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Timothy H. Raupach, Auguste Gires, Ioulia Tchiguirinskaia, Daniel Schertzer, and Alexis Berne

al. 2008 ), climate simulations ( Royer et al. 2008 ), weather model outputs ( Gires et al. 2011 ), weather radars ( Nykanen and Harris 2003 ; Verrier et al. 2010 ; Gires et al. 2011 ), and rain gauge data (e.g., Fraedrich and Larnder 1993 ; Olsson 1995 ; Tessier et al. 1996 ; De Lima and Grasman 1999 ; Molnar and Burlando 2008 ; De Lima and De Lima 2009 ) have been used. At smaller scales, studies have used lidar ( Mandapaka et al. 2009 ) and disdrometer measurements ( De Montera et al

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Dongqi Lin, Ben Pickering, and Ryan R. Neely III

://www.edmundoptics.com/resources/application-notes/imaging/contrast/ . Emory , A. E. , B. Demoz , K. Vermeesch , and M. Hicks , 2014 : Double bright band observations with high-resolution vertically pointing radar, lidar, and profilers . J. Geophys. Res. Atmos. , 119 , 8201 – 8211 , https://doi.org/10.1002/2013JD020063 . 10.1002/2013JD020063 Fabry , F. , 2015 : Radar Meteorology: Principles and Practice . Cambridge University Press, 254 pp . 10.1017/CBO9781107707405 Gunn , R. , and G. D. Kinzer , 1949 : The terminal velocity of fall for water

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H. Leijnse, R. Uijlenhoet, C. Z. van de Beek, A. Overeem, T. Otto, C. M. H. Unal, Y. Dufournet, H. W. J. Russchenberg, J. Figueras i Ventura, H. Klein Baltink, and I. Holleman

located at approximately 25 km from the CESAR site. In addition to these instruments, CESAR has multiple lidars and radiometers, an extensive radiation measurement site [Baseline Surface Radiation Network (BSRN); see, e.g., Wang et al. 2009 ], and a 213-m-high tower in which profiles of several variables such as temperature and wind are measured. Aerosols are sampled at 60 m in this mast, and turbulent fluxes are measured on the site as well. Hydrological data (ditch discharges, groundwater levels

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S. McKenzie Skiles and Thomas H. Painter

radiative forcing time series estimated from changes in surface reflectance following the method presented in Painter et al. (2007b) , which constitutes the long-term record of dust radiative forcing in the Colorado Rockies ( Painter et al. 2007b ). 2. Methods a. Forcing and validation measurements Following is a brief description of the relevant snow observations for radiative transfer model forcing and validation; a detailed description of the full dataset can be found in Skiles and Painter (2017

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Neil Debbage and J. Marshall Shepherd

analysis focused on 19–22 September since these days incorporated the most intense precipitation. First, the precipitation from the urban simulation was compared with three sets of observations to ensure that the model adequately captured the dominant features of the storm event. The spatial and temporal distribution of the modeled rainfall was evaluated using the National Centers for Environmental Prediction (NCEP) Stage IV quantitative precipitation estimates (QPEs; Nelson et al. 2016 ). The NCEP

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Zhong Zhong, Wei Lu, Shuai Song, and Yaocun Zhang

Faivre R. , 2010 : Aerodynamic roughness length estimation from very high-resolution imaging LIDAR observations over the Heihe basin in China . Hydrol. Earth Syst. Sci. , 14 , 2661 – 2669 . DeBruin, H. A. R. , and Moore C. J. , 1985 : Zero-plane displacement and roughness length for tall vegetation, derived from a simple mass conservation hypothesis . Bound.-Layer Meteor. , 31 , 39 – 49 . Entekhabi, D. , and Eagleson P. , 1989 : Land surface hydrology parameterization for the

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Clare Webster, Nick Rutter, Franziska Zahner, and Tobias Jonas

) Schematic map of the Seehornwald field site showing the location of the rail and linear array with reference to locations of radiometers from the distributed array on the forest floor. Filled points denote pyranometers and open points denote pyrgeometers. Radiometers in the distributed configuration are in blue and the linear configuration is in red. Green circles represent tree crown positions determined by aerial lidar data. Numbering of radiometers indicates those selected in the analysis with three

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Song-Lak Kang, Kenneth J. Davis, and Margaret LeMone

. , Gamage N. , Hagelberg C. R. , Kiemle C. , Lenschow D. H. , and Sullivan P. P. , 2000 : An objective method for deriving atmospheric structure from airborne lidar observations. J. Atmos. Oceanic Technol. , 17 , 1455 – 1468 . 10.1175/1520-0426(2000)017<1455:AOMFDA>2.0.CO;2 Deardorff, J. W. , and Willis G. E. , 1985 : Further results from a laboratory model of the convective planetary boundary layer. Bound.-Layer Meteor. , 32 , 205 – 236 . 10.1007/BF00121880 Holland, J. Z

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S. Bhushan and A. P. Barros

compare simulated spatial patterns of cyclonicity against satellite observations of clouds and rainfall. Barros et al. (2004 , 2006 ) noted the strong co-organization of the diurnal cycle of precipitation features and landform in the Himalayan range [contiguous regions of rainfall identified in the Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR) data; Nesbitt et al. 2000 ]. The hypothesis they proposed is that the space–time distribution of such precipitation features is

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Brice Boudevillain, Hervé Andrieu, and Nadine Chaumerliac

component is driven by the VIL evolution in the atmospheric column. The RadVil formulation is inspired from the model proposed by Georgakakos and Bras (1984) , which summarizes the rainfall formation processes in the conceptual way of a reservoir model. This model was designed to be coupled with a hydrological model in order to forecast floods on catchments subject to flash flooding. Several versions of this model have been proposed according to available observations in order to estimate the water

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