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Yanan Meng, Jianhua Sun, Yuanchun Zhang, and Shenming Fu

parameters, precipitation, and background circulations for all MCS categories are presented in section 3 ; and finally, section 4 presents a conclusion and discusses the results. Fig . 1. Geographic distribution of elevations in southwestern China (shading; m). The blue box is the study region, while the extended area (red box) denotes the MCS formation area. The purple lines represent the boundaries of the Tibetan Plateau and the Yungui Plateau. 2. Data and methods a. Data Hourly 0.05° × 0

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Simon R. Osborne and Graham P. Weedon

related to radiative cooling of the surface, typically in calm surface conditions, the eddy-covariance measurements of latent heat flux at 10 m almost invariably fail to represent the times, magnitudes and changes in negative heat flux overnight ( Fig. 7d ). For the same reasons, JULES is currently unable to simulate appropriate negative latent heat flux during dewfall conditions. Despite the improvement in JULES SHG overnight when using canht-rootd-kext compared to control , and also despite the

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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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M. Alves, D. F. Nadeau, B. Music, F. Anctil, and A. Parajuli

models ( Sellers et al. 1997 ; Stocks et al. 1998 ; Bonan 2008 ). To this end, land surface models (LSMs) are typically used to simulate vertical exchanges of energy, mass, and momentum, and to provide boundary conditions for atmospheric and hydrological models ( Letts et al. 2000 ; Abramowitz et al. 2008 ; Martynov et al. 2013 ; Weedon et al. 2014 ). In general, an LSM requires time-invariant information for soil and vegetation properties and meteorological forcing for each time step of the

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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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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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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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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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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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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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