科技报告详细信息
Air Quality Modeling Using the NASA GEOS-5 Multispecies Data Assimilation System
Keller, Christoph A ; Pawson, Steven ; Wargan, Krzysztof ; Weir, Brad
关键词: AIR QUALITY;    DATA SYSTEMS;    EARTH OBSERVING SYSTEM (EOS);    NITROGEN DIOXIDE;    NITROGEN OXIDES;    OZONE;    ATMOSPHERIC CHEMISTRY;    CARBON MONOXIDE;    CHEMICAL COMPOSITION;    TRACE ELEMENTS;    ENVIRONMENT MODELS;    FORECASTING;   
RP-ID  :  GSFC-E-DAA-TN51371
学科分类:地球科学(综合)
美国|英语
来源: NASA Technical Reports Server
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【 摘 要 】

The NASA Goddard Earth Observing System (GEOS) data assimilation system (DAS) has been expanded to include chemically reactive tropospheric trace gases including ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). This system combines model analyses from the GEOS-5 model with detailed atmospheric chemistry and observations from MLS (O3), OMI (O3 and NO2), and MOPITT (CO). We show results from a variety of assimilation test experiments, highlighting the improvements in the representation of model species concentrations by up to 50% compared to an assimilation-free control experiment. Taking into account the rapid chemical cycling of NO2 when applying the assimilation increments greatly improves assimilation skills for NO2 and provides large benefits for model concentrations near the surface. Analysis of the geospatial distribution of the assimilation increments suggest that the free-running model overestimates biomass burning emissions but underestimates lightning NOx emissions by 5-20%. We discuss the capability of the chemical data assimilation system to improve atmospheric composition forecasts through improved initial value and boundary condition inputs, particularly during air pollution events. We find that the current assimilation system meaningfully improves short-term forecasts (1-3 day). For longer-term forecasts more emphasis on updating the emissions instead of initial concentration fields is needed.

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