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Sara Q. Zhang, T. Matsui, S. Cheung, M. Zupanski, and C. Peters-Lidard

modeling system that represents cloud, precipitation, aerosol, and land process ( Peters-Lidard et al. 2015 ). It is based on the Advanced Research WRF ( Skamarock et al. 2008 ) with additional coupling to advanced Goddard physics packages, satellite simulators, and high-resolution satellite/reanalysis data to initialize boundary conditions. In this work the NU-WRF model simulations are carried out at storm scale with lateral boundary forcing from the Modern-Era Retrospective Analysis for Research and

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W.-K. Tao, T. Iguchi, and S. Lang

, . 10.1175/JAMC-D-13-0334.1 Iguchi , T. , and Coauthors , 2017 : Sensitivity of CONUS summer rainfall to the selection of cumulus parameterization schemes in NU-WRF seasonal simulations . J. Hydrometeor. , 18 , 1689 – 1706 , . 10.1175/JHM-D-16-0120.1 Johnson , D. E. , W.-K. Tao , J. Simpson , and C.-H. Sui , 2002 : A study of the response of deep tropical clouds to large-scale thermodynamic forcing

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Stephen E. Lang and Wei-Kuo Tao

1987 ; Kemball-Cook and Weare 2001 ). GCMs have traditionally struggled to properly simulate the MJO, and inaccuracies in their simulated heating profiles are one possible factor ( C. Li et al. 2009 ). At smaller scales, LH is a fundamental energy source for the maintenance and intensification of tropical cyclones ( Schubert and Hack 1982 ; Nolan et al. 2007 ). Because it is an integral part of the phase changes of water, LH is closely tied to cloud systems and precipitation. And despite its

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Veljko Petković, Christian D. Kummerow, David L. Randel, Jeffrey R. Pierce, and John K. Kodros

Scientific, 238 pp. 10.1142/3171 Romanov , P. , G. Gutman , and I. Csiszar , 2000 : Automated monitoring of snow cover over North America with multispectral satellite data . J. Appl. Meteor. , 39 , 1866 – 1880 , doi: 10.1175/1520-0450(2000)039<1866:AMOSCO>2.0.CO;2 . 10.1175/1520-0450(2000)039<1866:AMOSCO>2.0.CO;2 Rosenfeld , D. , R. Wood , L. J. Donner , and S. C. Sherwood , 2013 : Aerosol cloud-mediated radiative forcing: Highly uncertain and opposite effects from shallow and deep clouds

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Jackson Tan, Walter A. Petersen, and Ali Tokay

1. Introduction Satellite remote sensing of precipitation is critically important because of the absence of ground measurements in many parts of the world, including over oceans, mountainous regions, and sparsely populated areas. Early efforts on space-based precipitation retrievals focused on estimating rainfall from infrared measurements of cloud tops from geosynchronous satellites, but accuracy was limited because of the indirect connection between surface rain rates and cloud

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Sarah D. Bang and Daniel J. Cecil

b ) lower than 200 K. Over a cloud, a “depression” of microwave T b relative to the environment around it indicates that upwelling microwave emission is scattered away by ice particles in the column before reaching the radiometer ( Spencer et al. 1987 ). Depressions in T b above precipitating clouds can be used to estimate the volume of ice in the observed column, and the microwave frequency in which the depression is expressed can lend insight into the sizes of the ice particles therein

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Jiaying Zhang, Liao-Fan Lin, and Rafael L. Bras

). Nonetheless, we note that the range of the correlations during the winter is much wider than that during the summer, indicating that the quality of the IMERG and WRF products varies significantly in the winter. Since precipitation type during the summer is mostly convective, satellites have the ability to capture the magnitude and the spatial patterns while models have a harder time because of uncertainties introduced by cloud parameterizations ( Di et al. 2015 ; Gao et al. 2017 ). During the winter

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Md. Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, and Emmanouil N. Anagnostou

Global Precipitation Climatology Center (GPCC) dataset. The reanalysis precipitation dataset (EI_GPCC) that we used in this study was further downscaled from 0.5° to 0.25° based on the Climate Hazards Group’s Precipitation Climatology (CHPclim). The WATCH (Water and Global Change FP7 project) Forcing Dataset ERA-Interim (hereafter WFDEI; Weedon et al. 2014 ) is based on ERA-Interim with a geographical resolution of 0.5° and bias corrections using gridded rain gauge datasets. We chose specific

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Dalia B. Kirschbaum, George J. Huffman, Robert F. Adler, Scott Braun, Kevin Garrett, Erin Jones, Amy McNally, Gail Skofronick-Jackson, Erich Stocker, Huan Wu, and Benjamin F. Zaitchik

NASA’s precipitation measurement missions provide critical precipitation information to end users that improves understanding of Earth’s water cycle and enhances decision-making at local to global scales. Precipitation is the fundamental source of freshwater in the water cycle. If one could collect all of the water in the atmosphere, including water vapor, clouds, and precipitation, it would account for 4% of the total freshwater and 0.01% of the total water on Earth ( USGS 2016 ). Despite its

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Liao-Fan Lin, Ardeshir M. Ebtehaj, Alejandro N. Flores, Satish Bastola, and Rafael L. Bras

. 2012 , 2014 ; S. V. Kumar et al. 2014 ; Zhao et al. 2016 ). The family of soil moisture data assimilation methods uses prescribed atmospheric forcing (e.g., precipitation and downward radiation) and updates only selected land surface states, which often include soil moisture and temperature profiles. More recently, Rasmy et al. (2011 , 2012) developed a WRF-based system that is capable of updating the state of soil moisture, cloud liquid water, water vapor, rain, and snow through the

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