1) in which all desert regions were modified ("Global"), (2) modification of only the Sahara desert ("Sahara"), (3) in which only Asian deserts, i.e., from Saudi Arabia and the Middle East eastward, are modified ("Asian").

3.1. Global Effects

[30] The impacts on global and land-averaged temperatures and precipitation for each geoengineering scheme, as well as the effect of unmitigated global warming, are summarized in Table 2. At doubled CO ₂ there is a global average increase in surface air temperature of +3.0°C and an increase in precipitation of +4.0%. On land, the annual average temperature change is amplified (+4.2°C) whereas the precipitation enhancement is reduced (down to +1.8%). Global-average warming is not completely reversed by any SAM scheme, with urban geoengineering having the potential to cool on a global annual average basis by a maximum of 0.11°C, crop geoengineering by 0.23°C, and (global) desert geoengineering by 1.12°C, with the amount of cooling determined by the assumed degree of geoengineering intervention.

Urban Low, 2 × CO ₂

−0.05

−0.04
−0.10
0.20

Crops Low, 2 × CO ₂

−0.05

0.01
−0.11
0.12

[31] Changes in the radiative forcing of the planet affect the hydrological cycle in two ways: There is a "slow" or temperature-driven component that does not depend on the details of the radiative forcing mechanism, and there is a "fast" atmospheric adjustment component that differs between radiative forcing mechanisms [Andrews et al., 2010]. The slow temperature response has been found to cause around a 2%-3% change in precipitation for every degree Kelvin of temperature change, with precipitation increasing with rising temperatures [Lambert and Webb, 2008]. Our simulations show that sunshade geoengineering caused a 2.0% K −1 reduction in precipitation, whereas global desert geoengineering caused only a 1.1% K −1 reduction (we exclude urban and crop geoengineering as a statistically significant change in global average precipitation was not found). For comparison, a study on cloud albedo geoengineering (which increases albedo over ocean areas only) caused a 2.5% K −1 reduction in global average precipitation [Bala et al., 2010]. The different global precipitation responses of these geoengineering schemes are a result of the differing availability of moisture for evaporation in the regions affected, i.e., ocean regions have an infinite supply of water for evaporation whereas the continents do not. Thus, the effect of a reduction in incoming sunlight on the surface energy budget of the ocean will consist of a change in the latent and sensible heat fluxes, leading to a large reduction in evaporation, whereas over the land this will consist mainly of a change in sensible heat flux, with a smaller reduction in global evaporation.

[32] However, the change in continental precipitation shows an opposite result to this global picture; desert geoengineering has the largest reduction at 3.9% K −1, sunshade geoengineering shows 1% K −1, and cloud albedo geoengineering shows 0.9% K −1. This difference in continental precipitation arises from changes in circulation that redistribute the precipitation. This change in distribution has a greater effect on continental precipitation than does the change in the atmospheric moisture availability that controls global precipitation.

[33] The patterns of annual mean surface temperature change are shown in Figure 2. For unmitigated climate change ( Figure 2a), warming occurs everywhere, with greater warming toward the poles and over the land areas. As one would expect, SAM geoengineering does not produce a uniform cooling. Furthermore, in some areas, statistically significant warming (in addition to the impact of 2 × CO ₂) occurs under each of the different geoengineering interventions, probably as a result of changes in circulation patterns, i.e., diverting warm currents of air to high-latitude areas. An example of this is the Southern Ocean around Tasmania, which is warmer for all three SAM geoengineering schemes. In contrast, sunshade geoengineering produces a relatively uniform cooling across the world compared with the surface albedo geoengineering schemes, with land areas and high-latitude areas cooled more than others, reversing most of the warming from 2 × CO ₂.

[34] For urban geoengineering, we find a statistically significant cooling across most continental areas. This is in contrast to the results of Oleson et al. [2010], who did not find any statistically significant cooling as a result of a global reduction in urban albedo. This difference is likely to be partly due to the more extreme implementation we have assumed (and focused on the results of), together with the greater urban coverage assumed in our data set. We have also employed a longer averaging period: 100 years here compared with 58 years in the simulations of Oleson et al. [2010], and hence we are better able to identify small changes in climate against the background of modeled interannual variability. We find the largest cooling in Europe, North America, and in the Arctic, a consequence of the relatively large urban coverage of both Europe and North America ( Figure 1b). This regional cooling is amplified by positive cryospheric feedbacks operating in the high latitudes, particularly because of changes in sea-ice extent (see section 3.4).

[35] Crop albedo geoengineering exhibits a pattern of cooling ( Figure 2c) to a first order similar to urban geoengineering ( Figure 2b), with most of the cooling occurring in the Northern Hemisphere. This similarity between crop and urban albedo is due to the coexistence of greatest crop cover and urban fraction (population) in most regions ( Figures 1a and 1b). Consistent with the results of Singarayer et al. [2009], our results show that crop albedo geoengineering results in the greatest cooling across Eurasia and North America. We also find less cooling than may be expected in South and East Asia, an area with significant crop coverage, a result of an associated reduction in cloud cover in the region [Doughty et al., 2011; Singarayer et al., 2009]. Some warm anomalies are also induced, for example in the Barents Sea, but are not found consistently in the moderate or weak implementations of crop geoengineering and are therefore perhaps a result of long-term climate variability.

[36] Although global desert geoengineering has the potential to generate the largest global average cooling effect, this average masks the fact that most of the 1.12°C cooling is highly concentrated over the desert regions where the albedo increase is applied (compare Figures 2d and 1c). For example, global desert geoengineering causes some areas of the Sahara to be greater than 10°C cooler than in the preindustrial ( Figure 2f). A pronounced general cooling of most continental areas, of between 1.5°C and 2°C over most of Eurasia and North America also occurs, with the notable exception being India, which becomes slightly warmer despite being proximal to a number of desert areas. This warming in India can be explained by cloud feedbacks with an ∼10% reduction in cloud cover in the region (not shown). As with crop and urban geoengineering, the Northern Hemisphere tends to be cooled more than the Southern Hemisphere, a simple consequence of the presence of much greater land coverage in the north.

[37] Sunshade geoengineering produces a much more uniform cooling than the SAM schemes, with noticeably greater cooling in the Northern Hemisphere and the Arctic ( Figure 2e), but does not reproduce the preindustrial temperature distribution; with the low latitudes cooler than in the preindustrial and the high latitudes warmer ( Figure 2g). This difference in temperature is due to the greenhouse forcing acting to slow the loss of heat, which warms the Arctic more, and the reduced solar forcing, which has a greater role in the energy budget at low latitudes, acting to cool the tropics.

[38] In contrast to the response of surface air temperature, which is strongest at the sites of SAM geoengineering, changes in precipitation are much more heterogeneous ( Figure 3). Doubling CO ₂ leads to large regional changes in precipitation, with some areas becoming much drier, e.g., the Amazon, South Africa, and Australia, and others becoming much wetter, e.g., South Asia and equatorial Africa, but with an overall increase in precipitation (see Figure 3a and Table 2). For both urban and crop albedo geoengineering, only minimal shifts in precipitation occur, with the exception of equatorial Pacific regions ( Figures 3b and 3c), whereas desert geoengineering induces quite extreme changes in precipitation patterns throughout the tropics and subtropics ( Figure 3d).

[39] Urban and crop albedo techniques generally induce only small changes in precipitation, with few areas that exhibit a statistically significant change ( Figures 3b and 3c). The changes in precipitation that do occur are consistent with a small southward shift of the (Intertropical Convergence Zone (ITCZ), which is induced by an unequal change in the temperature between the Northern and Southern Hemispheres. Both schemes also result in slightly altered precipitation patterns around southeast Asia, the Indian Ocean, and Australasia, changes that are more marked with crop albedo geoengineering than urban. These changes in precipitation are due to changes in evaporation that occur locally and changes in circulation that redistribute rainfall.

[40] Our prescribed enhancement of desert albedo induces shifts in precipitation patterns ( Figure 3d) of comparable magnitude to those that arise from doubling CO ₂ levels alone (i.e., unmitigated climate change) ( Figure 3a). The most prominent changes occur in monsoonal regions such as sub-Saharan Africa, Southeast Asia, and Australia, where the decrease in rainfall leaves these regions drier than in the preindustrial simulation ( Figure 3f). Northern South America and Central America experience increases in precipitation that are sufficient to reverse the drying caused by doubling CO ₂.

[41] In comparison, sunshade geoengineering produces a reduction in precipitation in most regions relative to 2 × CO ₂, with some large positive and negative anomalies in the tropics ( Figure 3e). When compared with preindustrial areas, few regions experience statistically different precipitation, with exceptions occurring mostly in the tropics ( Figure 3g).

[42] The climatology of the HadCM3 model employed here reproduces many of the first-order features of the global climate system but, as with all models, is not perfect, and HadCM3 has some specific deficiencies that should be borne in mind when considering the results presented here:

[43] Although HadCM3 reproduces the global patterns of surface air temperature, it exhibits a cold bias at high latitudes in the Northern Hemisphere, which is particularly pronounced in Russia, east of Scandinavia, and the coarse-resolution orography leads to local and remote biases [Gordon et al., 2000]. The performance for precipitation is generally less good; the observed global patterns are captured, but significant biases exist: The South Pacific Convergence Zone extends farther and in a more easterly direction than observed (the "double ITCZ" problem), there is a strong wet bias around the maritime continent, and there is a dry bias in India and the northern Amazon region [Solomon et al., 2007].

[44] HadCM3, as with other GCMs, also fails to reproduce the temporal structure of observed"para42" precipitation, with simulated precipitation occurring too frequently and at lower intensity than observed.

3.2. European Summertime Changes

[45] Europe is a highly urbanized region with significant areas of agricultural land. It is also a region that experiences periodic damaging heat waves, with the 2003 heat wave causing an estimated 70,000 deaths [Robine et al., 2008]. Climate model projections suggest that average European summer temperatures as warm as in 2003 may become the mean state by the end of the 21st century, with significant implications for human health, energy consumption (air conditioning), and agriculture in the region [Stott et al., 2004]. Thus, Europe is one of the regions that may potentially benefit most from the application of land albedo geoengineering [Singarayer et al., 2009], with the strongest cooling effect tending to be exerted over the summer months, which should ameliorate some of the effects of extremely warm summers. Because of the relatively large fraction of the land occupied by urban areas and cropland, Europe will experience a cooling significantly greater than the global average [e.g., Ridgwell et al., 2009] under these albedo modification schemes.

[46] To examine the effect of SAM geoengineering on the climate of Europe, we examine results for interannual variability in average annual and summer (June, July, and August (JJA)) temperatures across the region of Western Europe (defined as in Figure 4e). Table 3 summarizes the annual and summer temperature anomalies for the different geoengineering schemes for this region. At 2 × CO ₂ there is an increase of 4.18°C in the annual temperature across the region, with a larger increase in summer (5.03°C).

[47] Against the greenhouse warming of 2 × CO ₂, urban geoengineering produces a cooling of 0.50°C annually and 0.57°C in summer for maximum deployment. For urban geoengineering there is a larger cooling for the lowest deployment than for a moderate deployment, which is likely a result of internal variability in the model. Crop albedo geoengineering is more effective than urban geoengineering in Europe, with a maximum deployment cooling by 0.83°C annually and 1.26°C in summer. Desert albedo geoengineering, applied globally, exerts a cooling of 1.55°C annually and 1.53°C in summer across the region.

[48] Rather counterintuitively, desert geoengineering restricted to the Sahara has less of a cooling effect in Europe than when it is restricted to Asia, the consequence of large changes in circulation that occur (see Figure 6). Desert geoengineering cools air locally but this air does not simply diffuse from the desert regions; instead, it is advected in a complicated manner by the patterns of circulation, which are also modified by desert geoengineering.

[49] Figure 4 shows how the frequency distribution of summer average temperatures over western Europe is affected by SAM geoengineering. At 2 × CO ₂ there is a much warmer summer (∼5°C warmer than the preindustrial on average), and during the 100 year period analyzed, all summers were warmer than the warmest preindustrial summer. A number of particularly warm summers also occur; four times with an average temperature above 23°C and once with an average temperature between 24°C and 25°C. High urban geoengineering ( Figure 4a) lowers the average summer temperature by ∼0.6°C, reducing the number of extremely warm summers. Crop albedo geoengineering ( Figure 4b) is more effective, and the greatest intervention lowers average summer temperatures by 1.3°C. With global desert geoengineering ( Figure 4c) there is a cooling in the summer of 1.5°C and a reduction in the number of extremely warm summers.

[50] The simulation of European surface air temperature in HadCM3 suffers from a cold bias of around 1°C-2°C in this region. Stott et al. [2004]found that internal variability in European summer temperatures in HadCM3 is similar to observed values, but the model might overestimate variability somewhat (note, however, that the region they defined differs from ours). In simulations of European climate with Regional climate models driven by HadAM3H (a high-resolution atmosphere-only version of HadCM3), it was found that higher resolution orography could improve the spatial patterns of surface air temperature but that problems with land surface schemes and the driving GCM's representation of blocking highs affected the surface air temperature variability [Jacob et al., 2007]. These problems with the land surface schemes and with blocking highs affect our model and hence our results. However, despite these problems, these results reveal the important local and seasonal effects of these SAM geoengineering schemes.

3.3. Monsoon Changes

[51] As was noted earlier, global desert geoengineering may cause large changes in precipitation patterns around the world, particularly in monsoon regions such as India, sub-Saharan Africa, and Australia, because of the mechanism that drives monsoon circulations: seasonal land-sea temperature differences. In the normal sequence of events, during the summer months continental areas warm faster than ocean areas, creating a pressure difference: this causes air to circulate, with warm, dry air rising over the continents being replaced by cooler, moist air from the ocean. In winter the opposite occurs as the oceans retain the heat collected over the summer for longer than the land does. With desert geoengineering, there is a large change in albedo of the continental land surface, resulting in cooler summer temperatures, which reduce monsoon circulation locally and lead to significant changes in regional precipitation patterns and also changes in global circulation patterns.

[52] Figure 5a shows the difference between June, July, August (JJA) and December, January, February (DJF) rainfall for the preindustrial. The monsoon systems have a positive difference in precipitation in the north and a negative difference in the south, i.e., greater rainfall in the summer relative to the winter in their respective hemispheres. Figure 5b shows the changes in precipitation seasonality between 2 × CO ₂ and preindustrial; there is an intensification of the seasonality of rainfall in Southeast Asia and Indonesia and a reduction in the Amazon region and around the Caribbean. For both urban and crop geoengineering, we find few statistically significant changes in the seasonality of rainfall and so these results are not shown here. For global desert geoengineering, there is a large reduction in monsoonal rains in areas neighboring the modified desert areas ( Figures 5c-5e). Global desert geoengineering reduces the intensity of the Indian, East Asian, North African, and Australian monsoons but intensifies seasonal rains in Central and South America relative to 2 × CO ₂ ( Figure 5c). On the whole there is a large reduction in summer continental rainfall across the tropics compared with that of the preindustrial ( Figure 5g).

[53] Restricting desert albedo modification to the Sahara ( Figure 5f) reduces the intensity of the North African monsoon and to a lesser extent the Asian monsoon, whereas Asian desert geoengineering ( Figure 5g) reduces the intensity of the Asian monsoon and, perhaps surprisingly, strengthens the North African monsoon, and both schemes increase summer rainfall over Central and South America.

[54] In comparison, sunshade geoengineering reverses most of the effects that doubling CO ₂ has on precipitation seasonality ( Figure 5f), returning the seasonality of precipitation very close to the preindustrial precipitation, with few statistically significant changes ( Figure 5h).

[55] In Figure 6 we show the seasonal changes in 850 hPa winds for global desert geoengineering alongside the changes in precipitation. Desert geoengineering profoundly changes the atmospheric circulation ( Figures 6a and 6b), with the most extreme changes occurring in the Northern Hemisphere summer, when the desert albedo changes have their greatest effect (compare Figures 6a and 6b). The altered patterns of precipitation ( Figures 6c and 6d) correlate well with changes in 850 hPa wind, i.e., there are changes in moisture advection driven by the changes in the winds. This can be seen, for example, along the Ivory Coast, where a large reduction in JJA rainfall coincides with a seaward wind anomaly (i.e., a reduction in monsoonal, landward winds), and in Central America, where the increase in JJA rainfall coincides with an increase in Pacific to Atlantic winds over the isthmus ( Figures 6a and 6c). In Australia, where there are reductions in precipitation, an anticyclonic anomaly in 850 hPa wind during the Austral summer (DJF) acts to reduce the advection of moisture into the north of the continent ( Figures 6b and 6d). In general, desert albedo geoengineering leads to a disruption of precipitation locally and remotely through changes in circulation and therefore in moisture advection.

[56] We identify six different areas of interest that may be affected significantly by desert geoengineering ( Figure 7g). The percentages of change in average annual precipitation for each of these six regions under different geoengineering scenarios are summarized in Table 4. Brazil experiences a large decrease in precipitation at 2 × CO ₂ compared to preindustrial, and all the geoengineering schemes increase precipitation in Brazil, with global desert geoengineering returning precipitation to just above the preindustrial value.

Urban High, 2 × CO ₂
4.6
0.7

−0.2
−3.8
−1.7

4.7

Crops High, 2 × CO ₂
6.8
0.5

−0.4
−9.8 −2.3
2.3

Sahara Desert, 2 × CO ₂
10.8 −33.4 −19.1 −12.5 −4.8
−2.8

[57] In the two African regions considered there are small increases in precipitation at 2 × CO ₂, and for crop and urban geoengineering there is little effect on average precipitation. Global and Saharan desert geoengineering causes large decreases in precipitation in the Sahel and Ivory Coast regions, whereas Asian desert geoengineering causes a large increase in the Sahel band.

[58] In India and Southeast Asia there are moderate increases in precipitation at 2 × CO ₂; both crops and urban geoengineering reduce rainfall in these regions, particularly in India, although it remains above the preindustrial value. Global desert geoengineering decreases rainfall in India significantly and in Southeast Asia to some extent, with a 37% reduction in rainfall, relative to preindustrial in India, and a 6% decrease in Southeast Asia.

[59] Australia experiences a reduction in precipitation at 2 × CO ₂, and most geoengineering schemes considered increase precipitation in Australia, whereas global desert geoengineering (which includes an Australian component) produces an 18% reduction in rainfall compared with the preindustrial.

[60] Variability in monsoon rainfall is also an important indicator of change; Figure 7 shows frequency plots for annual precipitation over India (in Figure 7g the Indian region is shaded blue). The rainfall distribution changes from preindustrial to 2 × CO ₂ with average rainfall up 15% and fewer dry years. Figure 7a shows that urban geoengineering reduces the rainfall over India slightly, returning the distribution somewhat closer to its preindustrial state. Crop geoengineering has a larger impact, returning the mean rainfall over India close to preindustrial values but broadening the distribution ( Figure 7b).

[61] The desert geoengineering schemes applied globally, in the Sahara, and in Asia, all reduce Indian rainfall, resulting in a 37% reduction, no statistically significant change, and an 18% reduction relative to the preindustrial, respectively ( Figures 7c-7e). For global desert geoengineering the wettest years are below the preindustrial mean and, in the driest years, India receives less than 300 mm of rain, down from more than 500 mm in the preindustrial. Asian desert geoengineering has a significant drying effect, whereas Sahara desert geoengineering returns the distribution close to that of the preindustrial state.

[62] Dabang et al. [2005]assessed some of the models used in the Coupled Model Intercomparison Project 3 (CMIP3) for their performance in reproducing the East Asian monsoon and found that all models had difficulties reproducing the observed behavior but that HadCM3 was one of the better models. They found that while HadCM3 overestimated precipitation in all seasons, the distribution of precipitation was similar to that of observations, and although the winter was too cold, the surface air temperature was well reproduced. These problems and others affect the quality of the monsoon results shown, and so the details of the results must be viewed with caution. However, because of desert geoengineering directly affecting the seasonal land-sea temperature difference, the driver of monsoon circulation, the general result of reduced rainfall near modified desert regions is likely to be robust.

3.4. Arctic Changes

[63] The Arctic is a region that is warming faster than the rest of the world, as a result of global warming [IPCC, 2007]. Although the exact mechanisms are uncertain, retreating sea ice and, to a lesser extent, changes in snow cover are likely to be involved [Screen and Simmonds, 2010]. The Arctic is home to large reservoirs of stored carbon, as decayed plant matter in permafrost and methane reserves in hydrates, which could provide an additional (carbon cycle) positive feedback [Archer, 2007]. We focus on the Arctic here for these reasons as well as the fact that it is remote from all the SAM schemes and hence illustrates the potential for nonlocal impacts (and teleconnections) arising from land albedo geoengineering.

[64] Figure 8shows the simulated preindustrial sea-ice and snow coverage for the Northern Hemisphere and the effects of doubling CO ₂ and geoengineering on sea ice and snow. Comparing Figures 8a and 8b, it can be seen that the sea-ice extent and thickness are reduced at 2 × CO ₂compared to preindustrial, with minimum sea-ice cover (September average) reduced by 71% ( Figure 8c). The change in snow depth is more spatially heterogeneous, with snow loss at midlatitudes but an increase in snow depth at high latitudes. At high latitudes the increase in snow accumulation outweighs the increased losses that are due to higher temperatures, and with a greater fraction of the Arctic Ocean ice free there will be more evaporation and consequently greater snowfall (the increase in precipitation is shown in Figure 3a). The snow depth projections for Greenland are omitted as the model does not include an ice sheet module and so cannot simulate changes in this region reasonably.

[65] Figures 8c and 8dshow that urban and cropland geoengineering induce a slight recovery of annual mean sea-ice thickness, with 13% and 20% increases, respectively, in minimum sea-ice cover (September average) relative to 2 × CO ₂and a very small effect on snow depth. Desert geoengineering exerts a more substantial effect on annual mean sea-ice thickness, with a 65% increase in minimum sea-ice cover relative to 2 × CO ₂, which remains 53% lower than the preindustrial coverage. Desert geoengineering also has a large impact on snow depth, with almost the opposite spatial pattern to that of 2 × CO ₂; i.e., desert geoengineering cools and dries the Northern Hemisphere, partly reversing the trend induced by global warming.

[66] Again, projections of effects of geoengineering on climate must be viewed in the context of the degree of fidelity of the climate model used: HadCM3 has a number of biases in the climate state of high northern latitudes that will affect the results shown in this section, the most important of which is a cold bias [Gregory et al., 2002]. HadCM3 also has a wet bias at high latitudes that will affect the quality of the snow cover results [Solomon et al., 2007]. There are problems in the sea-ice climatology of HadCM3 but the model does roughly reproduce the 20th-century trend in sea ice [Gregory et al., 2002] and matches the projections of other AOGCMs, predicting a large decline in summer sea-ice extent over the course of the 21st century [Johannessen et al., 2004]. However, the results shown are consistent with the cooling of the SAM schemes being concentrated in the Northern Hemisphere and show that SAM geoengineering may help to reduce Arctic climate change somewhat.

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Keywords

climate change;

climate engineering;

crop albedo;

desert albedo;

geoengineering;

urban albedo

Publication History

Issue online:

Version of record online:

Manuscript Accepted:

Manuscript Revised:

Manuscript Received:

Funded by

NERC. Grant Number: PhD studentship

EPSRC. Grant Number: EP/I014721/1

RCUK. Grant Number: Fellowship

Supporting Information

Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

References

Bala, G., K. Caldeira, R. Nemani, L. Cao, G. Ban-Weiss, and H.-J. Shin (2010), Albedo enhancement of marine clouds to counteract global warming: Impacts on the hydrological cycle, Clim. Dyn., 6, 1-17.

Caldeira, K., and L. Wood (2008), Global and Arctic climate engineering: Numerical model studies, Philos. Trans. R. Soc. A, 366(1882), 4039-4056.

Cao, L., and K. Caldeira (2008), Atmospheric COGeophys. Res. Lett., 35, L19609, doi:₂ stabilization and ocean acidification, 10.1029/2008GL035072.

Cattle, H., and J. Crossley (1995), Modeling Arctic climate-change, Philos. Trans. R. Soc. A, 352(1699), 201-213.

Commission of European Communities (2007), Limiting global climate change to 2 degrees Celsius: The way ahead for 2020 and beyond, Pap. 52007DC0002, 13 pp., Comm. of European Communities, Brussels.

Cox, P. M., R. A. Betts, C. D. Jones, S. A. Spall, and I. J. Totterdell (2000), Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model, Nature, 408(6809), 184-187, doi:10.1038/35041539.

Essery, R. L. H., M. J. Best, R. A. Betts, P. M. Cox, and C. M. Taylor (2003), Explicit representation of subgrid heterogeneity in a GCM land surface scheme, J. Hydrometeorol., 4(3), 530-543, doi:10.1175/1525-7541(2003)004<0530:EROSHI>2.0.CO;2.

Gaskill, A. (2004), Summary of meeting with US DOE to discuss geoengineering options to prevent long-term climate change, Environ. Ref. Mater., Inc., Research Triangle Park, N. C.

Global Rural-Urban Mapping Project (GRUMP) (2005), Gridded Population of the World and the Global Rural-Urban Mapping Project Data Set, http://sedac.ciesin.columbia.edu/gpw/, Socioecon. Data and Appl. Cent., Palisades, N. Y.

Irvine, P. J., D. J. Lunt, E. J. Stone, and A. Ridgwell (2009), The fate of the Greenland Ice Sheet in a geoengineered, high COEnviron. Res. Lett., 4(4), 045109, doi:10.1088/1748-9326/4/4/045109.₂ world,

Johannessen, O. M., et al. (2004), Arctic climate change: Observed and modelled temperature and sea-ice variability, Tellus Ser. A, 56(4), 328-341.

Johns, T. C., et al. (2003), Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emissions scenarios, Clim. Dyn., 20(6), 583-612.

Lambert, F. H., and M. J. Webb (2008), Dependency of global mean precipitation on surface temperature, Geophys. Res. Lett., 35, L16706, doi:10.1029/2008GL034838.

Robock, A., L. Oman, and G. L. Stenchikov (2008), Regional climate responses to geoengineering with tropical and Arctic SOJ. Geophys. Res., 113, D16101, doi:10.1029/2008JD010050.₂ injections,

Salter, S., G. Sortino, and J. Latham (2008), Sea-going hardware for the cloud albedo method of reversing global warming, Philos. Trans. R. Soc. A, 366(1882), 3989-4006.

Shepherd, J., et al. (2009), Geoengineering the Climate: Science, Governance and Uncertainty, RS Policy Doc. 10/09, Royal Soc., London.

Smith, R. N. B. (1993), Experience and developments with the layer cloud and boundary layer mixing schemes in the UK Meteorological Office Unified Model, paper presented at the ECMWF/GCSS Workshop on Parameterisation of the Cloud-Topped Boundary Layer, Eur. Centre for Medium-Range Weather Forecasts, Reading, U. K.

Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, and H. L. Miller (2007), Climate Change 2007: The Physical Science Basis: Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by D. Q. S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K.

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Climate and Dynamics

Authors

Peter J. Irvine,

Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK
Search for more papers by this author

Andy Ridgwell,

Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK
Search for more papers by this author

Daniel J. Lunt

Bristol Research Initiative for the Dynamic Global Environment, School of Geographical Sciences, University of Bristol, Bristol, UK
Search for more papers by this author

Urban Low, 2 × CO ₂

−0.05

−0.04
−0.10
0.20

Crops Low, 2 × CO ₂

−0.05

0.01
−0.11
0.12

Urban High, 2 × CO ₂
4.6
0.7

−0.2
−3.8
−1.7

4.7

Crops High, 2 × CO ₂
6.8
0.5

−0.4
−9.8 −2.3
2.3

Sahara Desert, 2 × CO ₂
10.8 −33.4 −19.1 −12.5 −4.8
−2.8

Ancillary

Article Information

Format Available

Full text: HTML | PDF

Copyright 2011 by the American Geophysical Union
Request Permissions

Keywords

climate change;

climate engineering;

crop albedo;

desert albedo;

geoengineering;

urban albedo

Publication History

Issue online:

Version of record online:

Manuscript Accepted:

Manuscript Revised:

Manuscript Received:

Funded by

NERC. Grant Number: PhD studentship

EPSRC. Grant Number: EP/I014721/1

RCUK. Grant Number: Fellowship

Supporting Information

Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

References

Bala, G., K. Caldeira, R. Nemani, L. Cao, G. Ban-Weiss, and H.-J. Shin (2010), Albedo enhancement of marine clouds to counteract global warming: Impacts on the hydrological cycle, Clim. Dyn., 6, 1-17.

Caldeira, K., and L. Wood (2008), Global and Arctic climate engineering: Numerical model studies, Philos. Trans. R. Soc. A, 366(1882), 4039-4056.

Cao, L., and K. Caldeira (2008), Atmospheric COGeophys. Res. Lett., 35, L19609, doi:₂ stabilization and ocean acidification, 10.1029/2008GL035072.

Cattle, H., and J. Crossley (1995), Modeling Arctic climate-change, Philos. Trans. R. Soc. A, 352(1699), 201-213.

Commission of European Communities (2007), Limiting global climate change to 2 degrees Celsius: The way ahead for 2020 and beyond, Pap. 52007DC0002, 13 pp., Comm. of European Communities, Brussels.

Cox, P. M., R. A. Betts, C. D. Jones, S. A. Spall, and I. J. Totterdell (2000), Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model, Nature, 408(6809), 184-187, doi:10.1038/35041539.

Essery, R. L. H., M. J. Best, R. A. Betts, P. M. Cox, and C. M. Taylor (2003), Explicit representation of subgrid heterogeneity in a GCM land surface scheme, J. Hydrometeorol., 4(3), 530-543, doi:10.1175/1525-7541(2003)004<0530:EROSHI>2.0.CO;2.

Gaskill, A. (2004), Summary of meeting with US DOE to discuss geoengineering options to prevent long-term climate change, Environ. Ref. Mater., Inc., Research Triangle Park, N. C.

Global Rural-Urban Mapping Project (GRUMP) (2005), Gridded Population of the World and the Global Rural-Urban Mapping Project Data Set, http://sedac.ciesin.columbia.edu/gpw/, Socioecon. Data and Appl. Cent., Palisades, N. Y.

Intergovernmental Panel on Climate Change (IPCC) (2007), Climate Change 2007: The Physical Science Basis: Contribution of Working Group 1 to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by D. Q. S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K.

Irvine, P. J., D. J. Lunt, E. J. Stone, and A. Ridgwell (2009), The fate of the Greenland Ice Sheet in a geoengineered, high COEnviron. Res. Lett., 4(4), 045109, doi:10.1088/1748-9326/4/4/045109.₂ world,

Johannessen, O. M., et al. (2004), Arctic climate change: Observed and modelled temperature and sea-ice variability, Tellus Ser. A, 56(4), 328-341.

Johns, T. C., et al. (2003), Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emissions scenarios, Clim. Dyn., 20(6), 583-612.

Lambert, F. H., and M. J. Webb (2008), Dependency of global mean precipitation on surface temperature, Geophys. Res. Lett., 35, L16706, doi:10.1029/2008GL034838.

Monteith, J. L., and M. H. Unsworth (1990), Principles of Environmental Physics, 2nd ed., 291 pp., Routledge, London.

Robock, A., L. Oman, and G. L. Stenchikov (2008), Regional climate responses to geoengineering with tropical and Arctic SOJ. Geophys. Res., 113, D16101, doi:10.1029/2008JD010050.₂ injections,

Salter, S., G. Sortino, and J. Latham (2008), Sea-going hardware for the cloud albedo method of reversing global warming, Philos. Trans. R. Soc. A, 366(1882), 3989-4006.

Shepherd, J., et al. (2009), Geoengineering the Climate: Science, Governance and Uncertainty, RS Policy Doc. 10/09, Royal Soc., London.

Smith, R. N. B. (1993), Experience and developments with the layer cloud and boundary layer mixing schemes in the UK Meteorological Office Unified Model, paper presented at the ECMWF/GCSS Workshop on Parameterisation of the Cloud-Topped Boundary Layer, Eur. Centre for Medium-Range Weather Forecasts, Reading, U. K.

Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, and H. L. Miller (2007), Climate Change 2007: The Physical Science Basis: Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by D. Q. S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K.

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Information on West Nile Virus. Provided by the U.S. Centers for Disease Control and Prevention.

# data[].attributes.attachment_link.readable_text
Mosquitoes carry infectious pathogens, such as the West Nile virus, Dengue fever, Zika virus, and malaria, and transmit them to humans via biting. As the Earth warms due to climate change, more regions can potentially support disease-bearing mosquitoes.

The increase in heat and humidity boosts mosquitoes' reproduction rates, lengthens their breeding season, makes mosquitoes bite more, and speeds the development of the disease-causing agents they carry (bacteria and viruses) to an infectious state.

West Nile virus is found in the U.S. where it is carried by numerous mosquito species. The U.S. has seen an outbreak of West Nile every summer since 1999. About 20 percent of those infected develop fever, body aches, nausea, and swollen lymph glands. More severe reactions include headaches, high fever, tremors, disorientation, convulsions, muscle weakness, coma and paralysis.

"Rising temperatures, changing precipitation patterns, and a higher frequency of some extreme weather events associated with climate change will influence the distribution, abundance, and prevalence of infection in the mosquitoes that transmit West Nile virus and other pathogens by altering habitat availability and mosquito and viral reproduction rates."
- U.S. Global Change Research Program
(see below)

Dengue fever is also mosquito-borne and climate-affected. Each year there are about 100 million cases of dengue worldwide. The Asian Tiger mosquito, which carries the disease, is found in the U.S., but to date has not been found to carry dengue. Mildest symptoms include headaches, severe pain behind the eyes, and joint, muscle, and bone pain. Dengue hemorrhagic fever causes severe abdominal pain and difficulty breathing, and if left untreated, can cause circulatory system failure, shock, and death.

An estimated 219 million cases of malaria worldwide lead to approximately 600,000 deaths annually. Malaria is most prevalent in Africa and parts of Oceania. Recent studies suggest mosquitoes carrying the disease migrate to higher elevations as temperatures rise, placing more people at risk. Symptoms begin with fever, headaches, nausea, and body aches; the disease can progress to cause neurologic abnormalities, severe anemia, acute kidney failure, acute respiratory distress syndrome, and death.

Climate change is not always a factor in outbreaks or spread of mosquito-borne diseases, and the relationship between weather, mosquito habitat and disease risk can be complex. For example, the current outbreak of Zika virus in Latin America and the Caribbean has not been linked by evidence to increased temperatures.

However, if the Zika virus becomes endemic in mosquitoes in the U.S., climate-driven factors will likely come into play.

Over 600 Zika cases have been reported in the U.S. and U.S. territories. They are believed to be travel-acquired or sexually contracted. Health effects are fever, red eyes, rash, and joint pain. If a fetus contracts the virus, it can be born with microcephaly -- a smaller brain that might not have developed properly. This can result in seizures, developmental delays, problems with movement and balance, and decreased ability to learn and function in daily life. These problems range from mild to severe and are often life-long.

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Climate change and insect bourne diseases 

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explains the links between climate change and insect-borne disease, and outlines priorities for developing country policymakers.

Some researchers have called climate change the biggest health threat the world has ever faced. With good reason - it is now an unavoidable truth that the health of the planet is linked to the health of its people.

As the world heats up, ecosystems are visibly struggling to cope with the rapid ecological changes. Global warming has already triggered weather changes - from flooding and storms to heatwaves and drought - that are taking a heavy toll on people's health around the world.

In high-level meetings, developed and developing country governments are busy battling over emission targets. Meanwhile, the world's poor, who bear the biggest disease burdens, can expect soaring rates of ill health.

This increase will come partly from shifting population dynamics, as people flee flooded coasts or searing deserts for more habitable areas. A rise in diseases carried by insects, such as mosquitoes or ticks, could be a key factor. Climate influences these 'vectors' in many ways - from controlling the length of their life cycle to influencing breeding conditions.

Scientists broadly agree that climate change will affect insect-borne diseases, but the exact consequences remain uncertain. Whether warmer, wetter conditions make it easier for vectors such as mosquitoes to multiply and spread disease will depend on a much broader range of ecological and societal factors than just rainfall or temperature.

We urgently need to build our understandingof how climate change will affect health, especially through insect-borne disease. And we must strengthen health systems to deal with the expected changes.

The warming planet

Climate scientists say a rise of up to two degrees Celsius more than pre-industrial global temperatures could be manageable, with people only in specific, vulnerable regions suffering catastrophic environmental effects. Any larger temperature increase puts the whole planet's population at risk.

But sticking to this limit seems impossible. The Intergovernmental Panel on Climate Change predicts that if emissions continue to rise unchecked - they are already 38 per cent higher than in 1990 - the world could warm by as much as four degrees Celsius by 2100 (see Figure 1). [1]

Some of the damage has already been done. The rise in greenhouse gas emissions over the past few decades has already warmed the planet by 0.8 degrees Celsius. The lag between growing emissions and the corresponding increase in temperature means that we can expect at least another 0.6-degree Celsius global temperature rise over the next few decades.

Figure 1: Global warming predictions based on different emission scenarios [2]

Credit: IPCC

And how much we must cut emissions remains unresolved. The G8 meeting of world leaders in July 2009 called for a 50 per cent cut in emissions by 2050. Earlier, in January, the World Economic Forum's Global Agenda Council on Climate Change, in Davos, was more ambitious. It called for a cut of 80 per cent by 2050.

Harmful health effects

Initial concerns about climate change in the early 1990s focused on environmental impacts and all but ignored links with health. But this imbalance is slowly changing as research emerges on the likely effects climate change will have on people's health and the spread of disease.

This year, for example, The Global Humanitarian Forum (GHF) published a report estimating that 315,000 people die due to climate change every year, and they predict this will rise to half a million by the year 2030. [3] While such estimates of direct deaths remain low relative to the size of the global population, about 310 million people are expected to have suffered ill health because of climate change by 2030.

Nine out of ten of these people will be in developing countries and the number of healthy years of life lost to environmental change, including climate change, is set to be 500 times higher in Africa than Europe (see Figure 2).

Figure 2: Estimated effects of climate change on health through number of Disability Adjusted Life Years (DALYs) - the sum of years of potential life lost due to premature death, and the years of productive life lost due to disability, associated with climate change [4]

Credit: WHO

Developing countries already bear the brunt of the global disease burden. Their populations are more likely to be undernourished, lack access to clean water and contract infectious diseases such as malaria. They are also dealing with a growing epidemic of chronic diseases such as diabetes and cancer.

Climate could worsen the problems in many ways. Changing rainfall patterns and sea level rises mean some areas will become drought-prone while others are flooded. Both situations have dire consequences for access to clean water. This, in turn, means a likely spread of waterborne diseases such as cholera and diarrhoea, which alone kills nearly two million children a year.

Increasing hunger and malnutrition are expected as increasingly common extreme weather events destroy crops, patterns of crop pest infestation change, and salt infiltrates flooded coastal areas. [5]

Heatwaves can kill thousands - in August 2003, Europe's summer was about 3.5 degrees Celsius above average and an estimated 45,000 people died over two weeks.

Climate change will also worsen air pollution. Both temperature and humidity influence how air pollutants and fine particulates form, and evidence suggests that fine particulates contribute to respiratory disease (such as pneumonia, asthma and chronic obstructive pulmonary disease), especially in children. [1] The WHO estimates that 800,000 people alreadydie each year because of outdoor air pollution.

Virulent vectors

One area of particular concern is how climate change will affect the spread of insect-borne diseases. These include dengue fever, malaria, Lyme disease, West Nile virus, Rift Valley fever, chikungunya and yellow fever. They are spread through the bite of 'vectors' such as mosquitoes, ticks and flies.

Researchers currently focus much of their attention on dengue fever and malaria, partly because the diseases are so prevalent but also because outbreaks seem linked to climate. Increased rainfall in normally dry areas, for example, can create stagnant pools of water where mosquitoes breed.

But the links between climate and insect-borne disease are far from simple (see Table 1 for potential interactions). The same rainfall increase in wet regions could reduce malaria by washing immature mosquitoes away. Changes in temperature can also have opposing effects, depending on where they occur.

Generally speaking, the malaria mosquito digests blood quicker and feeds more often in warmer weather, thus speeding up transmission. The parasite meanwhile completes its life cycle more quickly, increasing replication. In theory then, global warming might allow these vectors to spread into areas they weren't previously able to colonise.

By 2080, up to 320 million more people could be affected by malaria because of these new transmission zones. [6] Worryingly, the disease would then also be spreading to people whose immune systems may never have been exposed to malaria, and who may be more vulnerable as a result.

But increased temperatures in already hot regions could reduce the spread of malaria mosquitoes by pushing temperatures higher than the mosquitoes can survive. Most mosquitoes cannot survive above about 40 degrees Celsius, so regions where climate change pushes temperatures above this level could see a drop in malaria. This is starting to be seen in Senegal, for example, where malaria prevalence has dropped by more than 60 per cent in the past 30 years. [7]

And an increase in the population of vectors does not automatically translate into an increase in disease.

The dynamics of malaria transmission, for example, depend on both the human population's immunity and the parasite's levels of drug resistance. Other ecological and societal factors are equally important: water storage and disposal systems, agricultural practices, deforestation, population density, living conditions, control programmes and health infrastructure all play a role in determining the reach and spread of malaria.

Increased temperature

Decreased survival of some mosquito species

Change in susceptibility to some pathogens

Increased population growth

Increased feeding rate to combat dehydration (so higher vector-human contact)

Expanded seasonal and spatial distribution

Faster incubation in vector

Extended transmission season

Expanded distribution

Increase in container-breeding mosquitoes because of more water storage

Higher numbers of vectors that breed in dried-up river beds

Reduction - or elimination - of vectors such as aquatic snails, through drought

More breeding sites and increased size of vector population

Increased vector survival due to increased humidity

More potential habitats downstream of floods for vectors such as aquatic snails

Heavy rain can synchronise vector host-seeking and virus transmission

Breeding sites washed away by heavy rain

Habitat destruction by flooding

Little evidence of direct effects

Table 1: The effect of climate change on insect-borne disease recorded in research studies. [1]

These complexities mean that while on the surface climate seems linked to malaria transmission, scientists disagree about specific local impacts. For instance, in East Africa, a drop in mosquito control and a rise in drug resistance appears to be confounding studies assessing whether malaria incidence has grown because of, or independently of, climate. [1]

Similarly, studies arguing that climate change is extending malaria's latitudinal or altitudinal boundaries may not consider historical records that show malaria has previously existed in such places before global temperatures began to increase (see The malaria myths of climate change).

The complexities of dengue transmission also lead studies to report conflicting associations between climate variations and infection rates. The clearest links come from small countries such as Honduras and Nicaragua, where the number and spread of the dengue mosquito population has been well correlated with climate. [8]Links in larger countries like Brazil and China have not been significant - although this may be because climate data was country-wide rather than location-specific.

Nevertheless, some scientists estimate that by 2080, six billion people will be at risk of dengue, compared with 3.5 if the climate does not change. If the global population grows to about 10 or 11 billion by then, as some estimates suggest, over half the planet could be at risk.

The spread of other vector-borne diseases could also increase. The cholera bacteria Vibrio cholerae can live on some species of plankton. Warmer sea temperatures mean more plankton blooms, which could mean the cholera bacteria flourishes, spreading to populations on the warm coasts of countries such as Bangladesh.

Schistosomiasis, a parasitic disease transmitted by aquatic snails, also seems to be affected by climate. In China, the latitudinal threshold beyond which temperatures were too cold for the snail to live has moved northwards, putting nearly 21 million more people at risk of the disease.

Strategic policies

Although scientists have yet to agree how far climate change will make insect-borne disease rise, there is an emerging consensus on how to tackle a potential crisis. Developing accurate models and surveillance to predict or detect disease outbreaks and act as early warning systems is central to this.

Such systems will require both climate and disease data, and lots of it, if they are to be rigorous enough to be reliable (see Better surveillance key to malaria early warning systems ).

In the past, the paucity of surveillance systems has meant developing countries have lacked up-to-date information on diseases. One outcome of the threat of SARS and bird flu H5N1, and the current pandemic of swine flu A(H1N1), is that many countries have been shocked into action. Several, including China and India, are pledging to update their disease-monitoring systems.

But this is a challenging undertaking. These systems require advanced computer hardware and software to collate and analyse incoming data. Such technology might include, for example, geographic information systems that can link data to specific locations and allow both spatial and temporal analyses of disease data. The infrastructure of existing systems may need to be upgraded to accommodate these additions.

But monitoring disease is just one aspect of creating an early-warning system. Accuracy will also rely on researchers understanding how non-climatic factors, such as drug resistance, influence epidemics.

And early warning systems will only work if there are resources to respond to the alarm bells. Strengthening health systems in poor countries, a long-called-for necessity, is even more urgent in the face of these future challenges. Moreover, the medical staff within these must be fully aware of how climate is likely to affect the people they treat.

A WHO feasibility analysis for creating prediction systems calls for health policymakers' involvement at the earliest stages, because even the best early warning systems will be worth little if operational responsibilities aren't clearly delineated and agreed from the beginning. [9]

Earlier this year, The Lancet medical journal commissioned the University College London Institute for Global Health to draw up a policy response framework on climate change and disease. [5] Their recommendations for policies on vector-borne disease are summarised in Box 1.

Box 1: Priorities for policymakers

Monitoring infectious disease

Establishing localised early-warning systems

Communication between states in identifying and responding to epidemics

Empowering women through better health and education

Strengthening health infrastructure to ensure care for the rural poor

Developing vaccines for dengue fever, leishmaniasis, malaria and schistosomiasis

Deploying rapid methods for field diagnosis

Ensuring fairer intellectual property laws for medical supplies

Deploying low-cost, low-tech solutions like mosquito nets and water filters

Using satellite data and geographical information systems to feed into surveillance systems

Developing models of human socioecological interaction to understand how people respond to environmental stress

Stabilising social infrastructure to limit migration away from areas of epidemic disease

Reducing consumption levels of luxury goods

Ensuring that different levels of government work together

Avoiding policy contradictions

Involving sectors other than health and environment

Making global governance accountable and transparent

And finally, pouring valuable resources into adapting to climate change is only worthwhile if countries also make serious attempts to mitigate global warming. Ultimately, this means a commitment from all countries to reduce greenhouse gas emissions and move to a low-carbon economy.

Priya Shetty is a freelance science writer on health and the environment, based in New York.

References

[1] Intergovernmental Panel on Climate Change. Climate change 2007: Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds. Cambridge University Press (2007)

[2] Predicting future warming NASA (2007)

[3] Global Humanitarian Forum The anatomy of a silent crisis [3.23MB] (2009)

[4] WHO Climate change and human health: Risks and responses (2003)

[5] Costello, A., Abbas, M., Allen A. et al Managing the health effects of climate change The Lancet 373 1693-1733 (2009)

[6] Lindsay S. W. and Martens W. J. M. Malaria in the African highlands: Past, present and future [694kB] Bulletin of the WHO 76 33-45 (1998)

[7] Githeko, A. K., Lindsay, S. W., Confalonieri, U. E. et al Climate change and vector-borne diseases: A regional analysis [268kB] Bulletin of the WHO 78 1136-1147 (2000)

[8] Patz, J. A., Campbell-Lendrum, D., Holloway, T. et al Impact of regional climate change on human health Nature 438 310-317 (2005)

[9] Kuhn, K., Campbell-Lendrum, D., Haines, A. et al Using climate to predict infectious disease epidemics WHO (2005)

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Climate change and insect-borne disease: Facts and figures

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explains the links between climate change and insect-borne disease, and outlines priorities for developing country policymakers. Some researchers have called climate change the biggest health threat the world has ever faced. With good reason - it is now an unavoidable truth that the health of the planet is linked to the health of its people.

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Climate change

Over the last 50 years, human activities - particularly the burning of fossil fuels - have released sufficient quantities of carbon dioxide and other greenhouse gases to trap additional heat in the lower atmosphere and affect the global climate.

In the last 130 years, the world has warmed by approximately 0.85 oC. Each of the last 3 decades has been successively warmer than any preceding decade since 1850(1).

Sea levels are rising, glaciers are melting and precipitation patterns are changing. Extreme weather events are becoming more intense and frequent.

What is the impact of climate change on health?

Although global warming may bring some localized benefits, such as fewer winter deaths in temperate climates and increased food production in certain areas, the overall health effects of a changing climate are likely to be overwhelmingly negative. Climate change affects social and environmental determinants of health - clean air, safe drinking water, sufficient food and secure shelter.

Extreme heat

Extreme high air temperatures contribute directly to deaths from cardiovascular and respiratory disease, particularly among elderly people. In the heat wave of summer 2003 in Europe for example, more than 70 000 excess deaths were recorded(2).

High temperatures also raise the levels of ozone and other pollutants in the air that exacerbate cardiovascular and respiratory disease.

Pollen and other aeroallergen levels are also higher in extreme heat. These can trigger asthma, which affects around 300 million people. Ongoing temperature increases are expected to increase this burden.

Natural disasters and variable rainfall patterns

Globally, the number of reported weather-related natural disasters has more than tripled since the 1960s. Every year, these disasters result in over 60 000 deaths, mainly in developing countries.

Rising sea levels and increasingly extreme weather events will destroy homes, medical facilities and other essential services. More than half of the world's population lives within 60 km of the sea. People may be forced to move, which in turn heightens the risk of a range of health effects, from mental disorders to communicable diseases.

Increasingly variable rainfall patterns are likely to affect the supply of fresh water. A lack of safe water can compromise hygiene and increase the risk of diarrhoeal disease, which kills over 500 000 children aged under 5 years, every year. In extreme cases, water scarcity leads to drought and famine. By the late 21st century, climate change is likely to increase the frequency and intensity of drought at regional and global scale(1).

Floods are also increasing in frequency and intensity, and the frequency and intensity of extreme precipitation is expected to continue to increase throughout the current century(1). Floods contaminate freshwater supplies, heighten the risk of water-borne diseases, and create breeding grounds for disease-carrying insects such as mosquitoes. They also cause drownings and physical injuries, damage homes and disrupt the supply of medical and health services.

Rising temperatures and variable precipitation are likely to decrease the production of staple foods in many of the poorest regions. This will increase the prevalence of malnutrition and undernutrition, which currently cause 3.1 million deaths every year.

Patterns of infection

Climatic conditions strongly affect water-borne diseases and diseases transmitted through insects, snails or other cold blooded animals.

Changes in climate are likely to lengthen the transmission seasons of important vector-borne diseases and to alter their geographic range. For example, climate change is projected to widen significantly the area of China where the snail-borne disease schistosomiasis occurs(3).

Malaria is strongly influenced by climate. Transmitted by Anopheles mosquitoes, malaria kills over 400 000 people every year - mainly African children under 5 years old. The Aedes mosquito vector of dengue is also highly sensitive to climate conditions, and studies suggest that climate change is likely to continue to increase exposure to dengue.

Measuring the health effects

Measuring the health effects from climate change can only be very approximate. Nevertheless, a WHO assessment, taking into account only a subset of the possible health impacts, and assuming continued economic growth and health progress, concluded that climate change is expected to cause approximately 250 000 additional deaths per year between 2030 and 2050; 38 000 due to heat exposure in elderly people, 48 000 due to diarrhoea, 60 000 due to malaria, and 95 000 due to childhood undernutrition.

Who is at risk?

All populations will be affected by climate change, but some are more vulnerable than others. People living in small island developing states and other coastal regions, megacities, and mountainous and polar regions are particularly vulnerable.

Children - in particular, children living in poor countries - are among the most vulnerable to the resulting health risks and will be exposed longer to the health consequences. The health effects are also expected to be more severe for elderly people and people with infirmities or pre-existing medical conditions.

Areas with weak health infrastructure - mostly in developing countries - will be the least able to cope without assistance to prepare and respond.

WHO response

Many policies and individual choices have the potential to reduce greenhouse gas emissions and produce major health co-benefits. For example, cleaner energy systems, and promoting the safe use of public transportation and active movement - such as cycling or walking as alternatives to using private vehicles - could reduce carbon emissions, and cut the burden of household air pollution, which causes some 4.3 million deaths per year, and ambient air pollution, which causes about 3 million deaths every year.

In 2015, the WHO Executive Board endorsed a new work plan on climate change and health. This includes:

Partnerships: to coordinate with partner agencies within the UN system, and ensure that health is properly represented in the climate change agenda.

Awareness raising: to provide and disseminate information on the threats that climate change presents to human health, and opportunities to promote health while cutting carbon emissions.

Science and evidence: to coordinate reviews of the scientific evidence on the links between climate change and health, and develop a global research agenda.

Support for implementation of the public health response to climate change: to assist countries to build capacity to reduce health vulnerability to climate change, and promote health while reducing carbon emissions.

References

(1) IPCC, 2014: Summary for Policymakers. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

(2) Death toll exceeded 70,000 in Europe during the summer of 2003. Robine JM, Cheung SL, Le Roy S, Van Oyen H, Griffiths C, Michel JP, et al. C R Biol. 2008;331(2):171-8.

(3) Potential impact of climate change on schistosomiasis transmission in China. Zhou XN, Yang GJ, Yang K, Wang XH, Hong QB, Sun LP, et al. Am J Trop Med Hyg. 2008;78(2):188-94.

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Over the last 50 years, human activities - particularly the burning of fossil fuels - have released sufficient quantities of carbon dioxide and other greenhouse gases to trap additional heat in the lower atmosphere and affect the global climate. In the last 130 years, the world has warmed by approximately 0.85 oC.

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Using climate models to predict future climates

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Using climate models to predict future climates

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Discover how data from the ice core record are used to help scientists predict the future of our climate. (Please note that this is the final in a three-part series, which includes the first "Ancient Ice and Our Planet's Future" and the second "Life on the Ice")

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Public attitudes towards climate change 

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Public attitudes towards climate change 

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Public opinion Analysis: Regional attitudes to climate change across the UK

Do people across Britain think differently about climate change? Or does the UK speak as one voice? Data on regional attitudes to climate change is pretty thin on the ground, but the information that exists from the UK and further afield seems to tell an intriguing story.

A study published earlier this year in Nature Climate Change found differences in Americans' views on climate change, depending on where they lived.

Based on survey data gathered between 2008 and 2014, people living in the central US tended to be less worried about global warming than the national average, while residents of drought-stricken California showed noticeably more concern.

The map below shows the study's results . Red indicates high concern, blue is lower concern.

UK opinion on causes of climate change

Crossing the Atlantic to the UK, YouGov recently carried out a poll for the Sunday Times, showing how public perception of climate change varies across five regions: London, the South, Wales and the Midlands, the North and Scotland.

Participants were asked which of the following statements they agreed with: the climate is changing as a result of human activity, it's changing but not because of human activity, it's not changing, or they're unsure.

Subtracting the number of people who disagree that climate change is human caused from the number who agree is one way to express an overall level of agreement. We've plotted this in the map below:

On balance, it seems Britons are not so different from each other.

Looking at the map above, all five regions are within the orange-yellow band of the colour scale, suggesting that many more respondents agreed human activity is causing climate change than disagreed, or thought it wasn't happening at all.

Region by region

There is some variation from region to region, however. Geographical variations can happen because of differences in demographics, cultural and ideological factors, and because people with similar characteristics "tend to cluster together", according to the authors of the US study. Previous studies have suggested that local weather can also affect climate change perceptions, the scientists note.

The table below shows the results of the YouGov poll region-by-region:

Notably, Londoners appear to have a much higher acceptance of man-made climate change than the rest of the UK. In the capital, 68% of people agreed climate change is human-caused, compared to a national average of 59%.

Polls providing greater geographic detail than the five regions in the YouGov poll are pretty few and far between. While there have been plenty of surveys to see what Britons think about global warming, specific information about the location of respondents is often lacking or unavailable for privacy reasons. There is also the difficulty that the more you zoom in regionally, the larger the overall sample size has to be to produce reliable data.

The Public Attitudes to Science survey, carried out by Ipsos Mori on behalf of the UK government, provides the biggest regional breakdown within the various polling archives we could find, splitting the country into 12 government administrative regions.

Pooling together from the 2014 and 2011 surveys - previous ones did not ask exactly the same questions - gives a sample size of around 4,000 people nationally. Ideally, data would come from the same survey as regional patterns can change over time. But to obtain a large enough sample size, data can be combined across more than one survey, says polling expert Leo Barasi, if the questions are the same.

Participants were asked to what extent they agreed or disagreed with the statement: 'Human activity does not have a significant effect on the climate'.

The findings were interesting - and seem to show some differences with the recent YouGov poll. We've shown the results in the table below, split up by region:

At a country level, Scotland appears to be the least sceptical of man-made climate change, with only 12% of people saying they agree human activity does not have a significant effect on the climate. This is followed by England (15%), Northern Ireland (18%) and Wales (21%) (but note also the margins of error).

Noticeably, the results showed something of a North-South divide in England - with the Midlands and the North more sceptical than the South.

Respondents in the South-West were the least sceptical of all the government regions with 82% of people disagreeing with the statement that humans don't cause climate change.

This could be partly a result of the region experiencing severe flooding, says Barasi. A recent study suggests the 2013/2014 floods in the UK pushed up public acceptance of human-caused climate change, particularly among those personally affected.

Parallels could, perhaps, be drawn with the US study, too. California and Massachusetts were among the most concerned about climate change in the Yale study, and both have recently experienced record-breaking weather. More research is needed to clarify a possible link, however.

The Ipsos Mori results places London among the more sceptical regions in the UK, with 16% of respondents disagreeing that climate change is human-caused. This pattern is markedly different to the YouGov poll, where Londoners showed the highest acceptance of man-made climate change of all UK regions. However, it is difficult to compare the data directly as the questions are worded so differently.

A question of weighting

As ever, any single poll should be treated with caution until it's clear the results are backed up elsewhere (and, as the general election has shown, even multiple polls can get it wrong). Barasi says he's surprised by what the Ipsos Mori surveys seem to show about regional differences. He tells Carbon Brief:

"The results aren't really what I'd expect them to be. I'm surprised by the finding that Londoners are the second-most doubtful about the human influence on the climate, and that the West Midlands are the most doubtful. I certainly wouldn't have expected that the South East to be among the least doubtful, given it generally leans conservative politically."

Indeed, a similar nationwide poll of public perceptions of climate change that Carbon Brief conducted in 2013, again, shows some different results to the Ipsos Mori poll.

With a smaller sample size of 2,000, the Carbon Brief poll showed London to be the most accepting of climate change, with 60% agreeing that it is happening and is mostly caused by humans. The South East was among the least accepting, with 53% in agreement.

In a similar vein, an Observer poll published earlier this month found that people from London were most likely to agree that increasing frequency of extreme weather was a sign of climate change, while those living in the North West were least likely to agree.

Why the difference between the Ipsos Mori poll and the others?

One explanation could lie in sampling errors. Anna Quigley, director of the Ipsos Mori poll, tells Carbon Brief:

"While the data for both years are highly accurate at a national level - and when broken down into major demographic groups like gender and age - they become less reliable at the regional level where we get down to sample sizes of c.100 to c.200 peopleâ?¦ We would urge caution about drawing hard conclusions from regional differences appearing in the survey."

How polling data is analysed could prove to be even more of a problem, says Barasi. The Ipsos Mori data has been weighted - a technique used by many polls to give some data more influence than others - to ensure the results are representative of the national demographic.

But according to Barasi, this could potentially skew the sample profiles within each region, making the results an artifact of the weighting process rather than offering real insight.

In the Ipsos Mori poll, Barasi says 18-24 year olds appear over-represented in the South-East, for example, which could be significant as climate change perception varies across age and gender.

Quigley agrees, saying that skewed results from weighting are the "most likely explanation for the 2011 data and may be part of the issue for the 2014 data".

A detailed view

Public opinion on climate change is complex, and measuring it is even more so. Regional polling reveals a nuanced view of public opinion that can be hidden if you look only at the national average. And with so little data about how and why opinion varies from region to region, a comprehensive understanding will continue to elude us, suggests an editorial in the latest edition of Nature Climate Change. Referring to the last month's Yale study, it says:

"National surveys that continue to focus on basic questions around climate science obscure the complexities of public opinion on climate change. To understand this variation, social science needs to move beyond national data and find new ways to quantitatively unpack the public's occasionally incoherent views on climate change."

So, while national surveys can give us some important information about public perception of climate change, they only form part of the story. While there may not be a wealth of regional data available yet, it's intriguing to see patterns emerging.

Main image: Block of flats in London, England.

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Analysis: Regional attitudes to climate change across the UK | Carbon Brief

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Public opinion Analysis: Regional attitudes to climate change across the UK Do people across Britain think differently about climate change? Or does the UK speak as one voice? Data on regional attitudes to climate change is pretty thin on the ground, but the information that exists from the UK and further afield seems to tell an intriguing story.

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Key idea 3.a Climate change debate - this website will give you all the pros and cons. 

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Key idea 3.a Climate change debate - this website will give you all the pros and cons. 

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Are humans causing climate change? Pros and Cons of global warming debate.

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Carbon Dioxide Information Analysis Center

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Carbon Dioxide Information Analysis Centre

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Carbon Dioxide Information Analysis Centre

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UK .Gov article on strategies in place to decarbonise British Economy

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UK .Gov article on strategies in place to decarbonise British Economy

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This week the UK Government published its long awaited industrial strategy, marking a distinctive break from the previous Conservative regime. Gone is David Cameron's more laissez faire attitude to managing the economy. In its place is a more proactive approach, which seeks to stimulate industry with targeted investment. Taking advantage of the greater flexibility afforded by freedom from the EU's state aid rules the plan sees some exciting developments in the decarbonisation of the UK economy.

Among the ideas proposed are to make the UK a world leader in some of the low carbon technologies it already has an advantage in, namely electric vehicles, wind power and nuclear. The consultation, known as a green paper, proposes a roll out of electric vehicle charging points. The much-heralded announcement by Nissan last October to invest in its Sunderland plant - one they will now review depending on how Brexit goes - was understood to be helped by assurances from government of its commitment to making Britain a hub for electric car making.

The Sunderland factory will produce batteries for electric vehicles, an area of focus in the new strategy. Ministers have also asked the country's Chief Scientific Adviser, Sir Mark Walport, to review the case for a new research institution to work on battery technology, energy storage and smart grids. Battery storage has been seen by many as the killer app that could transform the potential for renewables, allowing their intermittent energy to be stored and accessed on demand. The wide-ranging strategy also sets out plans for upgrades to digital, transport, energy and flood defence infrastructures.

One of the goals set out in the paper is to "capitalise on strengths to win a substantial share of global markets". Hopefully this bodes well for the UK's offshore wind industry. The UK has more offshore wind capacity installed than any other country and the industry drew record investment of $29.9 billion last year, a rise of 40% from 2015. The Government also announced a review into reducing costs to business of its decarbonisation plans in line with its legal obligations enshrined in the Climate Change Act. If they are serious about reducing such costs then they should embrace onshore wind and solar farms which are some of the cheapest forms of new energy on the planet but which have been spurned so far by this government. (They would certainly be much better value than the eye-watering costs of Hinkley Point C's nuclear power station.)

Ultimately the strategy has the potential to use government investment to shift the country in the right direction. But we need more than just 'public money,' we need the public's money too.

Banks currently invest our savings with scant regard to its climate impact, often directly supporting fossil fuel companies, which is why NGOs are urging the UK's high street banks and asset managers to shift their investments towards renewables. If our taxes are being spent on a low carbon industrial strategy, why not the cash we hold in our bank accounts? With the banking AGM season coming up Christian Aid is holding a series of training workshops for people who want to get involved in helping shift the investment flows even further. This is a growing area of environmental activism - last year saw a record number of shareholder resolutions addressing climate change, 94, up from 82 in 2015.

This is going to be a revealing year for the UK's decarbonisation agenda. Theresa May may be busy dealing with Brexit and President Trump but climate change isn't going to wait around until she's finished. Her government will publish its carbon plan this year setting out how it will meet its decarbonisation commitments, not an easy circle to square if they plan on building a new runway at Heathrow. This industrial strategy is a good start. Climate Minister Nick Hurd's announcement on Wednesday of £28m for clean energy R&D also bodes well. But we're going to need more than just a few million here and there if Britain is going to stay competitive in a world starting to embrace this new industrial revolution. China is pursuing electric vehicles with gusto and is threatening to overtake the US auto industry which itself will not hand over its crown lightly.

The UK's low carbon industry cannot be competitive solely as an exporter; it needs to have a thriving domestic market too. Fortunately this is underpinned by the Climate Change Act, which gives the Government every reason to both invest in the industry and implement its products in decarbonising Britain.

With Donald Trump squandering the good work on the environment done by Barack Obama there is an opportunity for Theresa May's 'Global Britain' to show global leadership. It's vital that the UK's ongoing industrial strategy ensures it will be powered by the clean energy of the future not the dirty energy of the past.
This Author
Joe Ware is a journalist and writer at Christian Aid and a New Voices contributor for the Ecologist. He's on twitter at @wareisjoe.
For more information about Christian Aid's Big Shift training workshops, taking place across the country from Exeter to Kendal, sign up .

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Ultimately the UK Government's new industrial strategy has the potential to use government investment to shift the country in the right direction for the environment. But we need more than just 'public money,' we need the public's money too writes JOE WARE

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CASE STUDY: China's Contribution to GHG emissions.

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CASE STUDY: China's Contribution to GHG emissions.

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Stripped Pixel/Shutterstock

China accounts for a tenth of all the greenhouse gases and aerosols that have collected in the atmosphere over the industrial era, according to new research.

Boasting one of the world's largest economies, China has overtaken the EU and the US as the world's emitter, with CO ₂ emissions from fossil fuels tripling over the past 30 years.

But despite soaring CO ₂ emissions, China's relative contribution to climate change has remained steady - around the 10% mark - over the whole industrial period, says a published in Nature.

It's a pretty complicated picture. But in recent times, this is because cooling from aerosols has been masking part of the warming signal. The upshot of this is that cutting some types of aerosol in a much-needed bid to improve air quality could drive faster warming in the coming decades, say the authors.

Climate responsibility

The new study quantifies all the gases and particles currently in the atmosphere that are having an effect on global temperature, and which can be traced back to human activity.

This includes factors that have a warming influence - such as greenhouse gases and black carbon - and those that induce cooling, such as sulphate and nitrate .

The authors combined this with China's past and present emissions to estimate, for the first time, the size of the country's contribution to human-caused climate change.

Historical warming

Unlike aerosols, greenhouse gases stay in the atmosphere for a very long time. Carbon dioxide emitted at the start of the industrial revolution is still warming the atmosphere today, which is why scientists take into account historical emissions as well as present day ones to work out a country's contribution to climate change.

The graph below (main, not inset) shows the impact on global temperature - known as the radiative forcing - from different anthropogenic sources of greenhouse gases in China extending back to 1850.

China's single biggest source of warming is CO ₂ from fossil fuel burning (red line). With emissions rising steeply over the past few decades, fossil fuels overtook land-use change as the biggest source of CO ₂ from China in 1992 (brown line).

Warming as a result of changing land use rose throughout the 20th century, before declining in the 1980s as reforestation programmes turned the land from a net emitter to a net absorber.

In a News and Views that accompanies the study, Prof Dominick Spracklen , associate professor of aerosols and climate at the University of Leeds, says:

"China is now planting forests on a larger scale than anywhere else on the planet. These plantations sequester CO ₂ from the atmosphere, so that Chinese forests are now a net sink of this gas."

Despite this, past emissions from land-use change still account for a third of atmospheric CO ₂ attributable to China, with fossil-fuel burning making up the other two thirds, the paper notes.

The warming caused by emissions of nitrous oxide (yellow) and halogen compounds (pink) increased over the past two or three decades - to a far lesser extent than fossil fuel CO ₂, while methane-induced warming increased three-fold between 1950-2010 (orange line).

Relative contribution

To put the changes within China into a global context, the inset graph in the figure above shows the warming effect of Chinese greenhouse gases as a percentage of the global total.

Again, the impact of China's recent fossil fuel expansion is clear, with the country's contribution to total global fossil fuel CO ₂ almost tripling in the 30-year period between 1980-2010.

China currently accounts for 12% of the total greenhouse gases in the atmosphere - a figure that has remained fairly steady over the industrial period, at around 8-12% (blue line). This is effectively the balance of impacts from China's greenhouse gas emissions over time - i.e. carbon dioxide, methane, nitrous oxide and halogen compounds - and from all anthropogenic sources.

The 10% figure is lower than might be expected for the country topping of the list of the biggest emitters. But it reflects the fact that others, such as the US and the EU, have been emitting far longer, the paper notes. The paper does not calculate the contributions from these other entities, so a direct comparison is not possible.

Relative to the rest of the world, China's share of greenhouse gas warming fell slightly in the 1960s, 70s and 80s before starting to climb again as economic growth and fossil fuel burning accelerated.

But there's something else going on, too. China is responsible for a disproportionate amount of the aerosols emitted around the world, some of which have a strong cooling effect.

Cooling effect

According to the new study's results, China is responsible for 28% of the sulphate aerosols currently in the atmosphere (light blue bar in the graph below), 24% of nitrate aerosols (dark blue) and 14% of black carbon (pink).

Importantly, while the US and Europe have been slashing sulphates in an effort to improve air quality , China's aerosol emissions have been on the rise. Spracklen says:

"Air pollution is a serious environmental issue in China, where 1.3m people die each year because of exposure to poor-quality air outdoors."

As well as posing a growing public health crisis, sulphate aerosols have a strong cooling effect. Over the past few decades, this has been pulling in the opposite direction to rising CO ₂, methane and black carbon emissions, effectively muting China's relative impact on global temperature.

As the graph below from Spracklen's News and Views article shows, the balance between warming (red shading) and cooling (blue shading) have kept the country's contribution to human-caused climate change pegged at about 10% in recent decades, despite soaring fossil fuel emissions.

The implication is that if China follows the rest of the world in cutting sulphate aerosols in a bid to reduce air pollution, global temperatures could rise even faster in the coming decades since there would be less of a cooling effect to offset the warming. But this is no reason to avoid doing it, says Spracklen:

"This means that it will be difficult to achieve rapid reductions in near-term global warming through the control of Chinese air pollutants overall - a focus on greenhouse-gas emissions, in particular, will be required."

But given the upwards trend in fossil fuel CO ₂ emissions, the long lifetimes of existing infrastructure and the social and political systems in place, it is "unlikely" that China's relative contribution to global greenhouse gas warming will come down any time soon, say the authors in the paper.

While the study goes further than previous ones in terms of pinning down China's total contribution to climate change, the authors acknowledge a lot of remaining uncertainty, particularly about China's methane and sulphur dioxide emissions.

There is also work to be done in completing the complex picture of influencing factors. For example, the authors acknowledge the role of aerosols in stimulating clouds to form and the darkening of snow and ice by black carbon, adding that there is still too much uncertainty to include fully in their calculations.

Main image: View of the Forbidden City shrouded in pollution from Jingshan Park, Beijing. Credit: Stripped Pixel/Shutterstock.

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China is responsible for 10% of human influence on climate change, study says | Carbon Brief

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Stripped Pixel/Shutterstock China accounts for a tenth of all the greenhouse gases and aerosols that have collected in the atmosphere over the industrial era, according to new research. Boasting one of the world's largest economies, China has overtaken the EU and the US as the world's emitter, with CO 2 emissions from fossil fuels tripling over the past 30 years.

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Global Warming 101 | National Geographic

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Psychology behind why people don't believe in climate change

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Psychology behind why people don't believe in climate change

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Why People Don't Believe In Climate Science

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Teachers TV- Climate Change - The Causes

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Past atmospheric composition and greenhouse gases - University of Copenhagen

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The figure presents results from the Antarctic EPICA Dome C ice core showing the development of temperature in Antarctica and the concentrations of the atmospheric greenhouse gases carbon dioxide (CO 2, in blue) and methane (CH 4, in red) over the past 800 thousand years.

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Climate Change: Vital Signs of the Planet

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The rate of change since the mid-20th century is unprecedented over millennia.

Earth's climate has changed throughout history. Just in the last 800,000 years, there have been eight cycles of ice ages and warmer periods, with the end of the last ice age about 11,700 years ago marking the beginning of the modern climate era - and of human civilization. Most of these climate changes are attributed to very small variations in Earth's orbit that change the amount of solar energy our planet receives.

This graph, based on the comparison of atmospheric samples contained in ice cores and more recent direct measurements, provides evidence that atmospheric CO2 has increased since the Industrial Revolution. (Credit: Luthi, D., et al.. 2008; Etheridge, D.M., et al. 2010; Vostok ice core data/J.R. Petit et al.; NOAA Mauna Loa CO2 record.) Find out more about ice cores (external site).

The current warming trend is different because it is clearly the result of human activities since the mid-1800s, and is proceeding at a rate not seen over many recent millennia. It is undeniable that human activities have produced the atmospheric gases that have trapped more of the Sun's energy in the Earth system. This extra energy has warmed the atmosphere, ocean, and land, and widespread and rapid changes in the atmosphere, ocean, cryosphere, and biosphere have occurred.

Do scientists agree on climate change?

Yes, the vast majority of actively publishing climate scientists - 97 percent - agree that humans are causing global warming and climate change.

detailed answer

Earth-orbiting satellites and new technologies have helped scientists see the big picture, collecting many different types of information about our planet and its climate all over the world. These data, collected over many years, reveal the signs and patterns of a changing climate.

Scientists demonstrated the heat-trapping nature of carbon dioxide and other gases in the mid-19th century. Many of the science instruments NASA uses to study our climate focus on how these gases affect the movement of infrared radiation through the atmosphere. From the measured impacts of increases in these gases, there is no question that increased greenhouse gas levels warm Earth in response.

"Scientific evidence for warming of the climate system is unequivocal."

- Intergovernmental Panel on Climate Change

Ice cores drawn from Greenland, Antarctica, and tropical mountain glaciers show that Earth's climate responds to changes in greenhouse gas levels. Ancient evidence can also be found in tree rings, ocean sediments, coral reefs, and layers of sedimentary rocks. This ancient, or paleoclimate, evidence reveals that current warming is occurring roughly 10 times faster than the average rate of warming after an ice age. Carbon dioxide from human activities is increasing about 250 times faster than it did from natural sources after the last Ice Age.

References

References
Header image shows clouds imitating mountains as the sun sets after midnight as seen from Denali's backcountry Unit 13 on June 14, 2019. Credit: NPS/Emily Mesner

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Climate Change Evidence: How Do We Know?

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Vital Signs of the Planet: Global Climate Change and Global Warming. How do we know it's happening? Here's the evidence.

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1.a. How do we reconstruct past climates?

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1.a. How do we reconstruct past climates?

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Reconstructing Climate History - How Do We Know?

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Why is it important to reconstruct the long history of the Earth's climate, and how can we do that?

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Other side to the story - the rise of Climate change sceptics.

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Other side to the story - the rise of Climate change sceptics.

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Why is Climate Change a contested issue?

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What can I do?

Recent media stories - the facts behind the headlines

"Climate change scandal" - the headlines proclaim. In fact, the scandal is that the concrete and mounting evidence of the danger of climate change is being ignored by large sections of the media. It instead publishes stories implying the whole thing is a hoax.

The media climate has changed over the past years, such that in 2010,The Express felt complacent enough to publish " Global warming: what a climate con."

First was 'Climategate'. In autumn 2009, emails from the University of East Anglia's (UEA) Climatic Research Unit were illegally hacked and published, just before the Copenhagen negotiations, resulting in a high-profile media storm. Allegations that climatologists had manipulated results, flouted Freedom of Information laws and prevented critics from being published in the academic literature provoked a global controversy ( http://thegwpf.org/images/stories/gwpf-reports/Climategate-Inquiries.pdf). A detailed briefing on this affair nonetheless can be found at http://publicinterest.org.uk/climategate-a-briefer/ - the most telling point being that "[n]ot one piece of evidence or data has been altered or found to be wrong as a result."

The Institute of Physics - whose statements about UEA's "worrying scientific integrity" were jumped on by media sceptics to negate the whole phenomenon of climate change - have recently issued a clarification saying that, "our climate is changing, and we need to take action now to mitigate that change", while their submission, it has been revealed, is likely to have been influenced by an energy consultant.

Next came 'Glaciergate' in early 2010. Buried in the 3000-page 2007 IPCC report, there was a brief mention of a claim that the Himalayan glaciers would melt by 2035. The claim was argued to be based on an error and The Times and The Express in particular implied that this significantly undermines the whole report, claiming that this was a "central claim", which is . Nevertheless, the .

This was followed by '' - attempts to smear as unreliable the discussion in the report of possible impacts of climate change on African agriculture - and 'Seagate' - an incorrect figure which had been provided by a Dutch government agency for the proportion of the Netherlands below sea level, both in February 2010. See discussion at .

Another Times article on 14 February 2010, , cites work by Anthony Watts, a climate sceptic, on the location of temperature stations, alleging that some produce poor quality data. However, when the actual data is analysed, the poor quality stations are found to , not overestimate, any warming trend.

Back at The Times on 15 February 2010, an article which has since been retracted, read: "Professor Watson, currently chief scientific adviser to the Department for Environment, Food and Rural Affairs, said that if the errors had just been innocent mistakes, as has been claimed by the current chairman, Rajendra Pachauri, some would probably have understated the impact of climate change." nevertheless later reported that Robert Watson said, "The article distorted my statements - I was interviewed for an hour and it was obvious that the reporter wanted me to say that the authors were biased - I said I did not believe that."

Futhermore, in 2010, sceptic ex-Conservative MEP Roger Helmer (now UKIP, as of March 2012) used European taxpayers' money in order to pay for advertisements that read '"Green' Climate Policies: Probably Unnecessary, Certainly Ineffectual, and Ruinously Expensive." This prompted our petition against Roger Helmer's use of taxpayers' money to fund denialist propoganda and to tell the European Parliament to disavow the ads and make amends by funding a real "information" advertising campaign about the threats that climate change poses. Read more about this .

Climate science is being confronted by growing doubt and criticism. The debacle of the 2009 and 2011 United Nations Climate Change Conferences, in Copenhagen and Durban respectively, clearly reflected the rejection of reality.

The UK Independence Party (UKIP) is a staunch sceptic of climate change. At their Spring Conference in March 2010, the party leader Lord Pearson of Rannoch declared that "we must question the whole theory of man-made climate change." More information on their manifesto and policies can be found at the following links: , and .

Somewhat similarly, the British National Party (BNP) believes anthropogenic global warming is "non-existent" (). At the end of 2011, Nick Griffin, the party leader of the BNP, claimed that "[c]arbon trading is a money-making scam that enriches big business and the banks, at the taxpayers' expense. A scam, moreover, that will have a devastating effect on the job market and the ability of Britain to sustain any heavy industry," () and that "[c]limate change never was about drowning polar bears; it was always about big business profit and elite power." ().

The far right are not the only sceptics. Reports from prominent figures such as the former Cabinet Secretary in 2011 highlight the doubts and uncertainties that exist about the rise of global temperatures and the questionable reliance on the IPCC and its somewhat flawed procedures. Find more on this here:

Shale gas extraction or 'fracking' is still viewed by many as 'sustainable energy saviour'. Two earthquakes have already occurred in the Bowland Shale around Lancaster after the independent energy company Cuadrilla launched exploratory work for natural gas extraction in 2011. The connection between the two was swiftly denied by Cuadrilla as 'unlikely' and instead propose as many as 200-300 wells over the next three to five years to meet proposed productivity levels.

Despite the findings of the US Environmental Protection Agency that local groundwater had been contaminated with synthetic chemicals associated with 'fracking', Rob Ward, head of groundwater sciences at the British Geological Survey (BGS), further strengthens the 'fracking' causation as he declares the risk of groundwater contamination in the UK is 'low' and that it is by no way certain that methane in the water derives from shale gas activities. These claims were made while no sampling has been done at Cuadrilla's site. Pursuing shale gas as a source of endiverts funds away from actually sustainable and more climate-friendly energy sources. ()

()

The climate denial is so strong among the Republicans that efforts by U.S. climate scientists to educate the GOP leadership on the scientific evidence of man-made climate change have been futile. No candidate vying for GOP nomination can admit to climate change nor advocate measures relating to the issue. (). Republican spokespersons and media outlets have also given disproportionate attention to sceptics' viewpoints as well as challenged the scientific consensus on global warming. Unsurprisingly, the "percentage of self-identified Republicans or conservatives answering yes to the question of whether the effects of global warming were already being felt fell to 30% or less in 2010, down from 50% in 2007-08. Meanwhile, liberals and Democrats remained around 70% or more." ()

This scepticism originates in part from 'a long-term, well-financed effort on part of conservative groups and corporations to distort global warming science.' (). In February 2012, leaked documents showed U.S. thinktank the Heartland Institute's core mission is to discredit the established climate science. It has been receiving support from wealthy individuals including the Koch brothers and corporations such as Microsoft and RJR Tobacco, and has been making payments to bloggers, experts, schools and scientists to cast doubt on climate science.

Details can be found here: , , , and .

Undeniably, however, sceptics' campaigns in the U.S. played a crucial role in preventing domestic and international policymaking and agreement on climate change and efforts to reduce global warming pollution.

Below is a list of useful sites with facts debunking just about any climate sceptic myth.

News updates on climate chance scepticism:

https://www.theguardian.com/environment/climate-change-scepticism

What can I do?

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A rising tide of climate sceptic disinformation

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What can I do? Recent media stories - the facts behind the headlines "Climate change scandal" - the headlines proclaim. In fact, the scandal is that the concrete and mounting evidence of the danger of climate change is being ignored by large sections of the media.

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1.a Earths Climate is Dynamic: Methods for Reconstructing Past Climates

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1.a Earths Climate is Dynamic: Methods for Reconstructing Past Climates

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Tree Rings & Climate - Windows to the Universe

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Trees, alive or dead, are not the only source of wood used to construct such extended records. Beams from old buildings or ruins, samples from wooden frames of old paintings, and slivers from violins have all been used to add wood samples from trees long dead to climate chronologies.

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The Aral Sea is situated in Central Asia, between the Southern part of Kazakhstan and Northern Uzbekistan. Up until the third quarter of the 20th century it was the world?s fourth largest saline lake, and contained 10grams of salt per liter. The two rivers that feed it are the Amu Darya and Syr Darya rivers, respectively reaching the Sea through the South and the North. The Soviet government decided in the 1960s to divert those rivers so that they could irrigate the desert region surrounding the Sea in order to favor agriculture rather than supply the Aral Sea basin. The reason why we decided to explore the implications up to today of this human alteration of the environment is precisely that certain characteristics of the region, from its geography to its population growth, account for dramatic consequences since the canals have been dug. Those consequences range from unexpected climate feedbacks to public health issues, affecting the lives of millions of people in and out of the region.

By establishing a program to promote agriculture and especially that of cotton, Soviet government led by Khrouchtchev in the 1950s deliberately deprived the Aral Sea of its two main sources of water income, which almost immediately led to less water arriving to the sea. Not only was all this water being diverted into canals at the expense of the Aral Sea supply, but the majority of it was being soaked up by the desert and blatantly wasted (between 25% and 75% of it, depending on the time period). The water level in the Aral Sea started drastically decreasing from the 1960s onward. In normal conditions, the Aral Sea gets approximately one fifth of its water supply through rainfall, while the rest is delivered to it by the Amu Darya and Syr Darya rivers. Evaporation causes the water level to decrease by the same amount that flows into the Sea, making it sustainable as long as inflow is equal to evaporation on average. Therefore the diversion of rivers is at the origin of the imbalance that caused the sea to slowly desiccate over the last 4 decades.

Level of salinity rose from approximately 10g/l to often more than 100g/l in the remaining Southern Aral. Salinity of the rivers varies with place and time, as well as through the seasons. When going through the desert, rivers often collect some salt compounds residues in the ground that result in higher salinity, but may well be lowered again after going through irrigated lands. Dams also affect salinity, notably by reducing its variability with the seasons. Smaller lakes within the Aral Sea that have stopped being fed by river flows tend to have higher salinity due to evaporation, causing some or all fishes that either survived or had been reintroduced in the 1990s to die. Even re-watering those lakes does not compensate for the increased salinity over the years. In 1998, water level was down by 20m, with a total volume of 210km3 compared to 1,060km3 in 1960.

(source: http://www.envis.maharashtra.gov)

Most of the changes in climate and landscape in the Aral Sea basin that we are about to explore are at the least indirect products of Human induced changes. While we must remember at all times that society is responsible for the crisis that has unfolded in and around the Aral, the point we want to make is that most of the actual changes that have afflicted the Sea since the 1960s are the result of our environment's reaction to the stresses society has imposed on it. Thus, the difficulty lies as much in understanding the way climate and other natural systems function as in being capable of weighing the potential consequences of our actions before we undertake them. Risk assessment combined with scientific understanding should undercut our actions more efficiently; adding an ethical dimension to the equation remains more than welcome in addition to those more accessible and quantifiable factors, but is too fragile to be the centerpiece on which our decisions rely before we commit to large scale actions which can often, as we are about to see, engender even larger responses from our environment.

(source: http://www.geography.hunter.cuny.edu)

(source:www.nationalgeographic.com)

(source: http://eartfocus.typepad.com)

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In the last 60+ years the Aral Sea has suffered irreparable damage from an unnatural disaster.

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An interesting documentary on climate change influencing sea level rise 

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An interesting documentary on climate change influencing sea level rise 

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Earth Under Water Worldwide Flooding Sea Level Rise (SLR)

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Climate variations - natural factors vs human influences

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Climate variations - natural factors vs human influences

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Sir David Attenborough: The Truth About Climate Change

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The legendary broadcaster and naturalist Sir David Attenborough was long unsure about the causes of the observed climate warming. In his documentary, The Truth About Climate Change, he sheds doubt and explains what convinced him.

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Struggling with Spearmans Rank skill - then watch this video and work your way through the example

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Struggling with Spearmans Rank skill - then watch this video and work your way through the example

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Spearman's Rank Correlation Coefficient : ExamSolutions Maths Revision

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Go to http://www.examsolutions.net/ for the index, playlists and more maths videos on Spearman's rank correlation coefficient and other maths topics.

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Spearman's Rank Correlation Coefficient: its use in geographical field studies

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Polar ice doesn't care who's in the White House. It just melts. In the sixth session of TED2017, hosted by TED's Head Curator Chris Anderson, we hear blunt talk on climate change - taking a 30,000-foot view from the clouds and examining some market-based solutions for cleaning the planet. Below, recaps of the talks from Session 6, in [...]

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10 years of TED Talks show how the conversation around climate change has developed, from awareness-raising to dire warnings to a growing sense that we can actually do something about it.

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"I was excited to be a part of the 'Dream' theme," says Al Gore as he walks onto the TED2016 stage. "But then I found out I was leading off the nightmare section." He admits that what we've doing to our world is a nightmare, and that the consequences we're seeing are quite scary: "Every [...]

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Polar ice doesn't care who's in the White House. It just melts. In the sixth session of TED2017, hosted by TED's Head Curator Chris Anderson, we hear blunt talk on climate change - taking a 30,000-foot view from the clouds and examining some market-based solutions for cleaning the planet.

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Courtesy of Anna: Adapting to climate change 

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Courtesy of Anna: Adapting to climate change 

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Intergovernmental Panel on Climate Change

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Climate Change Commission of the Philippines

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International Union for Conservation of Nature

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A new video documentary by the UNFCCC Adaptation Committee aims at raising awareness on climate change adaptation. The 20 minute documentary "Adapting to a changing climate" introduces viewers to the topic of climate change adaptation, weaving in inspiring stories of adaptation action and interviews with experts.

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Courtesy of Liv - evidence to show Glacial ice cap loss

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Courtesy of Liv - evidence to show Glacial ice cap loss

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Greenland Ice Mass Loss: Jan. 2004 - June 2014

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GRACE consists of twin co-orbiting satellites that fly in a near polar orbit separated by a distance of 220 km. GRACE precisely measures the distance between the two spacecraft in order to make detailed measurements of the Earth's gravitational field.

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Plot the time trend for average July temperature in the USA 1901 - 2014

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Plot the time trend for average July temperature in the USA 1901 - 2014

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Very useful website - evidence for climate change

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Very useful website - evidence for climate change

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IPCC - Inter Governmental Panel for Climate Change

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IPCC - Inter Governmental Panel for Climate Change

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Fifth Assessment Report - Climate Change 2013

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Fifth Assessment Report - The Physical Science Basis includes assessment of climate change observations throughout the climate system; sea level change, biogeochemical cycles, clouds and aerosols, and regional climate phenomena.

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Global Warming case study impacts on the mediterranean

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Global Warming case study impacts on the mediterranean

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Human Mitigation and management of climate change

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Human Mitigation and management of climate change

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Summary of global warming and climate change

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Summary of global warming and climate change

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Complete the review questions

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A challenging read - print it our grab a highlighter and give it a go

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A challenging read - print it our grab a highlighter and give it a go

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Milankovitch cycles. Source: UCAR

A Milankovitch cycle is a cyclical movement related to the Earth's orbit around the Sun. There are three of them: eccentricity, axial tilt, and precession. According to the Milankovitch Theory, these three cycles combine to affect the amount of solar heat that's incident on the Earth's surface and subsequently influence climatic patterns.

Eccentricity

The path of the Earth's orbit around the sun is not a perfect circle, but an ellipse. This elliptical shape changes from less elliptical (nearly a perfect circle) to more elliptical and back, and is due to the gravitational fields of neighboring planets (particularly the large ones - Jupiter and Saturn). The measure of the shape's deviation from being a circle is called its eccentricity.

That is, the larger the eccentricity, the greater is its deviation from a circle. Thus, in terms of eccentricity, the Earth's orbit undergoes a cyclical change from less eccentric to more eccentric and back. One complete cycle for this kind of variation lasts for about 100,000 years.

Axial Tilt

We know the earth is spinning around its own axis, which is the reason why we have night and day. However, this axis is not upright. Rather, it tilts at angles between 22.1-degrees and 24.5 degrees and back. These angles are measured between the angle of the axis to an imaginary line normal (perpendicular) to the Earth's plane of orbit. A complete cycle for the axial tilt lasts for about 41,000 years.

Greater tilts mean that the hemispheres closer to the Sun, i.e., during summer, will experience a larger amount of heat than when the tilt is less. In other words, regions in the extreme upper and lower hemispheres will experience the hottest summers and the coldest winters during a maximum tilt.

Precession

Aside from the tilt, the axis also wobbles like a top. A complete wobble cycle is more or less 26,000 years. This motion is caused by tidal forces from the Sun and Moon.

Precession as well as tilting are the reasons why regions near and at the poles experience very long nights and very long days at certain times of the year. For example, in Norway, the Sun never completely descends beneath the horizon between late May to late July.

The Milankovitch Cycles are among the arguments fielded by detractors of the Global Warming concept. According to them, the Earth's current warming is just a part of a series of cyclical events that take thousands of years to complete, and hence cannot be prevented.

You can read more about milankovitch cycle here in Universe Today. Here are the links:

There's more about it at USGS and NASA. Here are a couple of sources there:

Here are two episodes at Astronomy Cast that you might want to check out as well:

References:
NASA Earth Observatory
NOAA Website

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Milankovitch cycles. Source: UCAR A Milankovitch cycle is a cyclical movement related to the Earth's orbit around the Sun. There are three of them: eccentricity, axial tilt, and precession. According to the Milankovitch Theory, these three cycles combine to affect the amount of solar heat that's incident on the Earth's surface and subsequently influence climatic ...

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A brief summary of what you may already know

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Climate Change 101 with Bill Nye | National Geographic

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Changes to the distribution of CO2 within the atmosphere during a year.

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NASA | A Year in the Life of Earth's CO2