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DOI10.5194/acp-17-7067-2017
Assimilation of satellite NO2 observations at high spatial resolution using OSSEs
Liu, Xueling1; Mizzi, Arthur P.2; Anderson, Jeffrey L.3; Fung, Inez Y.1; Cohen, Ronald C.1,4
2017-06-15
发表期刊ATMOSPHERIC CHEMISTRY AND PHYSICS
ISSN1680-7316
EISSN1680-7324
出版年2017
卷号17期号:11
文章类型Article
语种英语
国家USA
英文摘要

Observations of trace gases from space-based instruments offer the opportunity to constrain chemical and weather forecast and reanalysis models using the tools of data assimilation. In this study, observing system simulation experiments (OSSEs) are performed to investigate the potential of high space-and time-resolution column measurements as constraints on urban NOx emissions. The regional chemistry-meteorology assimilation system where meteorology and chemical variables are simultaneously assimilated is comprised of a chemical transport model, WRF-Chem, the Data Assimilation Research Testbed, and a geostationary observation simulator. We design OSSEs to investigate the sensitivity of emission inversions to the accuracy and uncertainty of the wind analyses and the emission updating scheme. We describe the overall model framework and some initial experiments that point out the first steps toward an optimal configuration for improving our understanding of NOx emissions by combining space-based measurements and data assimilation. Among the findings we describe is the dependence of errors in the estimated NOx emissions on the wind forecast errors, showing that wind vectors with a RMSE be low 1m s(-1) allow inference of N-x emissions with a RMSE of less than 30 mol/(km(2) x h) at the 3 km scale of the model we use. We demonstrate that our inference of emissions is more accurate when we simultaneously update both NOx emissions and NOx concentrations instead of solely updating emissions. Furthermore, based on our analyses, we recommend carrying out meteorology assimilations to stabilize NO2 transport from the initial wind errors before starting the emission assimilation. We show that wind uncertainties (calculated as a spread around a mean wind) are not important for estimating NOx emissions when the wind uncertainties are reduced below 1.5m s(-1). Finally, we present results assessing the role of separate vs. simultaneous chemical and meteorological assimilation in a model framework without covariance between the meteorology and chemistry.


领域地球科学
收录类别SCI-E
WOS记录号WOS:000403219200001
WOS关键词ENSEMBLE KALMAN FILTER ; AIR-QUALITY ; METHANE EMISSIONS ; NEXT-GENERATION ; UNITED-STATES ; ATMOSPHERIC COMPOSITION ; TRANSPORT MODEL ; SURFACE OZONE ; SYSTEM ; SPACE
WOS类目Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/16214
专题地球科学
作者单位1.Univ Calif Berkeley, Dept Earth & Planetary Sci, Berkeley, CA 94720 USA;
2.Natl Ctr Atmospher Res, Atmospher Chem Observat & Modeling Lab, POB 3000, Boulder, CO 80307 USA;
3.Natl Ctr Atmospher Res, Inst Math Appl Geosci, POB 3000, Boulder, CO 80307 USA;
4.Univ Calif Berkeley, Dept Chem, Berkeley, CA 94720 USA
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Liu, Xueling,Mizzi, Arthur P.,Anderson, Jeffrey L.,et al. Assimilation of satellite NO2 observations at high spatial resolution using OSSEs[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2017,17(11).
APA Liu, Xueling,Mizzi, Arthur P.,Anderson, Jeffrey L.,Fung, Inez Y.,&Cohen, Ronald C..(2017).Assimilation of satellite NO2 observations at high spatial resolution using OSSEs.ATMOSPHERIC CHEMISTRY AND PHYSICS,17(11).
MLA Liu, Xueling,et al."Assimilation of satellite NO2 observations at high spatial resolution using OSSEs".ATMOSPHERIC CHEMISTRY AND PHYSICS 17.11(2017).
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