The ORCA West Coast Regional Project - Use of Top-Down Modeling in a Regional Carbon Budget Approach to Estimate Gross Carbon Fluxes for Oregon-California

The ORCA project aims at determining the regional carbon balance of Oregon and northern California, with a special focus on the effect of disturbance history and climate variability on carbon sources and sinks. ORCA provides a regional test of the overall NACP strategy by demonstrating bottom-up and model-data fusion approaches to derive carbon balances at subregional to regional scales. The top-down modeling component of ORCA focuses on coupling simple process models for gross primary productivity (GPP), autotrophic (RA) and heterotrophic respiration (RH) with atmospheric transport modeling to interpret measured carbon dioxide concentration data. This approach builds on high-resolution remote sensing products (e.g. Landsat, MODIS) as well as re-analysis meteorological datasets (EDAS-40, DayMet) to drive the models. We couple BRAMS (Brazilian Regional Atmospheric Modeling System) mesoscale modeling to the STILT (Stochastic Time-Inverted Lagrangian Transport) footprint model to identify sources and sinks for carbon that influence observed carbon dioxide concentrations at measurement sites in the ORCA domain. This approach of linking surface fluxes to time series of atmospheric data allows one to extract information from the latter for process model optimization, with the objective of obtaining regionally representative parameter settings for different combinations of ecoregion and land cover type. We present a proof-of-concept of the ORCA top-down modeling approach by comparing modeled to measured carbon dioxide concentration data. This comparison also addresses the uncertainties introduced by different components of this approach. To demonstrate the effect of the improved process model parameterization, the results are compared with regional fluxes derived by the ORCA bottom-up modeling component.