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Tomoki Ushiyama, Takahiro Sayama, Yuya Tatebe, Susumu Fujioka, and Kazuhiko Fukami

Pakistan and its vicinity. Monsoon surges triggered by an intraseasonal variation strike increased moisture transport simultaneously, which helped evolve those heavy rainfall events ( Hong et al. 2011 ; Lau and Kim 2012 ). Fig . 1. Weather chart for 500-hPa height during the Pakistan flood. Color contours show geopotential height anomalies (m) with negative anomalies identified by dashed contours, and stream lines show airflow, averaged from 27 to 30 July 2010. Flood forecasting is an effective tool

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Zhangkang Shu, Jianyun Zhang, Junliang Jin, Lin Wang, Guoqing Wang, Jie Wang, Zhouliang Sun, Ji Liu, Yanli Liu, Ruimin He, Cuishan Liu, and Zhenxin Bao

1. Introduction Numerical weather prediction (NWP) is a forecasting method used to solve atmospheric motion and weather phenomena in a particular period of future time for a defined set of initial values and boundary conditions. NWP is based on the hydrodynamic and thermodynamic equations of the weather evolution process. The effects of quantitative precipitation forecast (QPF) in NWP show clear temporal and spatial variations because of the differences in the initial fields, the generation of

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Niko Wanders, Stephan Thober, Rohini Kumar, Ming Pan, Justin Sheffield, Luis Samaniego, and Eric F. Wood

1. Introduction Extreme drought and flood events have a large societal impact and occur in all regions of the world and thus are important phenomena to accurately monitor and forecast ( Kundzewicz and Kaczmarek 2000 ; Wanders et al. 2014 ). Early-warning decision support systems have been designed to provide forecasts of these impactful hydrological extreme events. Operational continental-scale forecasting systems have been developed for Europe [European Flood Awareness System (EFAS); Thielen

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Alexandros A. Ntelekos, Konstantine P. Georgakakos, and Witold F. Krajewski

of property is destroyed ( Chang 1998 ). The benefits of uncertainty quantification in real-time forecasting were acknowledged by scientists almost a century ago ( Cooke 1906 ). In the area of hydrologic and flash flood forecasting, uncertainty modeling has been discussed by several authors (e.g., Georgakakos and Hudlow 1984 ; Georgakakos 1992 ; Krzysztofowicz 1999 ; Ferraris et al. 2002 ), but much more remains to be done in research and development. Recently, the need for probabilistic

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Ji-Qin Zhong, Bing Lu, Wei Wang, Cheng-Cheng Huang, and Yang Yang

1. Introduction The Rapid-Refresh Multiscale Analysis and Prediction System–Short Term (RMAPS-ST), the operational short-range numerical weather prediction (NWP) system of Beijing Meteorological Service (BMS), is a WRF-based system developed by Institute of Urban Meteorology (BMS/IUM). However, noticeable systematic bias of 2-m temperature (T2) and 2-m specific humidity (Q2) forecasts are found in the RMAPS-ST operational forecasts in the winter. The near-surface temperature and humidity

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Randal D. Koster, Siegfried D. Schubert, Anthony M. DeAngelis, Andrea M. Molod, and Sarith P. Mahanama

1. Introduction The ability to forecast anomalies in meteorological variables such as precipitation and air temperature can provide substantial benefits to society. Accurate forecasts can provide information with regard to, for example, upcoming water supply deficits or temperature extremes, potentially giving various socioeconomic sectors the time that they need to implement damage-mitigation strategies. Complex, coupled numerical models of Earth system processes have accordingly been

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Francesco Silvestro, Nicola Rebora, and Luca Ferraris

times, which are often much shorter than what is necessary for starting up the “machine of civil protection” and its procedures. To overcome this problem, it is a common practice to resort to the use of numerical precipitation predictions issued by meteorological models as input for hydrological response models (e.g., Lin et al. 2002 ; Bacchi et al. 2002 ; Bartholomes and Todini 2005 ). Various works demonstrate that it is not possible to tackle the hydrological forecasting problem in a

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Chih-Chiang Wei

economic losses and casualties ( Hsu and Wei 2007 ). Therefore, a useful scheme for quantitative precipitation forecast (QPF) during typhoon periods is highly desired ( Chang et al. 1993 ; Lee et al. 2006 ; Wei and Hsu 2008a ). In Taiwan, Wang et al. (1986) first developed a technique using the climatology average method (a simple statistical approach developed from the spatial distribution of typhoon center) to forecast typhoon rainfalls over land in Taiwan. This method was adopted to be one of

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Michael Scheuerer and Thomas M. Hamill

1. Introduction Ensemble precipitation forecasts are routinely generated at operational weather prediction centers worldwide ( Molteni et al. 1996 ; Toth and Kalnay 1993 ; Charron et al. 2010 ) and provide valuable information about the flow-dependent forecast uncertainty. Unfortunately, systematic biases often affect all ensemble members, and not all sources of uncertainty are represented by the ensemble; it therefore cannot be considered a sample that represents the predictive distribution

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Thomas E. Adams III and Randel Dymond

1. Introduction Single-valued, deterministic quantitative precipitation forecast (QPF) is a commonly used model forcing in hydrologic forecasting ( Georgakakos and Hudlow 1984 ; Sokol 2003 ; Adams and Pagano 2016 ; Li et al. 2017 ). All 13 U.S. National Oceanic and Atmospheric Administration (NOAA)/National Weather Service (NWS) River Forecast Centers (RFCs) utilize QPF operationally for hydrologic forecasting, ranging in duration from 1 to 10 days ( Adams 2016 ). Despite its widespread

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