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Thomas Hengstebeck, Kathrin Wapler, Dirk Heizenreder, and Paul Joe

measurements. However, problems remain in composite border regions (the edge of the radar network domain). Rotation tracks are better defined in the central region of the composite and not too close to any of the radar sites, where vertical wind shear may cause high azimuthal shear signals (“hot spots”) that are not related to rotation. The forecaster must be aware of these limitations to carefully draw decisions in operational warning situations. 6. Case studies In the following subsections, two case

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Ana P. Barros and Kun Tao

. 2000 , 2006 ; among others). For hydrological applications and water resources management, the ability to estimate the spatial location of rainfall correctly with regard to the river basin boundaries—that is, placing rainfall in the catchment or watershed where it occurs—is essential to close the water budget. In operational hydrology, especially in the case of flood forecasting, the requirement is especially important for heavy rainfall. Whereas rainfall intensity, timing, and duration are also

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Qin Xu, Kang Nai, Li Wei, Pengfei Zhang, Shun Liu, and David Parrish

not ensured to be free of false dealiasing because it tends to retain as much of the original data coverage as possible. d. High data quality standard required by radar data assimilation Radial velocity observations from the operational WSR-88D have much higher spatial and temporal resolutions than the background resolutions provided by Weather Research and Forecasting (WRF) Nonhydrostatic Mesoscale Model (NMM) predictions for the regional data assimilation system at NCEP. Because of this, and

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Paul J. Neiman, Daniel J. Gottas, Allen B. White, William R. Schneider, and David R. Bright

-flow events in winter and the occurrence of freezing rain and/or snow in the normally maritime environment present in the metropolitan area encompassing Portland, Oregon, and Vancouver, Washington. The development of this data product was motivated by an operational forecasting challenge specific to the Portland WFO and the Columbia River Gorge. Its application to the forecasting process is twofold. First, having all of the relevant gap-flow-related observations collectively depicted in a single graphic

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Yuan Jiang and Qin Xu

, but their applications are often confronted with difficulties caused by the absence of any reliable reference velocity and by the lack of a correctly dealiased velocity to start the checking. The Nyquist velocities used by operational weather radars in the United States are usually in the range between 20 and 36 m s −1 , so radial velocities scanned from a hurricane can easily exceed these Nyquist velocities and become severely aliased. The operationally used dealiasing techniques ( Eilts and

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Matthew J. Hoffman, Takemasa Miyoshi, Thomas W. N. Haine, Kayo Ide, Christopher W. Brown, and Raghu Murtugudde

years, but often using less sophisticated schemes than those in atmospheric science. Many ocean data assimilation efforts, including most of the operational systems, have used some type of optimal interpolation ( Mellor and Ezer 1991 ; Fan et al. 2004 ). In the Chesapeake Bay, 2 months of salinity data from a ship-towed vehicle was assimilated by Xu et al. (2002) using a nudging method. While some improvements were seen, the nudging method introduced errors by disrupting the hydrodynamic balance

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Pengfei Zhang, Shun Liu, and Qin Xu

-precision level II wind data from the 120 National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) radars into their operational numerical weather forecast (NWP) systems. A simple QC has been developed for level II radar data assimilation ( Xu et al. 2004 ; Gu et al. 2001 ) with the U.S. Navy’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS; Hodur 1997 ), but it deals with the velocity aliasing problem only. Although its dealiasing capability has been improved recently

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Lisa Milani, Mark S. Kulie, Daniele Casella, Pierre E. Kirstetter, Giulia Panegrossi, Veljko Petkovic, Sarah E. Ringerud, Jean-François Rysman, Paolo Sanò, Nai-Yu Wang, Yalei You, and Gail Skofronick-Jackson

waters, coastlines, and sea ice edge. These classes come from a cluster analysis, purely empirical self-grouping of emissivity characteristics ( Prigent et al. 2006 ). The TPW and T2m parameters are obtained from the Global Atmospheric Analysis (GANAL; JMA 2000 ) and the European Centre for Medium-Range Weather Forecasts ( Dee et al. 2011 ) reanalysis datasets for the operational and the climatological GPROF outputs, respectively. For this study, the 1C-R-GMI product (TBs) and the climatological 2A

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Jinfeng Ding, Xiao-Yong Zhuge, Yuan Wang, and Anyuan Xiong

of the speed and direction increases (decreases) with the increases (decreases) in temperature difference. This phenomenon recurs for the samples within other pressure altitude ranges (not shown). The relationship between temperature and wind makes AMDAR reports different from conventional meteorological observations and should be duly noted during operational forecasting and assimilation. Fig . 7. The RMSE of speed (dot) and directions (circle) vs temperature difference. The solid line and the

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Xin Zhang, Xiang-Yu Huang, and Ning Pan

1. Introduction During the past two decades, the use of the adjoint technique in meteorology and oceanography rapidly increased. The adjoint model is a powerful tool in many applications, such as data assimilation, parameter estimation, and sensitivity analysis ( Errico and Vukicevic 1992 ; Errico 1997 ; Rabier et al. 1996 ; Langland et al. 1999 ; Li et al. 1999 ; Xiao et al. 2002 , 2008 ; Kleist and Morgan 2005a , b ). The Weather Research and Forecasting (WRF) modeling system

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