An Intercomparison of ERS-Scat and AMSR-E Soil Moisture Observations with Model Simulations over France

被引:147
|
作者
Ruediger, Christoph
Calvet, Jean-Christophe [1 ]
Gruhier, Claire [4 ]
Holmes, Thomas R. H. [2 ]
de Jeu, Richard A. M. [2 ]
Wagner, Wolfgang [3 ]
机构
[1] Meteo France, CNRS, CNRM GMME MC2, GAME, F-31000 Toulouse, France
[2] Vrije Univ Amsterdam, Fac Earth & Life Sci, Amsterdam, Netherlands
[3] Vienna Univ Technol, Inst Photogrammetry & Remote Sensing, A-1040 Vienna, Austria
[4] UPS, IRD, CNRS, CNES,CESBIO,UMR5126, Toulouse, France
关键词
VEGETATION OPTICAL DEPTH; LAND-SURFACE PROCESSES; NEAR-SURFACE; RADIOFREQUENCY INTERFERENCE; RETRIEVAL; PARAMETERIZATION; SCATTEROMETER; VALIDATION; SPACE;
D O I
10.1175/2008JHM997.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This paper presents a study undertaken in preparation of the work leading up to the assimilation of Soil Moisture and Ocean Salinity (SMOS) observations into the land surface model (LSM) Interaction Soil Biosphere Atmosphere (ISBA) at Meteo-France. This study consists of an intercomparison experiment of different space-borne platforms providing surface soilmoisture information [Advanced Microwave Scanning Radiometer for Earth Observing (AMSR-E) and European Remote Sensing Satellite Scatterometer (ERS-Scat)] with the reanalysis soil moisture predictions over France from the model suite of Systeme d'analyse fournissant des renseignements atmospheriques a la neige (SAFRAN), ISBA, and coupled model (MODCOU; SIM) of Meteo-France for the years of 2003-05. Both modeled and remotely sensed data are initially validated against in situ observations obtained at the experimental soil moisture monitoring site Surface Monitoring of the Soil Reservoir Experiment (SMOSREX) in southwestern France. Two different AMSR-E soil moisture products are compared in the course of this study-the official AMSR-E product from the National Snow and Ice Data Center (NSIDC) and a new product developed at the Vrije Universiteit Amsterdam and NASA (VUA-NASA)-which were obtained using two different retrieval algorithms. This allows for an additional assessment of the different algorithms while using identical brightness temperature datasets. This study shows that a good correlation generally exists between AMSR-E (VUA-NASA), ERS-Scat, and SIM for low altitudes and low-to-moderate vegetation covers (1.5-3 kg m(-2) vegetation water content), with a reduction in the correlation in mountainous regions. It also shows that the AMSR-E (NSIDC) soil moisture product has significant differences when compared to the other datasets.
引用
收藏
页码:431 / 447
页数:17
相关论文
共 50 条
  • [21] An evaluation of soil moisture from AMSR-E over source area of the Yellow River, China
    Zhang, TangTang
    Gebreinichael, Mekonnen
    Koppa, Akash
    Meng, XianHong
    Du, Qun
    Wen, Jun
    SCIENCES IN COLD AND ARID REGIONS, 2019, 11 (06): : 461 - 469
  • [22] Downscaling of AMSR-E Soil Moisture over North China Using Random Forest Regression
    Zhang, Hongyan
    Wang, Shudong
    Liu, Kai
    Li, Xueke
    Li, Zhengqiang
    Zhang, Xiaoyuan
    Liu, Bingxuan
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2022, 11 (02)
  • [23] AMSR-E Soil Moisture Disaggregation Using MODIS and NLDAS Data
    Fang, Bin
    Lakshmi, Venkat
    REMOTE SENSING OF THE TERRESTRIAL WATER CYCLE, 2015, 206 : 277 - 304
  • [24] Validation of AMSR-E soil moisture algorithms with ground based networks
    Jackson, T. J.
    Cosh, M. H.
    Bindlish, R.
    Du, J.
    IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 1181 - 1184
  • [25] An Updated Geophysical Model for AMSR-E and SSMIS Brightness Temperature Simulations over Oceans
    Zabolotskikh, Elizaveta
    Mitnik, Leonid
    Chapron, Bertrand
    REMOTE SENSING, 2014, 6 (03) : 2317 - 2342
  • [26] Surface temperature effect on soil moisture retrieval from AMSR-E
    Guo, Ying
    Shi, Jiancheng
    Mao, Kebiao
    IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 1192 - 1195
  • [27] Retrieval of Bare Surface Soil Moisture from AMSR-E Data
    Han, Nianlong
    Chen, Shengbo
    Wang, Zijun
    2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 2, 2010, : 67 - 72
  • [28] Impact of Rainfall on the Retrieval of Soil Moisture using AMSR-E data
    Jin, Kyoung-Wook
    Njoku, Eni
    Chan, Steven
    2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 1740 - 1743
  • [29] A comparison of in situ precipitation with soil moisture retrieved from AMSR-E
    Mikai, H
    Arai, Y
    Mutoh, T
    Imaoka, K
    Shibata, A
    IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 2005, : 3460 - 3461
  • [30] Comparison between SPI and soil moisture retrieved from AMSR-E
    Xu, Jingwen
    Zhao, Junfang
    Wang, Yupeng
    Chen, Qionglian
    Zeng, Liwei
    ADVANCED MATERIALS AND PROCESSES III, PTS 1 AND 2, 2013, 395-396 : 511 - +