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

1. Introduction Accurate temperature forecasts by numerical weather prediction (NWP) models are critical for the protection of life and property, economic and operational activities, and routine day-to-day planning. Temperature forecasts not only affect near-surface (2 m) conditions, but also atmospheric stability, planetary boundary layer (PBL) heights, near-surface winds, and precipitation type. Large systematic temperature errors from the Weather Research and Forecasting (WRF) Model are

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

Liu 2017 ; Bao et al. 2018 ), though they have only been applied to flows with neutral stability profiles, which is not the case here. Additionally, Bao et al. (2016) showed that at the coarser resolutions used here, current IBM implementations based on similarity theory perform similarly to those using a no-slip condition, with reasons varying based on the specifics of the implementation. Thus, a no-slip boundary is used in the present study to simplify validation as a result of the strict

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Hailing Zhang, Zhaoxia Pu, and Xuebo Zhang

1. Introduction The near-surface atmosphere, namely, the bottom 10% of the atmospheric boundary layer, is unique due to its direct interaction with the earth's surface ( Stull 1988 ). For instance, near-surface temperature is characterized by diurnal variation, with a maximum at local afternoon and a minimum at local midnight. This is very different from the free atmosphere in which temperature shows little diurnal variation. Turbulence causes the wind field in the atmospheric boundary layer

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

density current in the lee of the barrier ( Epifanio and Rotunno 2005 ). If the position of this boundary fluctuates, LTFs may be produced at the surface. Because of their small spatial scale and short temporal duration, LTFs present a challenge for numerical models. Models may not resolve the phenomena that contribute to LTFs or may have difficulty parameterizing those phenomena. Strong CAPs, an important component of LTFs, are particularly difficult to simulate and often display excessive vertical

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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

Comprehensive, multiscale, and multidisciplinary observations allow scientists to discover novel flow physics, address current deficiencies of predictive models, and improve weather prediction in mountainous terrain. Through woods and mountain passes the winds, like anthems, roll. —Henry Wadsworth Longfellow For centuries, humans have been both fascinated and awed by mountain weather, and its intriguing aberrancy continues to baffle weather forecasters. For instance, a clear morning on a

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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

(e.g., Doran et al. 1990 ; Whiteman and Zhong 2008 ), or with other flows such as synoptic winds (e.g., Barr and Orgill 1989 ) and other complex-terrain phenomena such as valley cold pools (e.g., Catalano and Cenedese 2010 ; Mahrt et al. 2010 ). In this paper, we describe the nocturnal boundary layer development during a quiescent spring night on a low-angle slope at the foot of a steep desert mountain that borders a large valley ( Fig. 1a ). The data were taken on the lower east sidewall of

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Feimin Zhang and Zhaoxia Pu

formation by changing the surface heat and moisture budget. Results from Steeneveld et al. (2015) showed that boundary layer formulation is critical for forecasting fog onset. Recent studies also found that inaccurate forecasts of near-surface atmospheric conditions are associated mostly with the failure of fog prediction in many cases ( Pu et al. 2016 ; Chachere and Pu 2019 ). Despite these various factors that contribute to the inaccurate numerical prediction of fog events, different processes

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

al. 1997 ), the Dudhia shortwave radiation parameterization ( Dudhia 1989 ), the Noah LSM ( Chen and Dudhia 2001 ), the Yonsei University PBL parameterization ( Hong et al. 2006 ), explicit sixth-order numerical diffusion ( Knievel et al. 2007 ), and the Kain–Fritsch cumulus parameterization ( Kain 2004 ). We used 0.5° Global Forecast System (GFS) analyses for initial atmospheric and land surface analyses, as well as lateral boundary conditions, as is done in the operational 4DWX-DPG system

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