Cooperative Institute for Research in the Atmosphere

WRF-Chem/DART: Introduction, Application, Verification, and Compact Phase Space Retrievals (CPSRs)

Air pollution is linked to lung and heart disease and other human health problems. It is also linked to regional climate change impacts with urban areas bearing the greatest burden of those impacts. In the United States its estimated costs range between $71B – $277B (0.7% – 2.8% of the 2005 GDP) annually. Clearly air pollution is an important social and scientific problem. To address the impacts of air pollution, policymakers and air quality managers rely on cutting-edge science to establish regulations and make management decisions to reduce and control air pollution with cost- effective approaches. WRF-Chem/DART – a regional chemical weather forecasting/ensemble data assimilation system is one such research/forecasting tool used in the United States, China, Mexico, Germany, and Canada to study and forecast air quality. WRF-Chem/DART integrates WRF-Chem (the Weather Research and Forecasting (WRF) model with online chemistry) into DART (the Data Assimilation Research Testbed) and includes the ability to assimilate: meteorology observations; in situ air chemistry observations; and satellite-based air chemistry observations (MOPITT CO full and partial column retrievals, IASI CO and O3 full and partial column retrievals, MODIS AOD total column retrieval, and OMI NO2 total column retrievals). In this talk, I will introduce WRF- Chem/DART and discuss its capabilities; application (FRAPPE, PANDA, and KORUS); and verification. Chemical data assimilation faces a number of challenges: spatially and temporally sparse in situ and satellite-based observations; indirect satellite observations (satellite retrievals); retrieval profile observations with large data-volume, low information density, and significant observation error covariance; emissions with large but unknown uncertainties, and non-Gaussian distributions. In WRF-Chem/DART we introduced Compact Phase Space Retrievals (CPSRs) to address the retrieval profile assimilation challenges. I will discuss CPSRs and their application to full and truncated retrieval profiles. I will close the talk with a discussion of some of the more important/difficult challenges still facing chemical data assimilation.