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Paul A. Dirmeyer, Yan Jin, Bohar Singh, and Xiaoqin Yan

than past studies of land–atmosphere interaction, and the peculiarities of individual climate models can be minimized. In this study, we perform a suite of analyses in three categories: the land surface (namely soil moisture) behavior, the land–atmosphere interface, and the atmospheric boundary layer. These categories represent segments in the feedback loop from land to atmosphere ( Dirmeyer 2006 ). Specifically, we examine the changes in mean temporal variability and lagged autocorrelation (often

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Karianne Ødemark, Malte Müller, and Ole Einar Tveito

. (2011) studied PMP for a catchment in California and applied a regional-scale high-resolution physical atmospheric model. Other studies have also applied NWP-based methods to estimate PMP, where the approach is based on physical maximization of a historical extreme rainstorm. Ishida et al. (2015a) alters boundary and initial conditions to maximize precipitation over targeted catchments. Chen and Hossain (2018) pointed out that there seems to have emerged a consensus that using a physical

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Dan Li, Elie Bou-Zeid, Mary Lynn Baeck, Stephen Jessup, and James A. Smith

rainfall modeling remains a significant challenge, particularly because of the strong and complex interactions between synoptic forcing, microphysical processes, land–atmosphere exchanges, and the evolution of the atmospheric boundary layer ( Pielke 2001 ; Shephard 2005 ; Trier et al. 2011 ; Yeung et al. 2011 ). The impact of land–atmosphere exchanges and atmospheric boundary layer processes on warm season rainfall is the subject of active research ( Trier et al. 2004 , 2008 , 2011 ), including a

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Hyun Il Choi, Xin-Zhong Liang, and Praveen Kumar

complete list of important factors for comprehensive terrestrial hydrologic simulations over larger basins, including aquifer recharge, regulation storage, consumptive use, and channel and groundwater flow routing across the basin boundaries. In the current CSSF mode, the overland-based surface flow scheme cannot fully capture the storage effect of real streams, and the topographically controlled baseflow scheme associated with the water table depth neglects the possible contribution from the deeper

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Vasubandhu Misra and Amit Bhardwaj

over PF. In fact, Misra et al. (2017a , b) show that the seasonal cycle of the hydroclimate over PF, the Loop and the Florida Currents, and the seasonal cycle of the upper-ocean temperatures in the West Florida Shelf and along the eastern coast of PF are all nearly in phase with each other. Misra and Mishra (2016) indicate that this overlap in the seasonal cycle of the upper ocean and that of the hydroclimate of PF are not a mere coincidence but are part of a complex feedback process. For

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Philippe Lucas-Picher, Fredrik Boberg, Jens H. Christensen, and Peter Berg

Danish Meteorological Institute ( Christensen et al. 2006 ). Details on the current version of HIRHAM5 can be found in Lucas-Picher et al. (2011) . The driving field providing initial and lateral boundary conditions is ERA-Interim (hereafter ERA-I; Dee et al. 2011 ), available at a resolution of T255 (~0.7° or ~80 km). The zonal and meridional wind components, atmospheric temperature, specific humidity, and surface pressure are introduced to the RCM at 6-h intervals as LBCs of the model. Sea

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Youcun Qi and Jian Zhang

represents the total number of matching gauge and radar pixel pairs in the BBA. A matching pair of radar-gauge is found if 1) the gauge location is within the boundary of a 1° × 1 km radar pixel and 2) both the radar estimate and the gauge observation are greater than zero. In addition, is an averaged radar rainfall in 5° × 5 km box centered at the corresponding gauge: Here is the averaged hourly gauge precipitation: Table 1. Summary of the events. In the current study, the corrected

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Chad W. Higgins, Eric Pardyjak, Martin Froidevaux, Valentin Simeonov, and Marc B. Parlange

is a constant whose value is typically taken as 0.25. This power-law formulation has been shown to be a good approximation of the typical neutrally stable atmospheric velocity profile ( Brutsaert and Yeh 1970 ). The flux of water vapor is modeled using a mixing length approach: Using a single-step change in surface humidity as boundary conditions, a closed form of the humidity distribution can be obtained: where is the friction velocity, is a constant whose value is taken as 0.8 in the

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Erin Dougherty and Kristen L. Rasmussen

nature of floods in the current climate, it is necessary to understand how they may change in a future warmer climate. Future flood risk has been examined globally and in the CONUS using flood inundation models and flood exposure estimates under various population growth scenarios ( Hirabayashi et al. 2013 ; Wing et al. 2018 ). While these studies highlight an increased future flood risk, future flood estimates are uncertain due to 1) the underestimation of rainfall in global climate models (GCMs

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Dikra Khedhaouiria, Stéphane Bélair, Vincent Fortin, Guy Roy, and Franck Lespinas

Tapiador et al. 2017 ). When used as input for subsequent modeling (e.g., hydrology, land surface data assimilation), the uncertainties of the precipitation need to be estimated ( Pappenberger and Beven 2006 ). The current study focuses on uncertainties of gridded precipitation analysis (PA) by using ensembles. Recent research on ensemble meteorological fields ( Buizza 2019 ; Duan et al. 2019 ; Raut et al. 2018 , among others) has revealed an increasing interest in the uncertainty assessment and an

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