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Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, and Marco Borga

( Ivanov et al. 2004a , b ; Vivoni et al. 2007 ). The tRIBS model is a distributed physics-based model that explicitly accounts for the spatial variability of land surface descriptors (terrain, soil, and vegetation), soil moisture, and atmospheric forcing. Infiltration is simulated in a sloped heterogeneous and anisotropic soil based on a kinematic approximation for unsaturated flow ( Cabral et al. 1992 ; Garrote and Bras 1995 ). An adaptive multiple resolution approach based on TINs ( Vivoni et al

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Tracy M. Backes, Michael L. Kaplan, Rina Schumer, and John F. Mejia

detected based on similar reanalysis data ( Dettinger et al. 2011 ; Neiman et al. 2008 ). Date and spatial matching between satellite-based ARs and our approach are consistent only when basic attributes of intensity and geometry are used to detect AR events. However, when constraining the events to low-level kinematic attributes (LLJ winds > 15 m s −1 ), as suggested by Smith et al. (2010) , Ralph and Dettinger (2011) , and Kingsmill et al. (2013) , matching drops dramatically. Not only does the

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Barbara Turato, Oreste Reale, and Franco Siccardi

peaks occur at the end of October), but they could be concurring agents of a complex synergistic mechanism. 3. Moisture sources for the Piedmont 2000 flood event a. Method To investigate surface evaporative sources contributing to the flood event, we adopt a kinematic quasi-isentropic trajectory technique documented in Dirmeyer and Brubacker (1999) ; used by Reale et al. (2001) , Brubacker et al. (2001) , and Burde and Zangvil (2001a , b ); and based on the fully implicit isentropic algorithm of

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Zhe Li, Dawen Yang, Bing Gao, Yang Jiao, Yang Hong, and Tao Xu

processes with various precipitation inputs. This distributed modeling framework takes advantage of the geomorphologic similarities to reduce the spatial-structure complexity within a grid and to characterize the catchment topography by hillslope–stream formulation. In brief, GBHM includes the following components: a gridded discretization scheme, a subgrid parameterization scheme, a hillslope-based hydrological modeling module, and a kinematic wave flow routing module. a. Model setup Hillslope is the

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Masahiro Ryo, Oliver C. Saavedra Valeriano, Shinjiro Kanae, and Tinh Dang Ngoc

the four precipitation datasets. The DHM employed is the geomorphology-based hydrological model (GBHM; developed by Yang et al. 2002 ; see Fig. 3 and appendix for details). Hydrological processes such as precipitation, canopy interception, evapotranspiration, infiltration, percolation, and groundwater flow are simulated. The discharge is computed with the kinematic wave equation. The computational grid size was set to 500 m and the unit time step was set to 6 h in order to include the

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William Amponsah, Lorenzo Marchi, Davide Zoccatelli, Giorgio Boni, Marco Cavalli, Francesco Comiti, Stefano Crema, Ana Lucía, Francesco Marra, and Marco Borga

) Spatially distributed rainfall–runoff model A distributed hydrologic model is used to examine hydrologic response associated with space–time radar rainfall variability and to check consistency with postflood indirect peak flow estimates. The Kinematic Local Excess Model (KLEM; Marchi et al. 2010 ) combines a grid-based runoff-generation model and a network-based hillslope and channel transport model. Runoff generation is simulated by applying the Soil Conservation Service Curve Number (SCS-CN) approach

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Timothy J. Lang, Steven A. Rutledge, and Robert Cifelli

.1175/1520-0493(2000)128<2687:TRBPAL>2.0.CO;2 Cetrone, J. , and Houze R. A. , 2006 : Characteristics of tropical convection over the ocean near Kwajalein. Mon. Wea. Rev. , 134 , 834 – 853 . 10.1175/MWR3075.1 Cifelli, R. , Petersen W. A. , Carey L. D. , Rutledge S. A. , and da Silva Dias M. A. F. , 2002 : Radar observations of kinematic, microphysical, and precipitation characteristics of two MCSs in TRMM LBA. J. Geophys. Res. , 107 , 8077 . doi:10.1029/2000JD000264 . 10.1029/2000JD000264 Cifelli, R

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Luis Gimeno, Raquel Nieto, Ricardo M. Trigo, Sergio M. Vicente-Serrano, and Juan Ignacio López-Moreno

. 2006 ), numerical water vapor tracers ( Joussame et al. 1984 ; Koster et al. 1986 ), and algorithms that use quasi-isentropic back trajectories in combination with model-derived surface fluxes to determine evaporation sources along back trajectories ( Dirmeyer and Brubaker 1999 ; Reale et al. 2001 ; Dirmeyer and Brubaker 2007 ). Most of the earlier-mentioned Lagrangian studies, however, have been limited by methodological (no kinematic trajectories) and conceptual (e.g., assumptions about how

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Jessica D. Lundquist, Paul J. Neiman, Brooks Martner, Allen B. White, Daniel J. Gottas, and F. Martin Ralph

. Hydrol. Processes , 12 , 1569 – 1587 . 10.1002/(SICI)1099-1085(199808/09)12:10/11<1569::AID-HYP682>3.0.CO;2-L Marshall, J. S. , Langille R. C. , and Palmer W. Mc K. , 1947 : Measurements of rainfall by radar. J. Meteor. , 4 , 186 – 192 . 10.1175/1520-0469(1947)004<0186:MORBR>2.0.CO;2 Marwitz, J. D. , 1983 : The kinematics of orographic airflow during Sierra storms. J. Atmos. Sci. , 40 , 1218 – 1227 . 10.1175/1520-0469(1983)040<1218:TKOOAD>2.0.CO;2 Marwitz, J. D. , 1987 : Deep

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Jonathan J. Gourley, Scott E. Giangrande, Yang Hong, Zachary L. Flamig, Terry Schuur, and Jasper A. Vrugt

-RDHM The model concepts used in this study originate from the Sacramento model ( Burnash et al. 1973 ). This model was subdivided into grid cells having 4.76-km resolution, in accordance with the NWS Hydrologic Rainfall Analysis Project (HRAP) grid. Each grid cell has a water balance component as well as kinematic overland and channel routing components ( Koren et al. 2004 ). The water balance component of the model, referred to as the Sacramento Soil Moisture Accounting model (SAC-SMA), considers

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