Impacts of geostationary satellite measurements on CO forecasting: An observing system simulation experiment with GEOS-Chem/LETKF data assimilation system

被引：15

作者：

Yumimoto, Keiya ^{[1
]}

机构：

[1] Japan Meteorol Agcy, Meteorol Res Inst, Tsukuba, Ibaraki 3050052, Japan

来源：

ATMOSPHERIC ENVIRONMENT | 2013年 / 74卷

基金：

日本学术振兴会;

关键词：

Data assimilation; Chemical transport model; Ensemble Kalman filter; Observing system simulation experiment; Geostationary satellite; East Asia; AIR-QUALITY; OZONE; EMISSIONS; POLLUTION; MODEL; NO2;

D O I：

10.1016/j.atmosenv.2013.03.032

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

We developed a chemical data assimilation system based on the GEOS-Chem global chemical transport model (CTM) and an ensemble-based data assimilation method, and performed an observing system simulation experiment (OSSE) to evaluate the impact of geostationary (GEO) satellite data obtained with a multi-spectral (thermal infrared (TIR) and near infrared (NIR)) sensor on air quality forecasting in East Asia. Initial conditions determined by assimilation of the three observation sets improved the forecasting of trans-boundary CO outflow. The performance of GEO satellite with TIR sensor (GEO-TIR) was better than that of LEO satellite with TIR sensor (LEO-TIR). However, in Seoul district (the Korean Peninsula) and Northern Kyushu (western Japan), the positive impact of the wider coverage and higher frequency of GEO disappeared when the forecast time was longer than 48 h. CEO satellite with NIR and TIR sensor (GEO-NIR + TIR) improved the forecast most, reducing the root mean square difference (RMSD), normalized mean bias, and normalized mean difference by more than 20% even for a forecast time longer than 48 h. Using the LEO-TIR result as a benchmark, we evaluated the ability of GEO-NIR + TIR to improve the forecast. The 60-h CO forecasting performances of GEO-TIR and GEO-NIR + TIR were about 30% and 120% better, respectively, than that of LEO-TIR The wider coverage and higher frequency of CEO therefore improved the RMSD by 30%, and the higher sensitivity in the lower troposphere of NIR + TIR improved it by an additional 90%. Thus, the higher sensitivity in the lower troposphere of NIR + TIR as well as the wider coverage and higher frequency of GEO had a notably positive impact on the forecasting of trans-boundary pollutants over East Asia. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：123 / 133

页数：11

共 48 条

[41] Uno I., J JAPAN SOC IN PRESS
[42] Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling
van der Werf, G. R.
Morton, D. C.
DeFries, R. S.
Giglio, L.
Randerson, J. T.
Collatz, G. J.
Kasibhatla, P. S.
[J]. BIOGEOSCIENCES, 2009, 6 (02) : 235 - 249
[43] Investigating the response of East Asian ozone to Chinese emission changes using a linear approach
Yamaji, Kazuyo
Uno, Itsushi
Irie, Hitoshi
[J]. ATMOSPHERIC ENVIRONMENT, 2012, 55 : 475 - 482
[44] Adjoint inversion modeling of Asian dust emission using lidar observations
Yumimoto, K.
Uno, I.
Sugimoto, N.
Shimizu, A.
Liu, Z.
Winker, D. M.
[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2008, 8 (11) : 2869 - 2884
[45] Yumimoto K., 2011, GEOPHYS RES LETT, V38
[46] Adjoint inverse modeling of CO emissions over Eastern Asia using four-dimensional variational data assimilation
Yumimoto, Keiya
Uno, Itsushi
[J]. ATMOSPHERIC ENVIRONMENT, 2006, 40 (35) : 6836 - 6845
[47] Asian emissions in 2006 for the NASA INTEX-B mission
Zhang, Q.
Streets, D. G.
Carmichael, G. R.
He, K. B.
Huo, H.
Kannari, A.
Klimont, Z.
Park, I. S.
Reddy, S.
Fu, J. S.
Chen, D.
Duan, L.
Lei, Y.
Wang, L. T.
Yao, Z. L.
[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2009, 9 (14) : 5131 - 5153
[48] Ozone air quality measurement requirements for a geostationary satellite mission
Zoogman, Peter
Jacob, Daniel J.
Chance, Kelly
Zhang, Lin
Le Sager, Philippe
Fiore, Arlene M.
Eldering, Annmarie
Liu, Xiong
Natraj, Vijay
Kulawik, Susan S.
[J]. ATMOSPHERIC ENVIRONMENT, 2011, 45 (39) : 7143 - 7150

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