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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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Li Fang, Xiwu Zhan, Jifu Yin, Jicheng Liu, Mitchell Schull, Jeffrey P. Walker, Jun Wen, Michael H. Cosh, Tarendra Lakhankar, Chandra Holifield Collins, David D. Bosch, and Patrick J. Starks

finescale based on the regression relationship, a moving window approach was applied, in which the central prediction area moves across the whole experiment region with some overlap from the previous area ( Gao et al. 2012 ). Results showed that this method was effective to remove the boundary effects because of common samples from overlap regions. In our implementation, MODIS global LAI and Fraction of Photosynthetically Active Radiation (FPAR) product (MOD15A2, V005) and LST (MOD11A1.006) product are

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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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Alyssa M. Stansfield, Kevin A. Reed, Colin M. Zarzycki, Paul A. Ullrich, and Daniel R. Chavas

(with 1984 discarded for spinup), resulting in 30 years of data. Since the model simulations do not include coupling to an ocean model, SST boundary conditions are set using the merged Hadley–NOAA/optimum interpolation (OI) dataset as described in Hurrell et al. (2008) . A disadvantage of using prescribed SSTs is the lack of TC-generated cold wakes, which could result in positive TC intensity biases ( Schade and Emanuel 1999 ). Simulations were performed with three different variable

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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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Xiaoyin Liu, Junzeng Xu, Shihong Yang, Yuping Lv, and Yang Zhuang

d were the best in those periods, with high R 2 (>0.90) and IOA (>0.97), and low RMSE (<0.51 mm h −1 ). Fig . 6. Average diurnal variation in model performance based on statistical indexes (slope, RMSE, R 2 , and IOA) for ET estimation during daytime in the 2015 and 2016 rice seasons. The reason these two hours provide the best estimation may be related to the neutral stability assumption for the atmospheric boundary layer. In several current studies on r a model implementation, neutral

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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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W. M. De Kock, R. C. Blamey, and C. J. C. Reason

rainfall recorded as late as 25 January 1981 over the study region and particularly in the Laingsburg region (about 100 km east of the eastern boundary of the red box in Fig. 7 ), where much devastation and loss of life occurred on 24 and 25 January ( Taljaard 1985 ). Figure 7 also shows different moisture sources between the COL and AR events. In the case of the COL, there is offshore flow of warm dry air over eastern South Africa that picks up moisture from the warm Agulhas Current, which flows

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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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Dayal Wijayarathne, Sudesh Boodoo, Paulin Coulibaly, and David Sills

in 1943 ( Sills and Joe 2019 ; Douglas 1990 ). Since then, the radar network was gradually expanded, and the application of weather radar in hydrometeorological applications has evolved significantly. The current Canadian radar network includes 31 radar stations and covers most of the populated areas ( Joe and Lapczak 2002 ). This radar network provides reflectivity measurement at a range of 256 km in a radius around the radar site and a Doppler coverage at a range of 120 km around the site

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