Assimilation of microwave brightness temperature in a land data assimilation system with multi-observation operators

被引：13

作者：

Jia, Binghao ^{[1
]}

Tian, Xiangjun ^{[1
]}

Xie, Zhenghui ^{[1
]}

Liu, Jianguo ^{[1
]}

Shi, Chunxiang ^{[2
]}

机构：

[1] Chinese Acad Sci, State Key Lab Numer Modeling Atmospher Sci & Geop, Inst Atmospher Phys, Beijing 100029, Peoples R China

[2] China Meteorol Adm, Natl Meteorol Informat Ctr, Beijing, Peoples R China

来源：

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES | 2013年 / 118卷 / 10期

基金：

中国国家自然科学基金;

关键词：

land data assimilation; observation operator; microwave brightness temperature; soil moisture; Bayesian model averaging; SOIL-MOISTURE; GLOBAL SIMULATION; EMISSION MODEL; PART I;

D O I：

10.1002/jgrd.50377

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

A radiative transfer model (RTM) that provides a link between model states and satellite observations (e.g., brightness temperature) can act as an observation operator in land data assimilation to directly assimilate brightness temperatures. In this study, a microwave Land Data Assimilation System (LDAS) was developed with three RTMs (The radiative transfer model for bare field (QH), land emissivity model (LandEM), and Community Microwave Emission Model (CMEM)) as its multi-observation operators (LDAS-MO). Assimilation experiments using the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) satellite brightness temperature data from July 2005 to December 2008 were then conducted to investigate the impact of the RTMs on the assimilated results over China. It was found that the assimilated volumetric soil-water content using each of the three observation operators improved the estimation of soil moisture content in the top soil layer (0-10cm), with reduced root mean square errors (RMSEs), and increased correlation coefficients with field observations (OBS) as compared to a control run with no assimilation for the absence of frozen or snow-covered conditions. The assimilated soil moisture for the QH model, which was more sensitive to dry soil than the other models, produced closer correlations with OBS in arid and semi-arid regions while smaller RMSEs were observed for LandEM. CMEM agreed most closely with OBS over the middle and lower reaches of the Yangtze River due to its better simulation of the brightness temperature over densely vegetated areas. To improve assimilation accuracy, a Bayesian model averaging (BMA) scheme for the LDAS-MO was developed. The BMA scheme was found to significantly enhance assimilation capability producing the soil moisture analysis, showing the lowest RMSEs and highest correlations with OBS over all areas. It was demonstrated that the BMA scheme with LDAS-MO has the potential to estimate soil moisture with high accuracy.

引用

页码：3972 / 3985

页数：14

共 49 条

[1]

[Anonymous], NOTE, DOI DOI 10.5065/D68S4MVH

[2] Landscapes as patches of plant functional types: An integrating concept for climate and ecosystem models [J].

Bonan, GB ;

Levis, S ;

Kergoat, L ;

Oleson, KW .

GLOBAL BIOGEOCHEMICAL CYCLES, 2002, 16 (02)

[3]

Darcy H., 1856, The Public Fountains of the City of Dijon

[4] AMMA Land Surface Model Intercomparison Experiment coupled to the Community Microwave Emission Model: ALMIP-MEM [J].

de Rosnay, P. ;

Drusch, M. ;

Boone, A. ;

Balsamo, G. ;

Decharme, B. ;

Harris, P. ;

Kerr, Y. ;

Pellarin, T. ;

Polcher, J. ;

Wigneron, J. -P. .

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2009, 114

[5] The ERA-Interim reanalysis: configuration and performance of the data assimilation system [J].

Dee, D. P. ;

Uppala, S. M. ;

Simmons, A. J. ;

Berrisford, P. ;

Poli, P. ;

Kobayashi, S. ;

Andrae, U. ;

Balmaseda, M. A. ;

Balsamo, G. ;

Bauer, P. ;

Bechtold, P. ;

Beljaars, A. C. M. ;

van de Berg, L. ;

Bidlot, J. ;

Bormann, N. ;

Delsol, C. ;

Dragani, R. ;

Fuentes, M. ;

Geer, A. J. ;

Haimberger, L. ;

Healy, S. B. ;

Hersbach, H. ;

Holm, E. V. ;

Isaksen, L. ;

Kallberg, P. ;

Koehler, M. ;

Matricardi, M. ;

McNally, A. P. ;

Monge-Sanz, B. M. ;

Morcrette, J. -J. ;

Park, B. -K. ;

Peubey, C. ;

de Rosnay, P. ;

Tavolato, C. ;

Thepaut, J. -N. ;

Vitart, F. .

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2011, 137 (656) :553-597

[6]

Dobson M., 1985, IEEE T GEOSC SCI REM, V38, P1635

[7] Assimilation of passive and active microwave soil moisture retrievals [J].

Draper, C. S. ;

Reichle, R. H. ;

De Lannoy, G. J. M. ;

Liu, Q. .

GEOPHYSICAL RESEARCH LETTERS, 2012, 39

[8] Comparing ERA-40-Based L-Band Brightness Temperatures with Skylab Observations: A Calibration/Validation Study Using the Community Microwave Emission Model [J].

Drusch, Matthias ;

Holmes, Thomas ;

de Rosnay, Patricia ;

Balsamo, Gianpaolo .

JOURNAL OF HYDROMETEOROLOGY, 2009, 10 (01) :213-226

[9] Multi-model ensemble hydrologic prediction using Bayesian model averaging [J].

Duan, Qingyun ;

Ajami, Newsha K. ;

Gao, Xiaogang ;

Sorooshian, Soroosh .

ADVANCES IN WATER RESOURCES, 2007, 30 (05) :1371-1386

[10]

FUJII H, 2005, THESIS U TOKYO TOKYO

← 1 2 3 4 5 →