Quantification of Transport Errors in Regional CO2 Inversions with a Calibrated WRF-Chem Physics-based Ensemble

Abstract:

Atmospheric inversions have been used to assess biosphere-atmosphere CO₂ surface exchanges at various scales, but variability among inverse flux estimates remain significant even at fine scales. Atmospheric transport errors are presumed to be one of the main contributors of this variability. However, few studies have quantified them thoroughly. Previous studies have quantified systematic errors affecting inversion estimates by using ensemble techniques but not limited to transport errors (e.g., different amount of observations, inverse methodologies, prior fluxes). Here, we isolated the transport errors and propagated them into CO₂ mixing ratios using a multi-physics ensemble created with the Weather Research and Forecast (WRF) mesoscale model. The transport differences of this ensemble will come exclusively from the different physical parameterization used (e.g., planetary boundary layer (PBL) schemes, land surface model (LSMs), cumulus parameterizations and microphysics parameterizations). Each simulation was coupled to the same CO₂ surface fluxes from CarbonTracker, which allow us to generate simulated atmospheric CO₂ mixing ratios. We evaluate the atmospheric transport errors over a highly instrumented (i.e., atmospheric soundings, in-situ CO₂ measurements) area, the Mid-Continental Intensive (MCI) region, for 2008 summer period. Meteorological variables (i.e., wind speed, wind direction and PBL height) are used to calibrate our ensemble and verify that we generated an ensemble that represents the transport errors over the region. Simulated atmospheric CO₂ mixing ratios from this calibrated ensemble are used to understand and estimate the contribution of transport errors in CO₂ mixing ratios. Using the flatness of the rank histogram as a metric we were able to find a calibrated ensemble that represents transport errors for the all three meteorological variables. Finally, we present how this calibrated ensemble can be used to understand and evaluate the impact of transport errors on atmospheric CO₂ mixing ratios.