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

cloudy during MATERHORN-Spring. 1) Measurement of SEB components Sensible heat flux H was calculated at 2 m AGL from sonic anemometer and sonic temperature measurements, and LE was calculated at 10 m from infrared gas analyzer measurements. The fluxes were calculated using 5-min averaging times and were quality controlled using the Utah Turbulence in Environmental Studies processing and analysis code (UTESpac; Jensen et al. 2016 ). The 2-m H and 10-m LE were treated as proxies for surface fluxes

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

synoptically with limited precipitation (8.7 mm at the DPG National Weather Service Cooperative Observer site). The 4DWX-MATERHORN configuration is the same as the 2012 version of 4DWX-DPG except for use of 1) WRF v3.5.1, 2) updated data assimilation with the observation quality control done inside the model, 3) biweekly cold starts on Tuesdays and Fridays at 0500 UTC, and 4) climatological Great Salt Lake temperatures obtained from Steenburgh et al. (2000) . Potentially important for the interpretation

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Hailing Zhang, Zhaoxia Pu, and Xuebo Zhang

temperature and 10-m wind speed and direction. According to Horel et al. (2002) , quality control algorithms and data monitoring programs are performed for all available data. The quality-controlled data are then made available hourly with quality flags. In this study, only those observations with a quality flag of “OK” (the highest quality) are used for verification. Since there is case-by-case variation in near-surface atmospheric conditions due to various synoptic systems and terrain, verification of

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Joshua P. Hacker and Lili Lei

is smaller in the data assimilation and because the higher quality observations can result in a larger analysis increment. Because they are now the same order of magnitude, the behavior of the predicted response to perturbations from direct perturbation and assimilation is easier to compare. Fig . 2. Slow-scale perfect-model ensemble-mean analysis mean squared error (blue) and ensemble spread (red) at an arbitrary grid point. Fig . 3. As in Figs. 1e and 1f , but with observation error variance

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Raquel Lorente-Plazas and Joshua P. Hacker

biases together ( Pauwels et al. 2013 ; Eyre 2016 ), and investigated the ability to optimize the data assimilation while considering both sources of error. A wide variety of algorithms can adaptively estimate bias as part of the assimilation. The general approach is to include parameters that represent the biases in the assimilation system, and augment the state vector (or control vector) with the parameters ( Friedland 1969 ). The parameters can represent biases in a model and/or observations, 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

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

number of stations used for verification varied among the three case studies. Most stations are clustered along the Wasatch Front, and no stations are located over far northwestern Utah. The vast majority of these stations are either over shrubland or urban land cover, except for the nine playa stations, which are all over playa land cover. Although no formal quality control was performed on any of the observational datasets, missing and obviously erroneous observations were removed. d. MATERHORN

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

sensible heat flux are available for four levels on ES2: 0.5, 4, 10, and 20 m AGL. All data were processed using the Utah Turbulence in Environmental Studies Processing and Analysis Code ( Jensen et al. 2016 ). Data were quality controlled following Vickers and Mahrt (1997) and a two-sector planar fit, divided between upslope and downslope winds, was applied ( Wilczak et al. 2001 ). A 5-min averaging period was used to maintain high temporal resolution for the purpose of this study. The ES2 tower is

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