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Qing Liu, Rolf H. Reichle, Rajat Bindlish, Michael H. Cosh, Wade T. Crow, Richard de Jeu, Gabrielle J. M. De Lannoy, George J. Huffman, and Thomas J. Jackson

scarce, both spatially and temporally. Regional to global soil moisture data rely largely on simulation with land surface models (LSM) forced by meteorological data ( Srinivasan et al. 2000 ; Dirmeyer et al. 2002 ) or on satellite observations of active or passive microwaves in the L- to X-band range (1.4–11 GHz) such as those currently available from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E; Jackson 1993 ; Njoku and Entekhabi 1996 ; Wagner et al. 1999 ; Owe

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Paul A. Dirmeyer

Radiometer (SMMR) orbital instruments have also been used to infer surface soil wetness (e.g., Paloscia et al. 2001 ). Data from active microwave sensors from European Remote Sensing (ERS) scatterometers have been used to create an index of soil wetness ( Wagner et al. 1999 ) that correlates well with in situ observations (e.g., Dirmeyer et al. 2004 ). Aircraft-borne passive-microwave sensors (e.g., Jackson et al. 2002 ), ground-based sensors ( de Rosnay et al. 2006 ), and Tropical Rainfall Measuring

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Sante Laviola, Agata Moscatello, Mario Marcello Miglietta, Elsa Cattani, and Vincenzo Levizzani

Powers J. G. , 2005 : A description of the advanced research WRF version 2 . NCAR Tech. Note NCAR/TN-468+STR, 88 pp . Staelin, D. H. , 1976 : Remote sensing of the atmospheric water vapor and liquid water with Nimbus-5 microwave spectrometer . J. Appl. Meteor. , 15 , 1204 – 1215 . Staelin, D. H. , and Chen F. W. , 2000 : Precipitation observations near 54 and 183 GHz using the NOAA-15 satellite . IEEE Trans. Geosci. Remote Sens. , 38 , 2322 – 2332 . Tartaglione, N. , Lanciani

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