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Ridwan Siddique and Alfonso Mejia

also accumulate snow and generate hillslope snowmelt based on the near-surface temperature. The hillslope runoff, generated at each grid cell by SAC-HT and SNOW-17, is routed to the stream network using a nonlinear kinematic wave algorithm ( Koren et al. 2004 ; Smith et al. 2012 ). Similarly, flows in the stream network are routed downstream using a nonlinear kinematic wave that accounts for parameterized stream cross-sectional shapes ( Koren et al. 2004 ; Smith et al. 2012 ). Here we run HL

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Hong-Yi Li, L. Ruby Leung, Augusto Getirana, Maoyi Huang, Huan Wu, Yubin Xu, Jiali Guo, and Nathalie Voisin

(MOSART) is a recently developed large-scale routing model with scale adaptive treatments of within- and between-grid routing processes. MOSART uses the kinematic wave equation for subgrid surface runoff and channel routing and for routing channel flow from one grid cell to another. Li et al. (2013) evaluated MOSART at the Columbia River basin in the U.S. Pacific Northwest, where excellent observation data are available. They showed that, under natural conditions, MOSART is capable of capturing the

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Katja Friedrich, Evan A. Kalina, Joshua Aikins, Matthias Steiner, David Gochis, Paul A. Kucera, Kyoko Ikeda, and Juanzhen Sun

(collisions) that limited drop size (larger drops would break up), or the distance between the melting layer and the ground. Future studies should identify the role of low-level convergence on the precipitation formation in the mountains. It would be interesting to determine the degree to which observations may be able to quantify and track low-level convergence and assess how well numerical models might reproduce the kinematic field. Acknowledgments The authors thank the organizations, technicians

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Brian Henn, Rachel Weihs, Andrew C. Martin, F. Martin Ralph, and Tashiana Osborne

://doi.org/10.1175/JHM-D-17-0098.1 . 10.1175/JHM-D-17-0098.1 Marwitz , J. D. , 1983 : The kinematics of orographic airflow during Sierra storms . J. Atmos. Sci. , 40 , 1218 – 1227 , https://doi.org/10.1175/1520-0469(1983)040<1218:TKOOAD>2.0.CO;2 . 10.1175/1520-0469(1983)040<1218:TKOOAD>2.0.CO;2 Marwitz , J. D. , 1987 : Deep orographic storms over the Sierra Nevada. Part I: Thermodynamic and kinematic structure . J. Atmos. Sci. , 44 , 159 – 173 , https://doi.org/10

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Deborah K. Nykanen, Efi Foufoula-Georgiou, and William M. Lapenta

. Perica and Foufoula-Georgiou (1996a) also established an empirical connection between statistical and physical storm characteristics by quantifying relations between the scaling parameter H and thermodynamic or kinematic indices of the prestorm environment, such as, the convective available potential energy (CAPE), convective inhibition, bulk Richardson number, wind shear, and severe weather threat index. The best correlation was obtained with CAPE, and only a small improvement in the explained

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Jian Sun and Guido D. Salvucci

momentum is approximated as . In our model, we estimated vegetation height as a free constant parameter. Following Chen et al. (1997) we specify the relation between and as In Eq. (A8) , is the kinematic molecular viscosity ( m 2 s −1 ), Re is the roughness Reynolds number, is the surface friction velocity, approximated (without stability correction) as , and C is a free parameter. In the equation, is further modified based on the formulation of . For LE , we need to consider

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Christopher J. Anderson, Raymond W. Arritt, and John S. Kain

I: General kinematic structure. J. Atmos. Sci. , 44 , 987 – 1008 . 10.1175/1520-0469(1987)044<0987:DWHPCP>2.0.CO;2 Koren, V. , Schaake J. , Mitchell K. , Duan Q-Y. , Chen F. , and Baker J. M. , 1999 : A parameterization of snowpack and frozen ground intended for NCEP weather and climate models. J. Geophys. Res. , 104 , D16 . 19569 – 19585 . 10.1029/1999JD900232 Kreitzberg, C. , and Perkey D. , 1977 : Release of potential instability. Part II: The mechanism of

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Lennert B. Stap, Bart J. J. M. van den Hurk, Chiel C. van Heerwaarden, and Roel A. J. Neggers

. The mean boundary layer temperature θ was diagnosed as the surface temperature, which is representative for the governing surface fluxes and properties. Mixing layer specific humidity q was diagnosed as the value at the lowest model level. The entrainment flux w e Δ θ is estimated as the minimal value of the profile of the turbulent kinematic flux of dry static energy. Boundary layer height h is taken as the height at which this minimum occurs, while w e Δ q is the turbulent moisture

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Marc Schleiss and James Smith

pp . Cifelli, R. , Petersen W. A. , Carey L. D. , Rutledge S. A. , and Dias M. A. F. D. , 2002 : Radar observations of the kinematic, microphysical, and precipitation characteristics of two MCSs in TRMM LBA . J. Geophys. Res. , 107 , 8077 , doi: 10.1029/2000JD000264 . Crane, R. K. , 1979 : Automatic cell detection and tracking . IEEE Trans. Geosci. Electron. , 17 , 250 – 262 , doi: 10.1109/TGE.1979.294654 . Delhomme, J.-P. , 1978 : Kriging in the hydrosciences . Adv. Water

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Yadong Wang, Stephen Cocks, Lin Tang, Alexander Ryzhkov, Pengfei Zhang, Jian Zhang, and Kenneth Howard

. Tang , 2016 : Operational C-band dual-polarization radar QPE for the subtropical complex terrain of Taiwan . Adv. Meteor. , 2016 , 4294271, https://doi.org/10.1155/2016/4294271 . 10.1155/2016/4294271 Wu , D. , K. Zhao , M. Kumjian , X. Chen , H. Huang , M. Wang , A. Didlake , Y. Duan , and F. Zhang , 2018 : Kinematics and microphysics of convection in the outer rainband of Typhoon Nida (2016) revealed by polarimteric radar . Mon. Wea. Rev. , 146 , 2147 – 2159 , https

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