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

Daniels et al. (2016) . This limitation restricts the use of models such as WRF in regions of steep and/or complex terrain where topographic effects on radiation are most important. The immersed boundary method (IBM), which uses a nonconforming grid and represents the topography by imposing boundary conditions along an immersed terrain surface, provides an alternative to terrain-following vertical coordinates. IBM reduces numerical errors related to the terrain slope, thus extending the range of

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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

the atmosphere above the slope that is not available for other IOP nights. The nocturnal boundary layer development started with the evening-transition period, which is characterized by strong surface cooling and the development of a surface-based inversion, as well as by the transition from daytime upslope/up-valley winds to nighttime downslope/down-valley winds. The evening transition was followed by a period of almost undisturbed boundary layer conditions on the sidewall until approximately

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Hailing Zhang, Zhaoxia Pu, and Xuebo Zhang

strong inversion layer extended from the surface up to 2000 m during this time. b. A brief description of numerical simulations Numerical experiments are conducted to simulate the aforementioned cases using the ARW with one-way nested domains. The initial and boundary conditions are derived from the National Centers for Environmental Prediction's (NCEP's) Northern American Mesoscale (NAM) model analysis by WRF preprocessing. A topography dataset at 30 arc-second (about 1000 m) resolution and an

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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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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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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

Notre Dame (UND; lead); University of California, Berkeley (UCB); Naval Postgraduate School (NPS); University of Utah (UU); and University of Virginia (UVA). MATERHORN consists of four components working symbiotically: The modeling component (MATERHORN-M) investigates predictability at the mesoscale, in particular, sensitivity (error growth) to initial conditions at various lead times, dependence on boundary conditions and input background properties, as well as merits of different data

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

). Conditions with ≫ 1 and large values of β typically result in blocked flow at low levels. Situations with values of ≫ 1 and smaller β are likely to result in flow splitting or the formation of an orographic wake in the lee of the barrier. Orographic wakes are potentially conducive to LTF development. During an orographic wake, potentially warmer air descending in the lee of terrain and relatively cold, stable air flowing around the terrain can produce a quasi-stationary boundary that resembles a

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

nature run, the WRF was initialized at 0000 UTC 19 January 2009 from the North American Regional Reanalysis (NARR), which also provided lateral boundary conditions. Soil temperature and moisture were reset every 3 h to the NARR, preventing land surface drift during the 10-day nature run. Synthetic observations were produced every 3 h; observation locations and physical quantities were identical to the actual radiosonde observations available in the National Centers for Environmental Prediction

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

; Kilpelainen et al. 2012 ; Holtslag et al. 2013 ; Ngan et al. 2013 ). These errors are especially prevalent in high-resolution modeling systems (<5-km grid spacing) over many regions of the western United States (e.g., Mass et al. 2002 ; Cheng and Steenburgh 2005 ; Hart et al. 2005 ; Zhang et al. 2013 ). By influencing low-level stratification, boundary layer depth and mixing, thermally driven flows, and convective initiation, NST forecast errors ultimately affect the prediction of precipitation

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