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

Terrain Atmospheric Modeling and Observations (MATERHORN) autumn 2012 field campaign, held at DPG from 25 September to 25 October 2012. We refer to September–October of 2011 and September–October of 2012 as the pre-MATERHORN and MATERHORN periods, respectively. The source of the forecasts is the U.S. Army Test and Evaluation Command Four-Dimensional Weather System (4DWX), developed by the National Center for Atmospheric Research (NCAR). We used two versions of the 4DWX run for DPG (4DWX-DPG). In 2011

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

higher than at 1400 LST, consistent with poorer model performance overnight and in the early-morning hours. With a stronger 2-m temperature contrast between the desert shrub and playa, SM-Albedo produces a stronger off-playa breeze at 1400 LST than does Control (cf. Figs. 12a and 12b ). SM-Albedo winds appear close to SAMS observations along the playa boundary in eastern DPG but are stronger than observations in southeastern DPG. Wind speed BEs improve and increase from −0.27 to 0.12 m s −1 in SM

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

) mission, which provides remotely sensed soil moisture data in 9-km pixels, much finer than previous satellite-based soil moisture estimates, also offers significant potential to improve soil moisture analyses worldwide. Acknowledgments This research was funded by Office of Naval Research Award N00014-11-1-0709, the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program, and by the U.S. Army Test and Evaluation Command (ATEC) through an interagency agreement with the National

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Hailing Zhang, Zhaoxia Pu, and Xuebo Zhang

Verification is first conducted to evaluate the accuracy of the numerical simulation of each synoptic event. Simulation results are compared with available observations and analyses. 2) Verification of near-surface atmospheric conditions The major emphasis of this study is on characterizing errors in the near-surface atmosphere. To quantify these errors, we use surface Mesonet observations ( Horel et al. 2002 ) to verify the model's performance in terms of the near-surface variables, namely, 2-m

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Raquel Lorente-Plazas and Joshua P. Hacker

the system. The root-mean-square error (RMSE), as well as its decomposed bias and error standard deviation (STD) components, assesses the quality of the assimilation experiments. The errors are quantified for the background/prior to evaluate how the assimilation is affected by the biases and bias estimation. RMSE of the parameter estimates (cf. the true observation bias or model forcing bias) are also useful to assess whether the biases are properly attributed to the model or the observations, and

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Feimin Zhang and Zhaoxia Pu

weather prediction (NWP; e.g., Golding 1993 ; Meyer and Rao 1999 ; Gultepe et al. 2016 ; Pu et al. 2016 ; Pu 2017 ). Zhou et al. (2012) evaluated the performance of low visibility/fog predictions over North America using the National Centers for Environmental Prediction (NCEP) operational forecast models. Results showed that the accuracy of visibility/fog forecasts from these models was poor in comparison to the accuracy of operational precipitation forecasts from the same models. Previous

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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

overshadowed by valley and secondary flows. This suggested reorientation of combos, thus circumventing a costly misperception. During campaigns, real-time WRF forecasts were made at high resolution (∼1-km horizontal grid intervals), initialized four times per day (at 0000, 0600, 1800, and 2400 UTC). After the field programs, the forecasts were evaluated against observations, which has been particularly helpful in model performance evaluation and devising improvements ( Pu et al. 2014 ). A number of studies

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

method in the Weather Research and Forecasting Model . Mon. Wea. Rev. , 146 , 2781 – 2797 , https://doi.org/10.1175/MWR-D-18-0067.1 . 10.1175/MWR-D-18-0067.1 Chen , F. , and Coauthors , 2007 : Description and evaluation of the characteristics of the NCAR high-resolution land data assimilation system . J. Appl. Meteor. Climatol. , 46 , 694 – 713 , https://doi.org/10.1175/JAM2463.1 . 10.1175/JAM2463.1 Chester , S. , C. Meneveau , and M. B. Parlange , 2007 : Modeling turbulent flow

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