Monday, 11 January 2016: 5:00 PM
Room 356 ( New Orleans Ernest N. Morial Convention Center)
Atmospheric transport model errors are one of the main contributors to the uncertainty affecting CO2 inverse flux estimates, but have not been quantified thoroughly. This study aims to assess the transport errors over the Mid-Continental Intensive domain with an ensemble of simulations created with the Weather Research and Forecasting (WRF) mesoscale model using different physical parameterizations (e.g., planetary boundary layer (PBL) schemes and land surface models (LSMs),cumulus parameterizations and microphysics parameterizations). Modeled meteorological variables and atmospheric CO2 concentrations were compared to observations (e.g., radiosondes, AmeriFlux and CO2 mixing ratio towers) during the summer of 2008. The model-data mismatch for several meteorological variables (i.e., wind speed, wind direction and PBL height) was used to examine the spread of the ensemble and identify the model configurations that were systematically biased. Then we present a study of the sensitivity of atmospheric conditions to the choice of physical parameterization, to identify the parameterization driving the model-to-model variability in atmospheric CO2 concentrations at the mesoscale over the MCI domain. Preliminary results show that wind speed and wind direction are influenced by choice of PBL schemes, whereas the PBL height is influenced by the choice of PBL scheme and LSM. Across the domain, the monthly average bias in wind speed is within the range of ±2m/s, wind direction is within ±25 degrees and PBL height within ±500 m. Finally, our sensitivity test shows that all physical parameterizations contribute to the model-to-model variability in atmospheric CO2 concentrations except for the microphysics parameterization. Future work will be to describe these transport errors in the regional atmospheric inversions using this ensemble, for the year of 2008.
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