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Filipe Aires
,
Fabrice Papa
,
Catherine Prigent
,
Jean-François Crétaux
, and
Muriel Berge-Nguyen

-resolution surface water maps as well as water height for rivers, lakes, inundated areas, and wetlands. Before the launch of this mission and in the framework of its preparation, long-term datasets of high-spatial-resolution surface water extent are in demand. Would it be possible to develop downscaling methodology to derive high-resolution surface water extent from the existing GIEMS low-resolution dataset? Since GIEMS has a global coverage, the ideal situation would be to develop a downscaling technique

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Chiara Corbari
and
Marco Mancini

role in the computation of the principal mass and energy fluxes. In the literature these parameters are usually defined using soil texture maps ( Rawls and Brakensiek 1985 ), but problems of representativeness arise owing to pixel heterogeneity. Satellite images of land surface temperature can help in the calibration of these parameters in each pixel of the analyzed domain, overcoming the traditional calibration based on a single multiplicative value retrieved from the comparison between observed

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J.-P. Vergnes
,
B. Decharme
,
R. Alkama
,
E. Martin
,
F. Habets
, and
H. Douville

) were used as the second criterion in the proposed methodology. Fig . 4. Data sources used to delimit the aquifer basin boundaries: (a) groundwater resources of the world according to the WHYMAP (BGR and UNESCO; http://www.whymap.org ), (b) the BGR geological units by age (BGR; http://www.bgr.de/karten/igme5000/igme5000.htm ), and (c) the simplified lithology of France (BRGM; http://infoterre.brgm.fr ). The comparison of the BDRHF map ( Fig. 3 ) with the two selected classes of WHYMAP, the IGME

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Auguste Gires
,
Ioulia Tchiguirinskaia
,
Daniel Schertzer
, and
Alexis Berne

rainfall fields down to drop scale using data collected by a 2D video disdrometer (2DVD) [see Kruger and Krajewski (2002) for a precise description of the device’s functioning], deployed in the Ardèche region (southeastern France) in the framework of the Hydrological Cycle in Mediterranean Experiment (HyMeX; Ducrocq et al. 2014 ), in an innovative way. Indeed, this device has been extensively used as a reference in comparison with other rainfall-measuring ones ( Krajewski et al. 2006 ; Tokay et al

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Renu Joseph
,
Thomas M. Smith
,
Mathew R. P. Sapiano
, and
Ralph R. Ferraro

are also compared with CMORPH, TMPA, a merged microwave product used in the creation of CMORPH called microwave combination (MWCOMB), and the GPCP 1DD daily data. Among these merged precipitation products used for comparison, TMPA is the only product that applies gauge corrections. Table 4 shows bias, correlation, and RMSD of the CHOMPS, CMORPH, and TMPA evaluated against the stage IV data ( Lin and Mitchell 2005 ). Figure 5 shows maps of the correlations and biases. This analysis is similar to

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Kristen J. Guirguis
and
Roni Avissar

′ and y ′, and r ′ x′y′ represents the spatial anomaly correlation coefficient. Equation (15) can be manipulated algebraically by dividing by S 2 y ′ and completing the square to give the normalized MSE (NMSE), represented as where A 2 is a nondimensional measure of the unconditional bias, B 2 is a measure of the conditional bias, C 2 is the phase error, and NMSE is the normalized MSE, where NMSE = MSE/ S 2 y ′ . For analyses of fields (maps), the terms in (16) can be physically

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Nicola Montaldo
and
John D. Albertson

z = d 1 . The difference θ g − θ g eq must represent the effect of the vertical gradient of hydraulic potential (between surface zone and lower root-zone region), with C 2 serving to map moisture content to matric potential units and to scale by the conductivity. The most significant obstacle for the stratified soil case is the θ g eq term. Recall from (3)–(5) that θ g eq is a function of θ 2 , with adjustments to account for the relative importance of capillary and gravity forces

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Huilin Gao
,
Eric F. Wood
,
Matthias Drusch
, and
Matthew F. McCabe

the assimilation of soil moisture by matching the two cumulative distribution functions (CDFs) over a comparison period. One assumption of CDF matching is that the ranked values of the two datasets are uniquely related. In practice this usually does not hold due to estimation uncertainties in both the retrieved and observed/modeled soil moisture, resulting in a statistical rather than a perfect dependency. An alternative approach is to construct statistical observation operators by fitting a

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Jie Li
,
Tao Tao
,
Zhonghe Pang
,
Ming Tan
,
Yanlong Kong
,
Wuhui Duan
, and
Yuwei Zhang

Beijing municipality, some 40 km south-southwest of the city center ( Fig. 1 ). Beijing has a typical continental monsoon climate, with four distinct seasons; cool and wet winters are dominated by the polar air mass, while hot and rainy summers are influenced by the East Asian summer monsoon. The annual precipitation is 574 mm, of which some 70% occurs during the summer season of June–September. Average annual temperature is around 12°C ( Fig. 2 ). Fig . 1. Sketched map showing the sampling location

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B. Decharme
,
H. Douville
,
A. Boone
,
F. Habets
, and
J. Noilhan

. This work, like that of Sivapalan et al. (1987) , accounts for saturation excess runoff generation (Dunne process) via TOPMODEL, but also includes a separate infiltration excess mechanism (Horton runoff) using a Philip approximation to the infiltration capacity. Based on these studies, Stieglitz et al. (1997) performed a comparison between a single-column model where k sat was taken to be vertically homogeneous, and another single-column model where k sat declined with depth and was much

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