Modeled dataset for the estimation of atmospheric transport errors using a Multi-Physics and Analysis Ensemble on the Midwest US

Atmospheric inversions are used to assess biosphere-atmosphere CO2 surface exchanges. However, large uncertainties exist among inverse flux estimates independent of the spatial scales. Atmospheric transport model errors are one of the main contributors to the uncertainty affecting CO2 inverse flux estimates but have not been quantified thoroughly. The model dataset archived here were used to evaluate atmospheric transport errors over the US upper Midwest with an ensemble of simulations created with the Weather Research and Forecasting (WRF) mesoscale model at 10-km spatial resolution. The various WRF simulations were performed using different meteorological driver datasets and physical parameterizations including planetary boundary layer (PBL) schemes, land surface models (LSMs), cumulus parameterizations and microphysics parameterizations. All the different model configurations were coupled to CO2 fluxes and lateral boundary conditions from the CarbonTracker inversion system to simulate atmospheric CO2 mole fractions. Each model configuration was evaluated from 18 June to 21 July 2008 for the meteorological variables (i.e., PBL height, wind speed, and wind direction) and from 26 June to 22 July 2008 for the CO2 mole fractions. Results shows that the performance of the different model configurations is highly variable over the region, limiting the selection of the optimal configuration. Sensitivity tests indicate that all physical schemes except for the microphysics parametrization influence the variability of in atmospheric CO2 from 3 to 4 ppm.