# data[].attributes.body
There is the influence of photoacclimation and phytoplankton composition in both (bbp and/or Chl) approaches [by Anonymous]

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Merginge data from satellites and in situ platforms to get a 4D view of carbon pools and constrain modelled fluxes

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Linking surface satellite measurements to vertical distribution [by Session chairs]

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Accurate representation of the spatial and temporal variability of model parameters [by Session chairs]

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Uncertainty estimation and  trends of primary production estimates [by Session chairs]

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Unifying the integration of primary production across interfaces [by Session chairs]

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We do not have the full capability to derive phytoplankton carbon from particle backscatter data. We should question if the coupling of chlorophyll-based EO data and bgc models may be better suited to derive phytoplankton carbon (it is closer to what is measured in situ).

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We do not currently have standardized methods to derive C-phyto in situ.

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We need resolution of bbp vs Chla relationships in subtropical gyres (low biomass issue).

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Methods for synergistic use/data fusion of different information (e.g. satellite surface coverage vs. in situ point high depth resolution) are very limited. [by Anonymous]

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In situ data that consists of phytoplankton carbon measurements is lacking; In data is biased towards open ocean Nano and Pico size fractions. So cannot be applied globally.

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Current scaling factors to derive carbon units (those needed also by modelers) are based only on a few lab experiments and limited set of species, thus lacking spatio-temporal variability for global applications.

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There is the gap of high resolution observations below surface in the water column on phytoplankton composition or phytoplankton pigments.

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We are missing multi-platform approaches to estimate Cphyto below the surface (essential for PP estimation and C budget closure).

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We should develop additional approaches that utilize other optical properties beyond bbp to derive C-phyto.

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Strong temporal variability/dynamics in tidal BC ecosystems (at hourly and tidal scales) [by Session chairs]

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Uncertainty estimation in carbon fluxes [by Session chairs]

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Accuracy of CDOM retrievals in coastal waters (e.g., in dark water bodies where small uncertainties in reflectance lead to large uncertainties in CDOM retrievals, in turbid waters where there is a strong interference by particles with similar absorption properties)

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The decoupling (seasonal, spatial) of CDOM and DOC in coastal waters and open ocean, making the retrieval of DOC from CDOM more challenging

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Sourcing of CDOM and DOC (terrigenous versus marine ; riverine vs effluent) from remote sensing

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Need for better atmospheric corrections (e.g, better accounting for different aerosols contribution, urban gases) in nearshore/coastal waters to ensure better measurements of reflectance at low wavelengths (<500 nm)

Need for enhanced spectral information relative to multispectral sensors (resolution and range at lower wavelengths)

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Lack of a quantitative understanding of processes regulating CDOM dynamics relative to that of DOC, and how this may be influenced by environmental change

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Can we leverage the spectral absorption and/or fluorescence properties of different types of DOM?

Can we measure the DOM fluorescence effects on reflectance (e.g., fluorescence of effluent)?

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Recent and upcoming sensors: OLCI, and PACE and GLIMR in future with improved spectral range/resolutions (UV, hyper spectral) and temporal resolutions (GLIMR).

Polarimeter on PACE to improve atmospheric corrections

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Process-based model of CDOM and DOC cycling in surface waters

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Combination of new measurements on FDOM fluorescence quantum yields in radiative transfer models (Hydrolight) can shed light on the feasibility of doing this.

Hyperspectral reflectance in the UV-visible range (PACE, GLIMR)

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Accuracy of PIC retrievals in coastal, shelf sea environments, or where other highly scattering materials are present

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Remote sensing of DIC from available satellite products

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Pixel-by-pixel uncertainty in satellite products

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Using coupled physical/BGC/Carbonate ecosystem models combined with Satellite/in situ data to better study the ocean biological pump.

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Fully spectral specific inherent optical properties for PIC

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Limited PIC observations in Pacific, Southern Ocean, coastal regions: need wider geographic spread of field observations

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Top-down approaches for DIC and PIC remote sensing

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Optimal estimation of air/sea CO2 flux using best-available data to parameterise the gas transfer velocity (K)

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Choice of sea surface temperature product and data processing approach to best-estimate the air/sea CO2 concentration difference

# data[].attributes.body
Accurate prediction of climatological seawater pCO2 from in situ observations and satellite data products

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Standardize the NN techniques to infer seawater pCO2 and CO2 fluxes, e.g the input data (which SST, SSS, Chl, wind speed, etc products to use), the type of NN and number of layers.

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Uncertain or unpredictable occurrences of EE in time and place, such as sandstorm, bushfire ash, Typhoon, tsunami, etc.

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High frequency and high spatial resolution satellite observation coupled with in-situ underwater measurement of time and place matching

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Satellite derived air-sea CO2 fluxes based on remote sensing products such as SST, SSS, CHL-a, wind speed-direction for coastal and marginal seas.
Natalia Stamataki

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Need to partition TPC into POC and PIC - one measurement protocol for all.

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PACE mission can only be your "dreams come true" mission if you help us make it one.
Join our community of practice and help us make it rainbow magical

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Applications are innovative uses of NASA satellite data to help improve decision-making and provide practical solutions to meet the needs of society. Data products produced by PACE will help monitor water resources and air quality, as well as respond to natural disasters, including flood, volcanic, and wildfire events. The PACE Applications Program will foster the expansion of observatory's science data to inform policy and management decisions.
Why is it Important?
PACE data will be publicly available, offering new ways to view the Earth and its ecosystems. Connecting PACE with applied science is key to realizing the full potential of this innovative, Earth-observing satellite. The PACE Applications Program also aims to build awareness of the PACE mission and its potential societal benefits. Overall, these efforts will enable quick integration of PACE data into decision-making processes and operational tools after launch.

How Does it Work?

The PACE Applications Program will engage two groups:

Community of Practice - People who are familiar with NASA products and routinely use satellite remote sensing data in processes or decision support. Early Adopters are part of this community.

PACE COMMUNITY OF PRACTICE

The PACE Community of Practice (CoP) is made up of those groups and individuals who are familiar with NASA products, have a well-defined need for proposed PACE data products, will optimize their use of PACE products, possibly even before launch as part of the PACE test-bed activities and PACE calibration/validation, and who are capable of applying their own resources (funding, personnel, facilities, etc.) to demonstrate the utility of PACE data for their particular research, application, or model. The Community of Practice includes PACE Early Adopters who have committed to engage in pre-launch applied research to accelerate the integration of PACE products after launch in their specific application that aids decision-making and directly benefits society.

Goals for the COMMUNITY OF PRACTICE

The overall goal of the PACE Community of Practice is to provide individuals and groups with the unique opportunity to network and share information with other members in the use of PACE data in pre-launch research. Through networking and information sharing, the CoP will seek to foster new partnerships and collaboration, generate new knowledge and innovations, and promote interdisciplinary research using PACE data.

COMMUNITY OF PRACTICE Member Benefits

Participate in PACE Applications events including workshops, focus sessions, tutorials, and quarterly webinars: PACE Applications will host multiple events for the Community of Practice to share updates on the mission status, provide support and information on the data products, gather feedback, share schedules and timelines, and answer questions.

Be in the know about PACE: As a member of the CoP, you will be among the first to know about any new features of the science data products and to receive updates and newsletters on the mission and PACE field campaigns.

Learn about access to simulated, proxy, calibration and validation (cal/val) data: CoP members will have access to simulated and proxy PACE data, cal/val data from PACE field campaigns, modeling, and synergistic studies via electronic file transfer through the Ocean Biology Distributed Active Archive Center (OB.DAAC).

Reference lessons learned: CoP members will have the opportunity to interact and exchange lessons learned with the Mission's Early Adopters during quarterly webinars and at the various applications events.

Community of Potential - People who are unfamiliar with satellite data products and PACE capabilities, but might be able to leverage and benefit from PACE data products.

Join Us! Interested in joining the PACE Community of Practice? Sign up by completing our online webform!

Read more about the "Mussel Man" (NASA Earth Observatory)
Learn more about Pseudo-nitzschia (Phytopia)

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Applications are innovative uses of NASA satellite data to help improve decision-making and provide practical solutions to meet the needs of society. Data products produced by PACE will help monitor water resources and air quality, as well as respond to natural disasters, including flood, volcanic, and wildfire events.

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Join us for the PACE training - a week in which we will teach you all the things PACE - in hope to make you a true PACE Ocean Carbon Padawan.. click on the link to learn more

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Background
In 2015, NASA directed the PACE mission to Goddard Space Flight Center following recommendations from the 2010 NASA documentResponding to the Challenge of Climate and Environmental Change: NASA's plan for Climate-Centric Architecture for Earth Observations and Applications from Space. This direction ultimately realized the research communities' decade-plus push for a future Earth-observing satellite mission to meet growing needs for scientific discovery. A central objective of PACE is enabling new insights on the sensitivity of global aquatic ecology and biogeochemistry to environmental change.

While heritage ocean color missions have provided desperately needed platforms for observing grossly under-sampled ocean ecosystems since 1997, the oceanographic community quickly recognized the need for enhanced satellite measurement capabilities to address the additional issues of changing phytoplankton distributions, ecosystem and habitat health, and carbon fluxes in the global oceans. The second objective of PACE is the retrieval of advanced atmospheric data products with the goals of reducing uncertainties in global climate models and improving our interdisciplinary understanding of the ocean-atmosphere system. Despite the substantial achievements of heritage satellite missions, better constraining aerosol and cloud properties and improving our understanding of effective radiative forcing requires significant advances in measurement capabilities. Phrased simply, PACE is NASA's next great investment in ocean, clouds, and atmospheric data records to enable continued and advanced insight into oceanographic and atmospheric responses to Earth's changing climate.
Read the proposal

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What's behind the curtain of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission? Training Activity - apply by 11 March 2022

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Background In 2015, NASA directed the PACE mission to Goddard Space Flight Center following recommendations from the 2010 NASA documentResponding to the Challenge of Climate and Environmental Change: NASA's plan for Climate-Centric Architecture for Earth Observations and Applications from Space .

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Direct or indirect earth observation techniques to monitor the dynamics of sediment carbon in blue carbon ecosystems (mangrove, seagrass, salt marsh)

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Cost-effective monitoring using EO techniques to track the progress of rehabilitation-restoration in blue carbon ecosystems

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Fusion of optical and microwave/SAR data provides a promising approach for characterization of tidal wetland interfaces, including wetland vegetation characteristics, inundation regimes, and their impact on carbon fluxes [by Session chairs]

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Hyperspectral observations (PACE, GLIMR, SBG) across spatial scales.

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Multiple images per day from a geostationary platform (GLIMR), to capture tidal dynamics in blue carbon ecosystems, and also monitor blue carbon ecosystems (e.g., seagrass meadows) under optimum conditions

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Longtime series and fundamental understanding (e.g. lab experiments, models) is needed to complement satellite observations and understand the full impact of extreme events

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Measuring aerosol deposition from space and extend observations over the ocean to cal/val

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1. Inclusion of particles of all sizes
2. Resolved size spectrum
3. Quality control and consistency across datasets
4. Spatiotemporal scale mismatch
5. Optically complex coastal and shelf waters
6. Inter-mission consistency
7. Partitioning POC into biogeochemically important components (phyto, NAP, detritus, heterotrophs)
8. Reconstructing vertical profiles using remote and in-situ sensors
9. Understand the fate of POC and its fractions globally, i.e. POC’s role in the biological pump

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1. Submicrometer particles inefficiently retained by GFF
2. Reliable quantification of largest size fractions
3. Documentation of methods for reliable uncertainty assessment and QC of historical datasets
4. Undersampled conditions
5. Appropriate flagging of POC according to water types
6. Separating POC and non-POC particles.
7. Direct measurement methodsInsufficient knowledge of IOPs (ie VSF) for optics-based POC apportionment
8. Relationship between optical variables (eg from sensors on autonomous platforms) and POC
9. Interannual POC export variability in empirical and mechanistic models
10. Fate of POC in shallow seas
11. Role of horizontal advection

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1. Develop better methodological standards (eg IOCCG)
2. Combine filtration with optics-based particle counting and sizing
3. Improved documentation of methods in databases (eg SeaBASS): retrospective + new submissions
4. Constraints from BGC-Argo
5. Incorporation of mechanistic principles in algorithms
6. Increased use of geostationary and hyperspectral data + in situ sensors
7. Support basic research on polarization properties of particles
8. Exploit polarization sensors (and combination of bbp/cp in situ)
9. Development of POC algorithms for in situ optical data (eg BGC-Argo)
10. Merging of satellite and BGC-Argo data via statistical or model assimilation methods
11. “Optical sediment traps” on BGC-Argo floats
12. Data-driven estimates of vertical POC fluxes
13. Constraining numerical models using remote and in situ autonomous sensors

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Develop assimilating models further. ECCO-Darwin is excellent, but we can go further in this direction. This approach can help integrate our developing understanding of air-sea fluxes with observations and calculations within the interior.

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Work towards a Digital Twin of the Ocean including Ocean Carbon. An important stepping stone is bringing more Ocean Colour products into the mix.

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Definitely need more events such as this. Need more "flux people", but I expect other topic communities were also under-represented. Good to see a reasonable gender balance. It would also be good to strengthen truly global participation and access. Also, across race, disability and ND.