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Marco L. Carrera, Bernard Bilodeau, Stéphane Bélair, Maria Abrahamowicz, Albert Russell, and Xihong Wang

were assimilated into the NASA GEOS-5 model over agricultural regions of North America. Blankenship et al. (2016) found similarly improved surface soil moisture correlations over the southeastern United States with the assimilation of SMOS soil moisture retrievals. More recently, Reichle et al. (2017) presented the positive impacts of globally assimilating SMAP brightness temperatures with the SMAP Level-4 soil moisture product. The joint assimilation of screen-level observations and microwave

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Chih-Chiang Wei and Jinsheng Roan

. Water Resour. Manage. , 22 , 1625 – 1647 . Wilheit, T. T. , and Chang A. T. C. , 1980 : An algorithm for retrieval of ocean surface and atmospheric parameters from the observations of the scanning multichannel microwave radiometer . Radio Sci. , 15 , 525 – 544 . Wilheit, T. T. , Chang A. T. C. , Rao M. S. V. , Rodgers E. B. , and Theon J. S. , 1977 : A satellite technique for quantitatively mapping rainfall rates over the oceans . J. Appl. Meteor. , 16 , 551 – 560 . Wilheit

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Veljko Petković and Christian D. Kummerow

observations. Today, the WMO as well as national agencies utilize all available resources in an effort to provide the best possible estimates of rain and snow accumulations. (See Table 1 for a full list of acronyms used throughout the paper.) Satellite products play an integral role in this scheme, particularly in areas that are not well instrumented. Relying largely on passive microwave measurements, significant challenges exist because of poor temporal sampling and the inability of land retrievals to

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Mohammad Reza Ehsani, Ali Behrangi, Abishek Adhikari, Yang Song, George J. Huffman, Robert F. Adler, David T. Bolvin, and Eric J. Nelkin

observational records [e.g., the Special Sensor Microwave Imager (SSM/I) goes back to 1987] and wider swath and geographical coverage (e.g., they often provide pole-to-pole observations) than satellite radars. However, with respect to high-latitude precipitation estimation, PMW-based retrievals face several challenges such as 1) poor sensitivity of sensors to light rain and snowfall that may lead to large missing or underestimation of precipitation ( Behrangi et al. 2012 ), 2) unknown surface emissivity

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Hidde Leijnse, Remko Uijlenhoet, and Alexis Berne

1. Introduction Microwave links have been shown to be highly suitable for estimating path-averaged rainfall intensity ( Ruf et al. 1996 ; Rincon and Lang 2002 ; Holt et al. 2003 ; Rahimi et al. 2003 , 2004 ; Minda and Nakamura 2005 ; Krämer et al. 2005 ; Upton et al. 2005 ; Grum et al. 2005 ; Messer et al. 2006 ; Leijnse et al. 2007a , b ). This is due to the near linearity of the relationship between the variable measured by the link (the path-integrated attenuation) and the rainfall

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Adam Eshel, Hagit Messer, Harald Kunstmann, Pinhas Alpert, and Christian Chwala

-197-2006 Alpert , P. , and Y. Rubin , 2018 : First daily mapping of surface moisture from cellular network data and comparison with both observations/ECMWF product . Geophys. Res. Lett. , 45 , 8619 – 8628 , . 10.1029/2018GL078661 Andersson , J. , P. Berg , J. Hansryd , A. Jacobsson , J. Olsson , and J. Wallin , 2017 : Microwave links improve operational rainfall monitoring in Gothenburg, Sweden. 15th Int. Conf. on Environmental Science and

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Robert E. Davis, Thomas H. Painter, Rick Forster, Don Cline, Richard Armstrong, Terry Haran, Kyle McDonald, and Kelly Elder

snow volume ( Chang and Rango 2000 ). Passive microwave observations have demonstrated sensitivity to snow water equivalent ( Chang et al. 1987 ; Goodison 1989 ; Nagler and Rott 1992 ; Grody and Basist 1996 ; Tait 1998 ; Pulliainen and Hallikainen 2001 ). Snow cover products derived from microwave measurements have a legacy dating back 25 yr or more ( Frei and Robinson 1999 ). However, they currently have coarse spatial resolutions that limit their use in hydrologic modeling to the larger

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Linda Bogerd, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet


Applications like drought monitoring and forecasting can profit from the global and near real-time availability of satellite-based precipitation estimates once their related uncertainties and challenges are identified and treated. To this end, this study evaluates the IMERG V06B Late Run precipitation product from the Global Precipitation Measurement mission (GPM), a multi-satellite product that combines space-based radar, passive microwave (PMW), and infrared (IR) data into gridded precipitation estimates. The evaluation is performed on the spatiotemporal resolution of IMERG (0.1° × 0.1°, 30 min) over the Netherlands over a five-year period. A gauge-adjusted radar precipitation product from the Royal Netherlands Meteorological Institute (KNMI) is used as reference, against which IMERG shows a large positive bias. To find the origin of this systematic overestimation, the data is divided into seasons, rainfall intensity ranges, echo top height (ETH) ranges, and categories based on the relative contributions of IR, morphing, and PMW data to the IMERG estimates. Furthermore, the specific radiometer is identified for each PMW-based estimate. IMERG’s detection performance improves with higher ETH and rainfall intensity, but the associated error and relative bias increase as well. Severe overestimation occurs during low-intensity rainfall events and is especially linked to PMW observations. All individual PMW instruments show the same pattern: overestimation of low-intensity events and underestimation of high-intensity events. IMERG misses a large fraction of shallow rainfall events, which is amplified when IR data is included. Space-based retrieval of shallow and low-intensity precipitation events should improve before IMERG can be implemented over the middle and high-latitudes.

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C. Derksen, R. Brown, and A. Walker

) . Evaluation of the MSC algorithm suite for various regions and time series is described in Derksen et al. (2002b ; 2003a , b) and Walker and Silis (2002) . The algorithms are typically capable of producing SWE retrievals within ±15 mm of surface observations, although consistent underestimation of SWE is a problem in heavily forested areas because of the complex impact of dense vegetation on microwave emission and scatter ( Walker and Silis 2002 ; Derksen et al. 2002b , 2003a ). All the

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Long Zhao, Zong-Liang Yang, and Timothy J. Hoar

simulations and independent satellite observations ( Vereecken et al. 2008 ). Considering the uncertainties in satellite soil moisture products ( Jackson et al. 2010 ; Su et al. 2011 ; Chen et al. 2013 ; Al-Yaari et al. 2014 ), some researchers prefer to directly assimilate microwave brightness temperatures (TB) through radiative transfer models (RTMs; Margulis et al. 2002 ; Crow and Wood 2003 ; Yang et al. 2007 ; Loew et al. 2009 ; Shi et al. 2010 ). Model parameters are sometimes updated

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