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Jeffrey D. Massey, W. James Steenburgh, Sebastian W. Hoch, and Derek D. Jensen

parameterize and can exhibit significant spatial variability and—for characteristics like soil moisture, albedo, and emissivity—temporal variability (e.g., Chen and Dudhia 2001 ; Ek et al. 2003 ; Malek 2003 ). Land surface characteristics affect near-surface forecasts of temperature, moisture, and momentum by changing the relative importance of components of the surface energy balance (SEB), with the net radiation R n partitioned into surface sensible heat flux H , latent heat flux LE, and ground

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Robert S. Arthur, Katherine A. Lundquist, Jeffrey D. Mirocha, and Fotini K. Chow

1. Introduction In mountainous terrain, the diurnal variations of the surface sensible heat flux can lead to thermally driven upvalley or upslope flow during the daytime and downvalley or downslope flow during the nighttime ( Zardi and Whiteman 2013 ). Topographic effects on radiation can strongly influence these flows by creating large spatiotemporal inhomogeneities in the net radiation, and thus in the surface energy budget. These effects include topographic shading, where direct solar

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Jeffrey D. Massey, W. James Steenburgh, Sebastian W. Hoch, and Jason C. Knievel

et al. 2003 ; Cheng and Steenburgh 2005 ). In this paper, we concentrate on the initialization and parameterization of land surface characteristics and processes, which control the surface energy budget and contribute to NST errors through the inaccurate partitioning of sensible, latent, and ground heat fluxes (e.g., Huang et al. 1996 ; Davis et al. 1999 ; Marshall et al. 2003 ; Reeves et al. 2011 ). In most land surface models (LSMs), land surface parameters (e.g., albedo, roughness length

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Feimin Zhang and Zhaoxia Pu

al. 2007 , 2016 ). Surface radiative cooling is closely related to the surface energy balance, which is composed of incoming and outgoing radiation and heat fluxes in the atmosphere, canopy, and soil. The complexities involved in the calculation of fluxes are substantial, especially in the case of radiation fog or ice fog. In numerical models, the parameterization of the surface energy balance is strongly related to the parameterizations of both the land surface and boundary layer. Specifically

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Manuela Lehner, C. David Whiteman, Sebastian W. Hoch, Derek Jensen, Eric R. Pardyjak, Laura S. Leo, Silvana Di Sabatino, and Harindra J. S. Fernando

time of local sunset, that is, the time of shadow passage ( Fig. 8a ) and the time of heat-flux reversal at the lowest tower levels, from an upward heat flux to a downward heat flux at 1810 MST at ES5 and at 1835 MST at ES2 and ES3 (not shown). Here, cooling onset refers to the beginning of the rapid near-surface temperature decrease after local sunset. Weaker cooling started already at an earlier time. The spatial distribution of cooling-onset times at the PWIDS stations and at the towers is shown

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H. J. S. Fernando, E. R. Pardyjak, S. Di Sabatino, F. K. Chow, S. F. J. De Wekker, S. W. Hoch, J. Hacker, J. C. Pace, T. Pratt, Z. Pu, W. J. Steenburgh, C. D. Whiteman, Y. Wang, D. Zajic, B. Balsley, R. Dimitrova, G. D. Emmitt, C. W. Higgins, J. C. R. Hunt, J. C. Knievel, D. Lawrence, Y. Liu, D. F. Nadeau, E. Kit, B. W. Blomquist, P. Conry, R. S. Coppersmith, E. Creegan, M. Felton, A. Grachev, N. Gunawardena, C. Hang, C. M. Hocut, G. Huynh, M. E. Jeglum, D. Jensen, V. Kulandaivelu, M. Lehner, L. S. Leo, D. Liberzon, J. D. Massey, K. McEnerney, S. Pal, T. Price, M. Sghiatti, Z. Silver, M. Thompson, H. Zhang, and T. Zsedrovits

evening transition, the signs of heat flux and vertical temperature gradient reverse, convective turbulence collapses, and the downslope/downvalley flow system reemerges. A host of physical processes contribute to morning ( Whiteman 1982 ; Princevac and Fernando 2008 ) and evening transitions ( Hunt et al. 2003 ; Nadeau et al. 2011 ). Other flow types include local (micro) circulations driven by thermal and roughness contrasts arising from land-cover inhomogeneities ( Jannuzzi 1993 ; Rife et al

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Jeffrey D. Massey, W. James Steenburgh, Jason C. Knievel, and William Y. Y. Cheng

modeling systems, resolutions, and configurations (e.g., Cheng and Steenburgh 2005 ; Hart et al. 2005 ; Zhang et al. 2013 ; Massey et al. 2014 ). Hypothesized contributors to the DTR underprediction include inadequate vertical or horizontal resolution, near-surface turbulence flux errors, or inaccurate land surface characteristics and processes (e.g., Hanna and Yang 2001 ; Mass et al. 2002 ; Marshall et al. 2003 ; Cheng and Steenburgh 2005 ; Massey et al. 2014 ). Recently, Massey et al. (2014

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Matthew E. Jeglum, Sebastian W. Hoch, Derek D. Jensen, Reneta Dimitrova, and Zachariah Silver

zone 12T) of the study area at DPG with the southern part of Granite Mountain detailed in the inset. The color-coded circles indicate the daily frequency of LTFs at various sites at DPG. Elevation contours are 80 m in the main plot and 30 m in the inset, with the 1315-m contour annotated in both. The transect in the inset marked L1–L4 is the primary slope transect in this study. The location of the flux tower ES2 and the Granite Ridge and West slope sites are annotated in the inset. An extensive

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Sean M. Wile, Joshua P. Hacker, and Kenneth H. Chilcoat

Assimilation Research Testbed. Bull. Amer. Meteor. Soc. , 90 , 1283–1296 , doi: 10.1175/2009BAMS2618.1 . Barker, D. , and Coauthors , 2012 : The Weather Research and Forecasting Model’s Community Variational/Ensemble Data Assimilation System: WRFDA . Bull. Amer. Meteor. Soc. , 93 , 831 – 843 , doi: 10.1175/BAMS-D-11-00167.1 . Beljaars, A. C. M. , 1995 : The parameterization of surface fluxes in large-scale models under free convection . Quart. J. Roy. Meteor. Soc. , 121 , 255 – 270 , doi: 10

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Hailing Zhang, Zhaoxia Pu, and Xuebo Zhang

studied ( Hanna and Yang 2001 ; Zhang and Zheng 2004 ). To accurately simulate near-surface atmospheric conditions, several factors must be represented properly in numerical models. These include land use, topography, surface heat flux transport, and various characteristics of the lower atmosphere ( Lee et al. 1989 ; Wolyn and McKee 1989 ; Shafran et al. 2000 ; Cheng and Steenburgh 2005 ). Thus, the accurate simulation of near-surface atmospheric diurnal variation is one of the most important and

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