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A. B. White, M. L. Anderson, M. D. Dettinger, F. M. Ralph, A. Hinojosa, D. R. Cayan, R. K. Hartman, D. W. Reynolds, L. E. Johnson, T. L. Schneider, R. Cifelli, Z. Toth, S. I. Gutman, C. W. King, F. Gehrke, P. E. Johnston, C. Walls, D. Mann, D. J. Gottas, and T. Coleman

goals: 1) to install a twenty-first-century observing system to help address California’s water and emergency management needs, 2) to provide a state-of-the-art numerical weather forecast model ensemble with a high-resolution nest over California, and 3) to develop decision support tools for weather and river forecasters and water managers. This project is part of the California Department of Water Resources (CA-DWR) Enhanced Flood Response and Emergency Preparedness Program. The HMT-Legacy project

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Laura Bianco, Daniel Gottas, and James M. Wilczak

et al. 1984 ) show very large northwesterly values at nighttime, largely caused by the migrating birds, as revealed in Fig. 2 . Assimilating data such as these into numerical weather prediction models can result in erroneous forecasts, and therefore it is important to remove the contamination, when present. Fig . 2. The 915-MHz wind profiler time–height cross sections of hourly winds computed by a standard consensus procedure for 9 Oct 2010 at Chico. In Fig. 3 we present the same data as those

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Qing Yang, Larry K. Berg, Mikhail Pekour, Jerome D. Fast, Rob K. Newsom, Mark Stoelinga, and Catherine Finley

1. Introduction One of the challenges with wind-power forecasts is the accurate prediction of ramps, which are rapid increases or decreases (for the sake of brevity hereinafter referred to as up-ramps and down-ramps, respectively) in generated power. Wind ramps pose challenges to power-system operators for maintaining grid reliability ( Wan 2011 ), and large wind ramps also are important in managing the electric market ( Cutler et al. 2007 ). Ramps with longer durations (from 1 h to several

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S.-E. Gryning, E. Batchvarova, and R. Floors

discrepancies between measurements and model counterparts that are due to local terrain effects ( Hahmann et al. 2010 ; Boilley and Mahfouf 2012 ). Observed wind speeds at greater heights can show large differences when using different reanalysis data to reinitialize the Weather Research and Forecasting (WRF) model ( Floors et al. 2013 ). Verification of data assimilation techniques is now possible with the advent of new types of instruments, such as wind Doppler lidars, that observe winds with high

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Valery M. Melnikov, Richard J. Doviak, Dusan S. Zrnić, and David J. Stensrud

typically occur at the top of the convective boundary layer (CBL) (e.g., Wyngaard and LeMone 1980 ; Fairall 1991 ), where there is strong mixing of moist and dry air. Monitoring of the CBL is very important for forecasting the timing and likelihood of storm initiation. Heinselman et al. (2009) and Elmore et al. (2012) show that if the reflectivity field obtained with the Weather Surveillance Radar-1988 Doppler (WSR-88D) in “clear air” exhibits an elevated maximum, its height correlates well with

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Elías Lau, Scott McLaughlin, Frank Pratte, Bob Weber, David Merritt, Maikel Wise, Gary Zimmerman, Matthew James, and Megan Sloan

height ( Hashiguchi et al. 1995 ; Cohn and Angevine 2000 ), cold front characterization ( Browning et al. 1998 ), heat and momentum fluxes ( Angevine et al. 1993 ), classification of precipitating clouds ( Williams et al. 1995 ), and rainfall drop size distributions ( Schafer et al. 2002 ). Operational applications include weather forecasting, air quality forecasting for urban areas, and wind shear determination at airports. Typical BL RWPs currently deployed utilize antenna arrays, either several

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