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Edmund Keith Stone and Gary Pearce

between the observation and the background value is then found (o−b value). The model fields used were T + 2-, 3-, 4-h forecasts retrieved from the operational archive. The wind vector was split into u and υ components prior to processing. The o−b values for every observation have been found and then placed into 250-m high-altitude bins. The average (mean, black lines) and root-mean-square (RMS, gray lines) o−b values for all of the observations in each bin were then calculated and plotted in

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Andrew C. Kren and Richard A. Anthes

. Part I: Overview and evaluation . J. Atmos. Oceanic Technol. , https://doi.org/10.1175/JTECH-D-19-0217.1 , in press . Tallapragada , V. , and Coauthors , 2014 : Hurricane Weather Research and Forecasting (HWRF) Model: 2014 scientific documentation. NCAR Development Testbed Center Rep., 105 pp. , http://www.dtcenter.org/HurrWRF/users/docs/scientific_documents/HWRFv3.6a_ScientificDoc.pdf . Wick , G. A. , J. P. Dunion , and J. Walker , 2018a : Sensing hazards with operational unmanned

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Lucas Besson and Jacques Parent du Châtelet

refractivity fields by forecasters provided complementary information that somewhat enhanced the forecasters' capability to analyze the near-surface environment and boosted their confidence in moisture trends. Weather radar networks are often not homogeneous. For instance, the French Application Radar à la Météorologie Infra-Synoptique (ARAMIS) operational network has three different radar frequencies (S, C, and X bands). This heterogeneity is also found with radar age (the oldest having been deployed in

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H. Hersbach and P. A. E. M. Janssen

-step-dependent wave-growth limiter. This limiter was introduced in cycle 4 of WAM, which, in September 1991, became the operational wave forecasting model at the European Centre for Medium-Range Weather Forecasts (ECMWF). For operationally feasible resolutions (Δ x > 50 km), satisfactory results were obtained. In this article, however, it will be shown that for very high resolution—relevant for applications in lakes, for example—the WAM cycle 4 limiter violates the well-known fetch-limited growth law for

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Marshall D. Earle

model parameterselections, run times per real time day of wave forecasting or hindcasting would be in the range between1 and 10 minutes on today's low cost super microcomputers. The units of the equations as given for the modelare both English and metric. Historically, English unitshave been used for operational wave model inputs (e.g.,wind speed in kts, distances in nm) and outputs (e.g.,wave height in ft), while internal equations based onthe scientific literature have used metric units. In

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Aart Overeem, Hylke de Vries, Hassan Al Sakka, Remko Uijlenhoet, and Hidde Leijnse

of a float placed in a reservoir, whereas the manual rain gauges are read by volunteers ( KNMI 2000 ). c. Numerical weather prediction data To allow for distinguishing between rain and other types of precipitation, the forecasted freezing-level height from the numerical weather prediction model HARMONIE-AROME ( Bengtsson et al. 2017 ) cycle 38, as of 3 April 2018 cycle 40, was obtained. HARMONIE-AROME is a nonhydrostatic regional NWP model used operationally at KNMI and various other European

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M. Weissmann, R. Busen, A. Dörnbrack, S. Rahm, and O. Reitebuch

state through advanced observations is a key to improve the forecast skill of NWP models. Our lidar observations showed deviations up to ±15 m s −1 to the operational ECMWF analyses. These differences did not only occur in topographically influenced regions close to Greenland but also above the Atlantic Ocean, as exemplified in this paper with a case study. On one side, the large differences emphasize the importance and need for wind measurements in data-sparse regions. On the other hand, further

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L. Cucurull, B. Navascues, G. Ruffini, P. Elósegui, A. Rius, and J. Vilà

a specific treatment of microphysical processes. At the INM, the HIRLAM system is run at two different horizontal resolutions, 0.5° latitude by 0.5° longitude [operational low-resolution run (OPR)], and 0.2° latitude by 0.2° longitude [high-resolution run (HIR)], both with the same 31 p -sigma, hybrid levels, and vertical resolution. The OPR model domain covers the area between 15.5° and 65.0°N and between −66.5° and 30.0°E. Global forecasts from the European Centre for Medium-Range Forecasts

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Anthony Kirincich

operating wind farm to balance loading of the electrical grid and minimize uncertainty. The potential spatially and temporally dense estimates of surface winds that a calibrated HF radar system could provide to a data-assimilating nested atmospheric model might be sufficient to constrain the hub-height predictions to the accuracies required for both near-term forecasts and resource characterization. Additionally, the direct observations of surface winds themselves would be operationally useful for

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Yicun Zhen, Pierre Tandeo, Stéphanie Leroux, Sammy Metref, Thierry Penduff, and Julien Le Sommer

estimating upper-ocean circulation at scales larger than the first Rossby radius of deformation where the geostrophic balance holds. Satellite altimetry is therefore a key source of information for ocean monitoring systems, and an essential constraint in ocean forecasting systems. In practice, many oceanographic applications of satellite altimetry rely on gridded SSH products rather than on raw along-track SSH data. Satellite altimeters indeed provide SSH measurements along ground tracks, following a

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