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Masamichi Ohba, Shinji Kadokura, Yoshikatsu Yoshida, Daisuke Nohara, and Yasushi Toyoda

example, weather pattern (WP) classification at the synoptic scale has been useful for characterizing statistical properties of climatic records, such as precipitation series, at the local scale (e.g., Brigode et al. 2013 ). In this framework, recent studies (e.g., Garavaglia et al. 2010 , 2011 ) have used WP subsampling and probability distribution with a hydrological model to predict floods from extreme rainfall events. Moreover, potential interannual to interdecadal changes in extreme events are

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Jonathan J. Gourley, Scott E. Giangrande, Yang Hong, Zachary L. Flamig, Terry Schuur, and Jasper A. Vrugt

1. Introduction Weather radars sample the atmosphere at high spatial resolution over contiguous regions, whereas operational rain gauge networks collect rainfall nearly continuously at points. Despite the opportunity to capture the spatial variability of rainfall, a number of studies have identified and quantified errors in radar rainfall estimation. Relevant literature reviews of radar-based rainfall errors can be found in Wilson and Brandes (1979) , Austin (1987) , and Joss and Waldvogel

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Sandra E. Yuter, David A. Stark, Justin A. Crouch, M. Jordan Payne, and Brian A. Colle

1. Introduction Much progress has been made in the last decade in the study of orographic precipitation using high-resolution idealized and forecast models, case studies from field projects, and the analysis of radar and precipitation-gauge characteristics from multiseason datasets. Mountains more commonly modify and amplify precipitation associated with preexisting weather disturbances rather than solely initiating all the precipitation ( Smith 2006 ). For unblocked flow, the strength and

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F. M. Ralph, T. Coleman, P. J. Neiman, R. J. Zamora, and M. D. Dettinger

below is motivated by the need to better understand and predict storm total rainfall and streamflow over several hours to several days in extreme events. To do so, the analysis bridges the fields of meteorology and hydrology. Extreme precipitation forecasts are often low by a factor of 2 in the region partly because weather prediction models do not adequately represent key AR characteristics ( Ralph et al. 2010 ), including landfall duration, and the cloud and precipitation microphysical processes

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James A. Smith, Gabriele Villarini, and Mary Lynn Baeck

snow determines the local maximum in flood peak occurrence in the northeastern United States ( Fig. 1b ), where March–April peaks account for up to 60% of annual peaks. Organized thunderstorm systems embedded in winter–spring extratropical systems, often associated with severe weather, are important flood agents in the southeastern United States ( Fig. 1b ). March–April peaks account for more than 50% of annual flood peaks in south Georgia, north Florida, and southeastern Alabama ( Fig. 1b

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Ali Behrangi, Bisher Imam, Kuolin Hsu, Soroosh Sorooshian, Timothy J. Bellerby, and George J. Huffman

1. Introduction High-quality precipitation data at fine time and space resolution have many hydrometeorological applications including flood forecasting, drought monitoring, disaster management, and initialization of numerical weather prediction models, among others. The current constellation of earth observing satellites allows global retrieval of precipitation data that complement ground precipitation observations from relatively sparse radar/gauge networks. While high

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