气候变化领域集成服务门户(CCPortal): Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations

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DOI	10.1016/j.atmosenv.2021.118751
	Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations
	Cheng P.; Pour-Biazar A.; White A.T.; McNider R.T.
发表日期	2022
ISSN	1352-2310
卷号	268
英文摘要	Clouds play an important role in the Earth's climate system since they can affect various physical and chemical processes within the atmosphere. Misplacement of clouds is a major source of error in the numerical weather prediction (NWP) models, and it also impacts the accuracy of air quality simulations since the meteorology and air quality are directly coupled. In this study, a cloud assimilation technique was utilized to improve cloud placement within the Weather Research and Forecasting (WRF) model by assimilating Geostationary Operational Environmental Satellite (GOES)-derived cloud products. Meteorological outputs from the WRF model were then used as inputs for the Community Multiscale Air Quality (CMAQ) model. The impact of cloud assimilation on air quality was tested over the June–September 2016 period. The results indicated that, by modifying model clouds, cloud assimilation corrected surface solar radiation and photochemical reaction rates, altered light sensitive biogenic emissions, adjusted horizontal transport and vertical mixing, and finally improved the prediction of surface ozone concentration. Cloud assimilation improved daytime surface ozone prediction over most of the U.S. domain, with exceptions in California. On average, cloud assimilation improved the prediction of daytime peak ozone and reduced bias by 47% (∼1.5 ppb). The largest improvement was seen over the southeast U.S. region (∼2.6 ppb reduction in daytime peak ozone), where convective clouds are more frequent and transient and biogenic volatile organic compound (VOC) emissions are more intense than elsewhere. © 2021 The Authors
关键词	Biogenic emissions Cloud assimilation CMAQ Geostationary Operational Environmental Satellite (GOES)Ozone Photochemical reaction Solar radiation Volatile organic compound (VOC)WRF
语种	英语
scopus关键词	Air quality; Earth atmosphere; Geostationary satellites; Ozone; Photochemical reactions; Reaction rates; Solar radiation; Weather forecasting; Biogenic emission; Cloud assimilation; Community multi-scale air qualities; Geostationary operational environmental satellite; Geostationary operational environmental satellites; Ozone prediction; Surface ozone; Volatile organic compound; Weather research and forecasting; Weather research and forecasting models; Volatile organic compounds; ozone; volatile organic compound; air quality; cloud cover; detection method; geostationary satellite; GOES; observational method; ozone; solar radiation; summer; volatile organic compound; air monitoring; air quality; Article; boundary layer; circadian rhythm; cloud; forecasting; humidity; meteorology; prediction; simulation; solar radiation; summer; sunlight; surface property; temperature; time series analysis; wind; California; United States
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248160
作者单位	Department of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, AL, United States; Earth System Science Center, University of Alabama in Huntsville, Huntsville, AL, United States
推荐引用方式 GB/T 7714	Cheng P.,Pour-Biazar A.,White A.T.,et al. Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations[J],2022,268.
APA	Cheng P.,Pour-Biazar A.,White A.T.,&McNider R.T..(2022).Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations.ATMOSPHERIC ENVIRONMENT,268.
MLA	Cheng P.,et al."Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations".ATMOSPHERIC ENVIRONMENT 268(2022).