ccmmf · dlebauer · Jul 17, 2024 · Jul 10, 2024 · Jul 16, 2024 · Jul 17, 2024
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 # California Cropland Monitoring and Modeling Framework
 
 ## About
+
+The California Cropland Monitoring and Modeling Framework (CCMMF) will be a biogeochemical model and data integration pipeline to generate current year inventories and future projections of soil carbon (SOC) stocks and greenhouse gas fluxes (GHG) from California’s croplands. 
+CCMMF will leverage Bayesian techniques to combine model predictions and heterogeneous datasets into unified wall-to-wall inventories and climate and scenario-based projections. 
+Data layers will be generated as ensemble projections to facilitate propagation of uncertainty through downstream applications.
+
+CCMMF will produce new gridded time series of key agronomic practices including planting, harvest, irrigation, and tillage at a consistent temporal resolution. 
+These agronomic management time series will be generated by combining remotely sensed data with agronomic statistics and biogeochemical modeling.
+The biogeochemistry model will be built on the SImplified PhotosyNthesis and EvapoTranspiration model (SIPNET), expanded to represent agronomic management, nitrogen cycling, and fluxes of nitrous oxide and methane. 
+We will utilize existing and newly-derived remote sensing of annual land management and agricultural practices to drive the model will produce consistent model estimates that do not depend on obtaining records from individual farmers. 
+The statistical workflow engine will extend the Predictive Ecosystem Analyzer (PEcAn) to support annual updates and both climate-based and management scenario-based projections.
+
+The combination of a simplified biogeochemistry model that simulates agronomic practices from remote-sensed inputs and an open, consistent, variance-explicit data framework will allow CCMMF to achieve robust estimates of SOC and GHG inventories across lands with highly varied but coarsely measured management. 
+All data and software that is part of CCMMF will be open, free, and deployable on state computing resources. 
+This requirement sets a bar for transparency, and a foundation for future innovation and transferability, that is not possible with the current suite of proprietary systems.
+
+## People 
+
+- Chris Black, Pools and Fluxes LLC
+- David LeBauer, The LeBauer Approach LLC and The University of Arizona
+- Mike Dietze, Boston University
+- Rob Kooper, University of Illinois and National Center for Supercomputing Applications
+- Mike Longfritz
+- Shawn Serbin, NASA
+
+## Research Partners and External Stakeholders
+
+- National Aeronautics and Space Administration
+- California Air Resources Board
+
+## Contributing
+
+This section will be developed as the project gets under way. In the mean time, feel free to reach out directly to team members or through our [GitHub
+Discussions](https://github.com/orgs/ccmmf/discussions).