JuliaCon 2022 (Times are UTC)

Terrestrial ecosystems (i.e., not ocean) have been absorbing about a third of human CO2 emissions, mitigating climate change as atmospheric carbon goes into biomass or soil organic matter. However, it is unclear if this carbon sink will continue in the future. The scientific community uses measurements from field site and satellite remote sensing to understand mechanisms regulating this behavior and create models to make predictions. However, efforts are segmented into specific disciplines (e.g., field experimentalists, modelers, plant ecologists, hydrologists) that rarely collaborate. This is due to using different programming languages (i.e., experimentalists using scripting language such as Python or R, and modelers using fast languages such as Fortran), or the nature of scientific publications encouraging small teams. In recent decades, global standardized databases are being created, as well as community open-source research tools, and Julia, a scripting language as fast as Fortran. This opens the door for collaboration in land-atmosphere exchange science. We use Julia, GitHub, and packages such as Franklin.jl and WGLMakie.jl to create CUPofTEA, a community platform to host versioned analysis and visualizations of land-atmosphere exchange science across fields. We demonstrate the workflow with DAMMmodel.jl, a package to analyze and visualize the response of CO2 emission from ecosystems to soil moisture and temperature, and global database of ecosystem (FLUXNET) and soil (COSORE) fluxes.