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Chris Kidd, Erin Dawkins, and George Huffman

paper assesses how well the operational European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model simulates the mean annual and seasonal diurnal rainfall cycles relative to the satellite-derived Tropical Rainfall Measuring Mission (TRMM) Merged Precipitation Analysis (TMPA) and Precipitation Radar (PR) products across the global tropics (40°N–40°S 180°W–180°E) over a 7-yr time period (2004–11). This is the region where models typically show the least accuracy at simulating

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Louise Arnal, Andrew W. Wood, Elisabeth Stephens, Hannah L. Cloke, and Florian Pappenberger

) in the winter and fall due to higher precipitation forecasting skill in strong ENSO phases ( Wood et al. 2005 ). Increasing the seasonal streamflow forecast skill remains a challenge: one that is being tackled by improving IHCs and SCFs using a variety of techniques. Techniques include model developments and data assimilation and can vary in computational expense. However, over the past several decades, it has been shown that operational streamflow forecast quality has not significantly improved

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M. Tugrul Yilmaz and Wade T. Crow

matching techniques are perhaps the most common. A handful of studies have applied rescaling based on least squares regression techniques ( Crow et al. 2005 ; Crow and Zhan 2007 ) but failed to offer any clear rationale for this choice. Additionally, signal variance-based rescaling, typically applied as a preprocessing step in triple collocation analysis ( Stoffelen 1998 ), also provides a means to rescale datasets using three independent estimates of the same variable. However, this approach has not

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T. J. Bellerby

G. , and Zhu Y. , 2003 : Probability and ensemble forecasts. Forecast Verification, I. T. Jolliffe and D. B. Stephenson, Eds., Wiley, 137–164. Turk, F. J. , and Miller S. D. , 2005 : Toward improving estimates of remotely-sensed precipitation with MODIS/AMSR-E blended data techniques . IEEE Trans. Geosci. Remote Sens. , 43 , 1059 – 1069 . Ushio, T. , and Coauthors , 2009 : A Kalman filter approach to the Global Satellite Mapping of Precipitation (GSMaP) from combined passive

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Klaus Vormoor and Thomas Skaugen

Norway, observed meteorological data are usually only available as daily values, whereas meteorological forecast data are available on almost any desired temporal resolution. Since most hydrological models need to be calibrated with historical data, we need to close the gap in temporal resolution between historical and forecasted meteorological data and introduce appropriate techniques to refine historical meteorological data into a subdaily resolution. The Norwegian Water Resources and Energy

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Ryan R. Neely III, Louise Parry, David Dufton, Lindsay Bennett, and Chris Collier

radar networks, the ability to create maps of precipitation on national scales at 5-min frequencies with subkilometer resolutions has become routine. These reveal important microphysical and dynamical information and are an invaluable tool for flood forecasters ( Herzegh and Jameson 1992 ; Zrnić and Ryzhkov 1999 ; Ogden et al. 2000 ; Lascaux et al. 2007 ; Cifelli and Chandrasekar. 2010 ; Gourley et al. 2010 ; Berne and Krajewski 2013 ; Antonini et al. 2017 ). The effectiveness of dual

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Blandine Bianchi, Peter Jan van Leeuwen, Robin J. Hogan, and Alexis Berne

1. Introduction The problem of accurate measurement of rainfall intensity has been long investigated because it has important implications in meteorology, agriculture, environmental policies, monitoring of sewage systems in urban areas, and weather forecasting. Over past decades, various techniques have been developed for monitoring rainfall, but its strong spatial and temporal variability still represents a significant source of uncertainty. In this study, a variational approach is proposed to

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Joseph Bellier, Michael Scheuerer, and Thomas M. Hamill

Bunkers , M. J. , B. A. Klimowski , J. W. Zeitler , R. L. Thompson , and M. L. Weisman , 2000 : Predicting supercell motion using a new hodograph technique . Wea. Forecasting , 15 , 61 – 79 ,<0061:PSMUAN>2.0.CO;2 . 10.1175/1520-0434(2000)015<0061:PSMUAN>2.0.CO;2 Buschow , S. , J. Pidstrigach , and P. Friederichs , 2019 : Assessment of wavelet-based spatial verification by means of a stochastic precipitation model (wv_verif v0

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Marouane Temimi, Ricardo Fonseca, Narendra Nelli, Michael Weston, Mohan Thota, Vineeth Valappil, Oliver Branch, Hans-Dieter Wizemann, Niranjan Kumar Kondapalli, Youssef Wehbe, Taha Al Hosary, Abdeltawab Shalaby, Noor Al Shamsi, and Hajer Al Naqbi

’s physical properties, and hence their representation in numerical models is very important for an accurate simulation of the surface and near-surface fields. An accurate modeling of land–atmosphere interactions strongly depends on how accurate the surface properties, in particular the predominant soil texture and LULC, are represented in the model. Göndöcs et al. (2015) investigated the sensitivity of the Weather Research and Forecasting (WRF; Skamarock et al. 2008 ) Model’s response to a more

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Viviana Maggioni, Humberto J. Vergara, Emmanouil N. Anagnostou, Jonathan J. Gourley, Yang Hong, and Dimitrios Stampoulis

ensemble prediction system for flood forecasting. Atger (2001) showed that the ensemble prediction system performs better than a single forecast based on the same model. He also demonstrated that the impact of reducing the number of ensemble members is rather small (i.e., differences between 51 members and 21 members are not significant). Moreover, Verbunt et al. (2007) corroborated that probabilistic flood forecasts have advantages compared to the deterministic forecast for a particular flood

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