Highlight issues for A wide array of programs in the earth sciences are working on challenges that cross the generalizing this use same domains as this project. case (e.g. for ref. architecture) More Information Under development (URLs) Earth, Environmental and Polar Science> Use Case 50: AmeriFlux and FLUXNET Use Case Title DOE-BER AmeriFlux and FLUXNET Networks Vertical (area) Research: Earth Science Author/Company/Email Deb Agarwal, Lawrence Berkeley Lab. Actors/Stakeholders AmeriFlux scientists, Data Management Team, ICOS, DOE TES, USDA, NSF, and Climate and their roles and modelers. responsibilities AmeriFlux Network and FLUXNET measurements provide the crucial linkage between Goals organisms, ecosystems, and process-scale studies at climate-relevant scales of landscapes, regions, and continents, which can be incorporated into biogeochemical and climate models. Results from individual flux sites provide the foundation for a growing body of synthesis and modeling analyses. AmeriFlux network observations enable scaling of trace gas fluxes (CO2, water vapor) Use Case Description across a broad spectrum of times (hours, days, seasons, years, and decades) and space. Moreover, AmeriFlux and FLUXNET datasets provide the crucial linkages among organisms, ecosystems, and process-scale studies—at climate-relevant scales of landscapes, regions, and continents—for incorporation into biogeochemical and climate models Current Compute(System) NERSC Solutions Storage NERSC Networking ESNet Software EddyPro, Custom analysis software, R, python, neural networks, Matlab. towers in AmeriFlux and over 500 towers distributed ≈150 Big Data Data Source globally collecting flux measurements. Characteristics (distributed/centralized) Volume (size) Velocity (e.g. real time) Variety The flux data is relatively uniform, however, the (multiple datasets, biological, disturbance, and other ancillary data needed to mashup) process and to interpret the data is extensive and varies widely. Merging this data with the flux data is challenging in today’s systems. Variability (rate of change)
Highlight issues for generalizing this use case (e.g. for ref. architecture) A wide array of programs in the earth sciences are working on challenges that cross the same domains as this project. More Information (URLs) Under development Earth, Environmental and Polar Science> Use Case 50: AmeriFlux and FLUXNET Use Case Title DOE-BER AmeriFlux and FLUXNET Networks Vertical (area) Research: Earth Science Author/Company/Email Deb Agarwal, Lawrence Berkeley Lab. Actors/Stakeholders and their roles and responsibilities AmeriFlux scientists, Data Management Team, ICOS, DOE TES, USDA, NSF, and Climate modelers. Goals AmeriFlux Network and FLUXNET measurements provide the crucial linkage between organisms, ecosystems, and process-scale studies at climate-relevant scales of landscapes, regions, and continents, which can be incorporated into biogeochemical and climate models. Results from individual flux sites provide the foundation for a growing body of synthesis and modeling analyses. Use Case Description AmeriFlux network observations enable scaling of trace gas fluxes (CO2, water vapor) across a broad spectrum of times (hours, days, seasons, years, and decades) and space. Moreover, AmeriFlux and FLUXNET datasets provide the crucial linkages among organisms, ecosystems, and process-scale studies—at climate-relevant scales of landscapes, regions, and continents—for incorporation into biogeochemical and climate models Current Solutions Compute(System) NERSC Storage NERSC Networking ESNet Software EddyPro, Custom analysis software, R, python, neural networks, Matlab. Big Data Characteristics Data Source (distributed/centralized) ≈150 towers in AmeriFlux and over 500 towers distributed globally collecting flux measurements. Volume (size) Velocity (e.g. real time) Variety (multiple datasets, mashup) The flux data is relatively uniform, however, the biological, disturbance, and other ancillary data needed to process and to interpret the data is extensive and varies widely. Merging this data with the flux data is challenging in today’s systems. Variability (rate of change)