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Tirthankar Roy, Xiaogang He, Peirong Lin, Hylke E. Beck, Christopher Castro, and Eric F. Wood

limitations persist. First, most of the above studies are regional assessments, which makes it difficult to generalize their results to other regions. Second, none of the studies considered all the models currently available within the NMME system (there are 16 in total that has both precipitation and temperature forecasts), raising concerns about the performance of the excluded models. Third, not all of them considered both precipitation and temperature in the skill assessment. Fourth, none of them

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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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Xiang Gao, Alexander Avramov, Eri Saikawa, and C. Adam Schlosser

1. Introduction The state and amount of water in the soil is a critical determinant in many complex Earth system processes. Soil moisture serves as the reservoir for the land surface hydrologic cycle and a boundary condition for the atmosphere. It regulates the partitioning of land surface heat fluxes, affects the status of overlying vegetation, modulates the thermal properties of the soil, and controls the exchange of trace gases at Earth’s surface. Knowledge of the temporal and spatial

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Dazhi Xi, Ning Lin, and James Smith

profiles (RCLIPER) as a function of TC intensity. The model was further improved by Lonfat et al. (2007) to account for rainfall asymmetry caused by topographic and shear effects. In addition to the statistical approach, Langousis and Veneziano (2009a) developed a TC rainfall model based on basic thermodynamics and TC boundary layer theory. The model accounts for the azimuthal asymmetries in surface friction related to storm motion, but it does not account for the interaction of the storm with its

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Andrea Manrique-Suñén, Annika Nordbo, Gianpaolo Balsamo, Anton Beljaars, and Ivan Mammarella

-weighted average. Koster and Suarez (1992) and Essery et al. (2003) compared both strategies and showed similar results, with the tiling method giving slightly lower turbulent fluxes, especially for contrasting surfaces. However, the former focused on heterogeneity due to different vegetation types, and in the latter the comparison is made against climatology. In the current study, we evaluate the tiling method in the more extreme case of a forest and a lake and concentrate on a local situation with

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Rhonalyn V. Macalalad, Roy A. Badilla, Olivia C. Cabrera, and Gerry Bagtasa

the east, Caraballo Mountains to the north, and parts of the Zambales Mountains where Mt. Pinatubo is located to the west. Of these boundaries, the Zambales Mountains to the west are characterized by ultramafic rocks with some volcanic components ( Schopka et al. 2011 ). The Sierra Madre range to the east comprise more of dissected and eroded terrain ( JICA 2011 ). The central part of the study area is called the Central Luzon Plain due to its relatively flat terrain. It is an alluvial plain with

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Rong-Yu Gu, Min-Hui Lo, Chi-Ya Liao, Yi-Shin Jang, Jehn-Yih Juang, Cho-Ying Huang, Shih-Chieh Chang, Cheng-I Hsieh, Yi-Ying Chen, Housen Chu, and Kuang-Yu Chang

forcing ( Foster 2001 ; Oliveira et al. 2014 ; Williams et al. 2015 ; Still et al. 1999 ; Nair et al. 2003 ). Understanding the relationship between ET and fog may improve water cycle projections under changing fog frequency in the MCFs. Generally, soil moisture–precipitation feedback indicates interaction between land and atmosphere through surface fluxes and boundary layer development; the feedback often occurs on daily to monthly time scales ( Findell and Eltahir 1997 ; The GLACE Team 2004

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Zhongkun Hong, Zhongying Han, Xueying Li, Di Long, Guoqiang Tang, and Jianhua Wang

et al. 2013 ; Pang et al. 2017 ; Tang et al. 2018b ; Tong et al. 2014b ; Yang et al. 2004 ). There are currently four primary ways to estimate precipitation: 1) ground-based gauge observations, 2) ground-based radar remote sensing, 3) satellite remote sensing, and 4) atmospheric reanalysis models ( Beck et al. 2017a ). Gauge-based precipitation observations are generally considered most accurate and reliable. But there are almost no meteorological stations in the vast western and northern TP

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Bin Yong, Liliang Ren, Yang Hong, Jonathan J. Gourley, Xi Chen, Jinwei Dong, Weiguang Wang, Yan Shen, and Jill Hardy

are the 10 selected catchments, stream networks, and large reservoirs. Note that the red dotted lines in the bottom picture represent the boundaries of two midstream catchments (catchments 8 and 9). Catchment 10 is the whole Laoha basin. In this study, we selected 10 catchments ( Fig. 1 , bottom) including seven headwater catchments from north to south (catchments 1–7), two midstream catchments (catchments 8 and 9, indicated with the dotted boundaries in Fig. 1 , bottom), and the whole basin

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Rui Sun, Xueqin Zhang, Yang Sun, Du Zheng, and Klaus Fraedrich

predominant causes for lake changes based on a balance between inflow (e.g., rainfall over lake, river inflows) and outflow (e.g., evaporation from lake). As the runoff entering the lake can influence the lake level directly, it is important to estimate the streamflow of inflowing rivers and its responses to climate change. Fig . 1. The geographic position, elevation, and river network of Kadongjia River watershed and its 35 subwatersheds for SWAT modeling. The boundaries and drainage system of the

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