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Feimin Zhang and Zhaoxia Pu

1. Introduction Fog is a near-surface atmospheric phenomenon that has a significant influence on human activities such as transportation, aviation, and communication. The financial and human losses related to fog and low visibility are comparable to those from other weather events such as tornadoes or, in some situations, even hurricanes ( Gultepe et al. 2007 ). Therefore, accurate fog prediction is of great importance, yet it remains a challenge, despite significant advances in numerical

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

1. Introduction Fog events in the Salt Lake basin in Utah, with impacts on aviation operations at the Salt Lake City International Airport (KSLC), arise in a range of flow scenarios. Typically, weak synoptic forcing and nonlinear water phase changes present challenges to numerical weather prediction (NWP) models when fog is possible. Because interactions between the land–water surface and the lower atmosphere can strongly modulate fog production and dissipation, near-surface shelter and

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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

instrumented UAV, sensors for moisture and fog measurements, and a combined hot-film/sonic anemometer system for probing turbulence down to Kolmogorov scales. Advanced data retrieval and processing algorithms are also attempted. The parameterization component (MATERHORN-P) develops high-fidelity physics-based fundamental (quantitative) relationships for complex-terrain processes, which are implemented in mesoscale models followed by model evaluations. The Granite Mountain Atmospheric Science Testbed of the

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Joshua P. Hacker and Lili Lei

. Around the same time, Hakim and Torn (2008) and Torn and Hakim (2008) used the regressions underlying ensemble sensitivities to identify dynamic links in evolving weather patterns. Application of adjoint and ensemble sensitivity methods to high-resolution forecast problems (grid spacing less than 5 km) has to this point been sparse. One example is Wile et al. (2014, manuscript submitted to Wea. Forecasting , hereafter WHC) who applied ensemble sensitivities to a weakly forced fog case over the

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

(amount and type), fog and clouds, air quality, and surface and boundary layer winds (e.g., Hanna and Yang 2001 ; Rife et al. 2002 ; Marshall et al. 2003 ; Holt et al. 2006 ). There have been numerous hypotheses concerning the sources of these NST forecast errors ranging from inadequate horizontal or vertical resolution to the inaccurate initialization and parameterization of boundary layer and land surface characteristics and processes (e.g., Hanna and Yang 2001 ; Mass et al. 2002 ; Marshall

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