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Liang Chen, Trent W. Ford, and Priyanka Yadav

observations. As drier soil can be more sensitive to precipitation variability, precipitation with a similar or higher CV will lead to higher variability of soil moisture, which could potentially cause more flash drought events. Therefore, the overestimated flash drought can be associated with the combined effects of dry biases and higher precipitation variability in CESM2. c. Impacts of increased LAI on land surface and atmosphere Increased vegetation productivity and water uptake will both decrease soil

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Anna-Maria Tilg, Flemming Vejen, Charlotte Bay Hasager, and Morten Nielsen

Precipitation and other meteorological parameters were measured at Voulund (56.0372426°N, 9.159357°E, 67 m), a flat open area with a size of around 2000 m 2 and no nearby obstacles, in western Denmark in connection to the Danish hydrological observatory (HOBE) project ( Jensen and Illangasekare 2011 ). The focus of the HOBE project was the investigation of the influence of natural and anthropogenic changes on hydrological processes within the Skjern River catchment. The Danish Meteorological Institute (DMI

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

decreasing, this trend was statistically insignificant at the 95% level ( Klotzbach et al. 2018 ). Nonetheless, multiple studies of recent impactful TCs using different methodologies conclude that the storms produced more precipitation than they would have in the absence of anthropogenic forcing ( Van Oldenborgh et al. 2017 ; Risser and Wehner 2017 ; Emanuel 2017 ; Patricola and Wehner 2018 ; Wang et al. 2018 ; Trenberth et al. 2018 ; Reed et al. 2020 ). These results are highly relevant since

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Jessica C. A. Baker, Dayana Castilho de Souza, Paulo Y. Kubota, Wolfgang Buermann, Caio A. S. Coelho, Martin B. Andrews, Manuel Gloor, Luis Garcia-Carreras, Silvio N. Figueroa, and Dominick V. Spracklen

1. Introduction Global climate models offer a way to predict how increasing anthropogenic emissions and land-use change will impact climate. However, before models can be reliably used for future projections, it is necessary to validate their performance in the present day, including their ability to represent key physical processes in the climate system ( Flato et al. 2013 ). Such process-based model evaluation has become increasingly important as models have gained in complexity, with novel

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Jiali Ju, Heng Dai, Chuanhao Wu, Bill X. Hu, Ming Ye, Xingyuan Chen, Dongwei Gui, Haifan Liu, and Jin Zhang

Considering the large number of PAs in the three HMs, the Morris method was used to screen the most sensitive PAs before performing uncertainty analysis ( Morris 1991 ). The principle of the Morris method is the discretization of each input PA in levels and the implementation of a number of OAT designs, in which each PA is varied while others are fixed. The selection of the variation direction and the samples from the PA space is random. The elementary effects of each PA on the model output are estimated

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Liqing Peng, Zhongwang Wei, Zhenzhong Zeng, Peirong Lin, Eric F. Wood, and Justin Sheffield

Fig. 4b . All three satellite datasets show a bimodal structure with strong peaks at 100 and 200 W m −2 . The positive RBIAS of satellite products in Fig. 4a is associated with higher probability density between 200 and 300 W m −2 and lower probability density between 50 and 200 W m −2 . SRB and UMD have very similar PDF structures, which suggests the special treatments of aerosol, land use, water and ice clouds in UMD ( Ma and Pinker 2012 ) have marginal effects on the overall PDF in this

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

of 2030–49 is expected to increase by 1.89% in spring and by 2.59% in summer and to decrease by 4.42% in autumn and by 0.32% in winter; the monthly temperature of Tibet in spring, summer, autumn, and winter will increase by 1.65°, 1.76°, 1.96°, and 2.01°C, respectively. The second type is the presumptive scenario adopted because of the large uncertainty in the projections of future anthropogenic climate change ( Xu et al. 2003 ; Ding et al. 2007 ; Liu et al. 2009 ). Compared to the period of

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Qian Cao, Alexander Gershunov, Tamara Shulgina, F. Martin Ralph, Ning Sun, and Dennis P. Lettenmaier

previous analysis, we also showed that when ASM is high or storm precipitation is sufficiently large, extreme precipitation events can lead to extreme discharge events of the same POT threshold (see Fig. 12 in Cao et al. 2019 ). On the other hand, if the ASM is low, extreme precipitation may not lead to extreme discharge of the same POT threshold. In the following section, we examine whether the future increases in storm precipitation could outweigh the effects of future changes in ASM and thus

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Bailing Li, Matthew Rodell, Christa Peters-Lidard, Jessica Erlingis, Sujay Kumar, and David Mocko

time of in situ groundwater to atmospheric effects. Most wells in Pennsylvania are located in fractured sandstone, shale and crystalline rock aquifers [based on metadata of these wells; the USGS well numbers are provided in Li et al. (2019b) ] where fractures allow infiltrated water to reach the water table faster than in other types of media. These subsurface properties are not reflected in the hydraulic parameters used in Noah-MP, which were derived based on surface soil texture. The bedrock

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Anne Felsberg, Gabriëlle J. M. De Lannoy, Manuela Girotto, Jean Poesen, Rolf H. Reichle, and Thomas Stanley

with steep local relief and with hillslope materials of low shear strength. Time-variant preconditioning factors can be of anthropogenic, seismic, or hydrometeorological (climatic or seasonal) nature. In this study, we focus on the latter, taking into account solely hydrologically triggered landslides. To prevent loss of life and mitigate damages, efforts are made to predict the likelihood of landslides by determining and monitoring the conditions leading to landslides (hereafter referred to as

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