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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

magnitude of SM–ET relationships, representation of variables impacting land–atmosphere interactions over the Caatinga in ERA5-Land, HadGEM3, and BAM-1.2 could still be improved. d. Tracing surface-to-atmosphere moisture pathways When considering land–atmosphere moisture transfer pathways, it can be helpful to distinguish between processes that operate at the land–atmosphere interface and processes that occur in the atmospheric boundary layer. For example, the coupling between the land surface and

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Kichul Jung, Taha B. M. J. Ouarda, and Prashanth R. Marpu

Ouarda 2008 ; Wazneh et al. 2016 ). Several methods have been proposed to delineate homogeneous regions. For instance, Matalas et al. (1975) and Beable and McKerchar (1982) used geographic and administrative boundaries, Hosking and Wallis (1997) proposed hierarchical clustering using Ward’s method ( Ward 1963 ), and Ouarda et al. (2001) recommended using canonical correlation analysis (CCA) to determine hydrological neighborhoods to improve the estimation of flood quantiles. Durocher et al

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Peter J. Shellito, Sujay V. Kumar, Joseph A. Santanello Jr., Patricia Lawston-Parker, John D. Bolten, Michael H. Cosh, David D. Bosch, Chandra D. Holifield Collins, Stan Livingston, John Prueger, Mark Seyfried, and Patrick J. Starks

thus act as a capping evaporative “crust” barrier at the upper boundary of the topmost soil layer” ( Ek et al. 2003 ). In Noah, this is accomplished with a single empirical parameter, denoted fx, which is set to 2. The evaporation term E dir is formulated as ( Ek et al. 2003 ) (1) E dir = ( 1 − σ f ) × FX fx × E p , where σ f is fractional vegetation cover (prohibiting evaporation beneath the canopy), FX is relative degree of saturation, and E p is potential evaporation rate. The squared term

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Guiling Wang, Christine J. Kirchhoff, Anji Seth, John T. Abatzoglou, Ben Livneh, David W. Pierce, Lori Fomenko, and Tengyu Ding

current study compares precipitation characteristics and their future changes derived from the MACA-M (simply referred to as MACA hereafter) and LOCA databases, and elucidates what may have caused the differences between these two products using the U.S. Northeast as a case study. Theoretical analysis of Earth’s energy and water budgets and atmospheric thermodynamics suggests that as global temperature rises, global precipitation amount and extreme precipitation intensity will increase, while

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Rasool Porhemmat, Heather Purdie, Peyman Zawar-Reza, Christian Zammit, and Tim Kerr

Alps ( Fitzharris and Garr 1995 ; Sirguey 2009 ). This contribution impacts the hydroelectricity generation capability and sustainable irrigation during summer ( Hendrikx et al. 2012 ; McKerchar et al. 1998 ; Thompson 2002 ). However, climate change is expected to substantially impact the seasonal snowpacks in the Southern Alps ( Hendrikx et al. 2012 ; Poyck et al. 2011 ; Jobst et al. 2018 ). Regional climate models currently suggest that the maximum daily temperatures in the Southern Alps of

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Hernan A. Moreno, Enrique R. Vivoni, and David J. Gochis

limits to flood predictability in mountain catchments experiencing summer convection are currently unknown. This study seeks to quantify flood predictability using the triangulated irregular network (TIN)-based Real-time Integrated Basin Simulator (tRIBS; Ivanov et al. 2004a ; Vivoni et al. 2007a ) as a tool to generate flood predictions using radar nowcasting QPFs. With these coupled simulation tools, we quantify the relation of flood forecasting skill with lead time in a set of mountain basins

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Shakti P. C.,, M. Maki, S. Shimizu, T. Maesaka, D.-S. Kim, D.-I. Lee, and H. Iida

variable because of the effects of the topography ( Barros et al. 2000 ). Austin et al. (2002) show that during a storm, rainfall may vary by tens of millimeters per hour, from minute to minute, and over distances of only a few tens of meters. Weather radar, at S-band, C-band, or X-band wavelengths, is one of the currently available options used to estimate the spatial and temporal distribution of precipitation over a specific time interval. Several output parameters, for example, horizontal

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David M. Lawrence and Julia M. Slingo

with enhanced surface evaporation into rainfall (the “direct” feedback). Instead, the indirect feedback, which some studies suggest is the dominant feedback (e.g., Schär et al. 1999 ), considers how soil moisture affects precipitation through its influence on boundary layer characteristics and atmospheric stability. The indirect feedback mechanism, illustrated in schematic form in Fig. 1 , works in the following way. Anomalously wet soil generated by a significant rainfall event induces a strong

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M. J. Best, A. Beljaars, J. Polcher, and P. Viterbo

surface schemes within the same GCM. This will allow the attribution of differences in the model as a whole to differences in land surface schemes. We therefore need to design a consistent “plug compatible” structure for the interface between these land surface schemes and the boundary layer schemes. The interface needs not only to cover all the physical processes that are currently treated at the interface, but it should also be compatible with all existing numerical schemes. There are several ways

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George J. Huffman, Robert F. Adler, Mark M. Morrissey, David T. Bolvin, Scott Curtis, Robert Joyce, Brad McGavock, and Joel Susskind

estimates, mostly resulting from geo-IR. In the current release, the 3-hourly images in each day (0000 UTC, . . . , 2100 UTC) are summed to produce the daily value. The daily product is considered more reliable than individual 3-hourly images for two reasons. First, GPI-type IR estimates show better correlation with precipitation as the averaging period increases ( Arkin and Meisner 1987 ). Second, the current procedure does not take into account the time of day (i.e., diurnal cycle biases). As a result

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