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Kingtse C. Mo and Dennis P. Lettenmaier

of hydrological drought. As a result of the sparseness of observations of SM and the complexities of the relationships between (spatially distributed) runoff and observed streamflow, the use of model-derived SM and runoff from efforts like the North American Land Data Assimilation System (NLDAS) ( Mitchell et al. 2004 ; Xia et al. 2012 ) and extensions thereof by Maurer et al. (2002) and Livneh et al. (2013) have become popular. The Environmental Modeling Center (EMC) of the National Centers

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Paul A. Dirmeyer, Jiangfeng Wei, Michael G. Bosilovich, and David M. Mocko

.g., Gimeno et al. 2012 ; Goessling and Reick 2011 ). Van der Ent (2010) developed a backtracking model based on the vertically integrated moisture transport and the constraints of atmospheric water balance, but still in the Eulerian framework. Keys et al. (2012) developed an interesting variant on that approach to estimate the “precipitation sheds” of regions to assess their potential vulnerability to changing evapotranspiration with land use changes. Another approach is to include water vapor

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Bart Nijssen, Shraddhanand Shukla, Chiyu Lin, Huilin Gao, Tian Zhou, Ishottama, Justin Sheffield, Eric F. Wood, and Dennis P. Lettenmaier

a suite of land surface models. The U.S. Drought Monitor ( Svoboda et al. 2002 ) has provided weekly drought updates since 1999 as part of a partnership between the National Drought Mitigation Center at the University of Nebraska–Lincoln, the U.S. Department of Agriculture, and the National Oceanic and Atmospheric Administration. Kogan and Sullivan (1993) made an early attempt to develop a global drought monitor using satellite information, primarily using satellite-based vegetation indices

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Youlong Xia, Michael B. Ek, David Mocko, Christa D. Peters-Lidard, Justin Sheffield, Jiarui Dong, and Eric F. Wood

monthly anomalies and percentiles of hydrologic fields (soil moisture, snow water equivalent, total runoff, streamflow, evaporation, and precipitation) output from the four land surface models [Noah, Mosaic, Sacramento (SAC), and Variable Infiltration Capacity (VIC)] on a common ⅛° grid using common hourly meteorological forcing (see the drought tab on the NLDAS website, ). The climatology of each hydrologic field was calculated as the average of 28 yr (1980–2007) of

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Jiarui Dong, Mike Ek, Dorothy Hall, Christa Peters-Lidard, Brian Cosgrove, Jeff Miller, George Riggs, and Youlong Xia

agriculture. Knowledge of various snowpack properties is crucial for short-term weather forecasts, climate change prediction, and hydrologic forecasting for producing reliable daily to seasonal forecasts. One potential source of this information is the multi-institution North American Land Data Assimilation System (NLDAS) project ( Mitchell et al. 2004 ). Real-time NLDAS products are used for drought monitoring to support the National Integrated Drought Information System (NIDIS) and as initial conditions

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Sujay V. Kumar, Christa D. Peters-Lidard, David Mocko, Rolf Reichle, Yuqiong Liu, Kristi R. Arsenault, Youlong Xia, Michael Ek, George Riggs, Ben Livneh, and Michael Cosh

runoff estimation is the use of land surface models (LSMs) forced with observed meteorology, which generate spatially and temporally continuous estimates of land surface conditions ( Mitchell et al. 2004 ; Rodell et al. 2004 ; Kumar et al. 2006 ). The gridded runoff can be subsequently routed to generate estimates of streamflow, and several studies provide descriptions and evaluations of these approaches ( Schlosser et al. 1997 ; Nijssen et al. 1997 ; Boone et al. 2004 ; Lohmann et al. 2004

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Zengchao Hao and Amir AghaKouchak

used standardized drought indices (i.e., SPI and SSI), are derived using the National Aeronautics and Space Administration’s (NASA) land-only version of Modern-Era Retrospective Analysis for Research and Applications (MERRA-Land) data and validated with the U.S. Drought Monitor (USDM) data. 2. Method In a recent study, Hao and AghaKouchak (2013) proposed the MSDI for characterizing overall drought conditions, taking into account precipitation deficit and soil moisture deficit. This approach is an

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Hongshuo Wang, Jeffrey C. Rogers, and Darla K. Munroe

drought indices when facing the limited retrieval of soil moisture from either remote sensing data (only soil moisture at the surface layer <5 cm) or large uncertainties in soil moisture output from land surface models ( Guo et al. 2004 ). The study may help meteorologists and ecologists to understand and monitor soil moisture and drought in agricultural areas of China. The results suggest a preference to use multiscalar drought indices rather than drought indices from a two-layer bucket model, which

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Hailan Wang, Siegfried Schubert, Randal Koster, Yoo-Geun Ham, and Max Suarez

as well as from some limited simulations with the atmosphere–ocean coupled version of the GEOS-5 model. The discussion and conclusions are provided in section 4 . 2. Model experiments a. Reanalysis The reanalysis data consist of 3-hourly and monthly MERRA ( Rienecker et al. 2011 ) and MERRA-Land data ( Reichle et al. 2011 ; Reichle 2012 ) for the period January 1979–August 2012. The MERRA data are used primarily to describe the atmospheric circulation. Overall, as discussed in Rienecker et al

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Richard Seager, Lisa Goddard, Jennifer Nakamura, Naomi Henderson, and Dong Eun Lee

imposed allowing land surfaces to warm and the atmospheric circulation to adjust to the changes in radiative properties. The other model is the European Centre-Hamburg model, version 4.5 (ECHAM4.5; Roeckner et al. 1996 ), and we use a 24-member ensemble from 1950 on available in the International Research Institute for Climate and Society Data Library ( ). We also use the NCEP–NCAR reanalysis and the Interim European Centre

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