气候变化领域集成服务门户(CCPortal): Enhancing Accuracy of Air Quality and Temperature Forecasts During Paddy Crop Residue Burning Season in Delhi Via Chemical Data Assimilation

CCPortal

DOI	10.1029/2020JD033019
	Enhancing Accuracy of Air Quality and Temperature Forecasts During Paddy Crop Residue Burning Season in Delhi Via Chemical Data Assimilation
	Kumar R.; Ghude S.D.; Biswas M.; Jena C.; Alessandrini S.; Debnath S.; Kulkarni S.; Sperati S.; Soni V.K.; Nanjundiah R.S.; Rajeevan M.
发表日期	2020
ISSN	2169897X
卷号	125 期号:17
英文摘要	This paper examines the accuracy of Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) generated 72 hr fine particulate matter (PM2.5) forecasts in Delhi during the crop residue burning season of October-November 2017 with respect to assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals, persistent fire emission assumption, and aerosol-radiation interactions. The assimilation significantly pushes the model AOD and PM2.5 toward the observations with the largest changes below 5 km altitude in the fire source regions (northeastern Pakistan, Punjab, and Haryana) as well as the receptor New Delhi. WRF-Chem forecast with MODIS AOD assimilation, aerosol-radiation feedback turned on, and real-time fire emissions reduce the mean bias by 88–195 μg/m3 (70–86%) with the largest improvement during the peak air pollution episode of 6–13 November 2017. Aerosol-radiation feedback contributes ~21%, ~25%, and ~24% to reduction in mean bias of the first, second, and third days of PM2.5 forecast. Persistence fire emission assumption is found to work really well, as the accuracy of PM2.5 forecasts driven by persistent fire emissions was only 6% lower compared to those driven by real fire emissions. Aerosol-radiation feedback extends the benefits of assimilating satellite AOD beyond PM2.5 forecasts to surface temperature forecast with a reduction in the mean bias of 0.9–1.5°C (17–30%). These results demonstrate that air quality forecasting can benefit substantially from satellite AOD observations particularly in developing countries that lack resources to rapidly build dense air quality monitoring networks. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	air quality forecast; assimilation; New Delhi; PM2.5; satellite AOD
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/185796
作者单位	National Center for Atmospheric Research, Boulder, CO, United States; Indian Institute of Tropical Meteorology, Ministry of Earth Sciences (MoES), Pune, India; Centre for Development of Advanced Computing (C−DAC), Pune, India; Ricerca sul Sistema Energetico (RSE) SpA, Milan, Italy; India Meteorological Department, Ministry of Earth Sciences (MoES), New Delhi, India; Ministry of Earth Sciences (MoES), New Delhi, India
推荐引用方式 GB/T 7714	Kumar R.,Ghude S.D.,Biswas M.,et al. Enhancing Accuracy of Air Quality and Temperature Forecasts During Paddy Crop Residue Burning Season in Delhi Via Chemical Data Assimilation[J],2020,125(17).
APA	Kumar R..,Ghude S.D..,Biswas M..,Jena C..,Alessandrini S..,...&Rajeevan M..(2020).Enhancing Accuracy of Air Quality and Temperature Forecasts During Paddy Crop Residue Burning Season in Delhi Via Chemical Data Assimilation.Journal of Geophysical Research: Atmospheres,125(17).
MLA	Kumar R.,et al."Enhancing Accuracy of Air Quality and Temperature Forecasts During Paddy Crop Residue Burning Season in Delhi Via Chemical Data Assimilation".Journal of Geophysical Research: Atmospheres 125.17(2020).