23 Oct. Charla: Improving regional air quality predictions: Assimilation of next generation geostationary retrievals and multiplatform inversion of wildfire emissions

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23octEl Dr. Pablo Saide (Center for Global & Regional Environmental Research, University of Iowa) dictará el próximo Jueves 23 de Octubre de 2014, la charla: «Improving regional air quality predictions: Assimilation of next generation geostationary retrievals and multiplatform inversion of wildfire emissions»

A las 14:30 hrs. en la SALA DE SEMINARIOS- 5TO PISO, DPTO. GEOFÍSICA- FCFM. (Blanco Encalada 2002)

La charla será transmitida por streaming en: https://new.livestream.com/accounts/7520184

Resumen: 

Two studies will be shown:
1) Planned geostationary satellites will provide aerosol optical depth (AOD) retrievals at high temporal and spatial resolution which will be incorporated to current assimilation systems that use low-earth orbiting (e.g., MODIS) AOD. The impacts of such additions are explored in a real case scenario using AOD from the GOCI sensor on board of the COMS, a geostationary satellite observing northeast Asia. The addition of GOCI AOD into the assimilation system generated positive impacts, which were found to be substantial with respect of only assimilating MODIS AOD. We found that GOCI AOD can help significantly to improve surface air quality simulations in Korea for dust, biomass mass burning smoke and anthropogenic pollution episodes when the model represents the extent of the pollution episodes and retrievals are not contaminated by clouds. We anticipate future geostationary missions to considerably contribute to air quality forecasting and provide better reanalyses for health assessments and climate studies.

2) We coupled airborne, ground-based, and satellite observations; regional simulations; and a novel inverse modeling technique to constrain hourly smoke emissions from the 2013 Rim Fire: one of the largest known fires to occur in California, USA. We find that constrained emissions are a factor of ~3 higher than initial unconstrained estimates and show notable nocturnal enhancements, sometimes over a factor of 20, highlighting the need for better characterizing diurnal profiles currently used when modeling extreme fire events. Constraints using only satellite data result in smaller enhancements, likely because of missing retrievals near the emissions source. This underestimate suggests that a multiplatform approach is required to resolve emissions from these events. Constrained emissions correlate better with daily burned area data, and predictions using constrained emissions agree better with trace gas and aerosol measurements and modify downwind meteorology through aerosol feedbacks, emphasizing the need to further reduce uncertainties in exceptional fire emissions.

Para ver la charla en directo: https://new.livestream.com/accounts/7520184

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