Continental bottom-up data assimilation to support terrestrial carbon cycle and disturbance Monitoring, Reporting, Verification, and Forecasting

The ability to understand the current state of the carbon cycle, at scales from the local to continental, is of pressing importance to increasing our basic science understanding of ecosystem processes and anthropogenic impacts, to national Monitoring, Reporting, and Verification (MRV) requirements, and to finer-scale carbon credit accounting, mitigation efforts, and ecosystem service management. The status quo for such efforts has focused predominantly on the generation of spatially-extensive data layers for individual dimensions of the carbon cycle (e.g. biomass, soil carbon, NEE, NPP), but there is a pressing need to be able to maintain an ongoing, up-to-date synthesis across data sources and project this understanding into the near future. Here we present current results from version 2 of the PEcAn model-data assimilation system, which leverages model-based forecasts to fuse multiple data constraints and provide a complete carbon- and water-cycle budget synthesis. Version 2 extends our spatial scale from CONUS to North America. We also extend the data constraints used in the assimilation from MODIS LAI and LandTrendr aboveground biomass to also include SoilGrids soil carbon and NEE, LE, and soil moisture across a network of eddy-covariance sites. Beyond picking up Canada, Mexico, and Alaska, the extension to a continental-scale also allows us to make explicit comparisons to top-down atmospheric inversions in terms of both overall budgets and spatial and temporal variability in carbon fluxes. For validation we will also leverage country-specific carbon inventory products, satellite soil moisture, and GEDI lidar data. This talk will also touch on the development of new algorithms developed to assimilate discrete disturbance events, to be incorporated into our version 3 product, and their regional-scale validation against fire, pest, and logging disturbances in central Oregon.