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首页> 外文期刊>Journal of Applied Meteorology and Climatology >Evaluating a Hybrid Prognostic–Diagnostic Model That Improves Wind Forecast Resolution in Complex Coastal Topography
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Evaluating a Hybrid Prognostic–Diagnostic Model That Improves Wind Forecast Resolution in Complex Coastal Topography

机译:评估杂交预后诊断模型,从而改善复杂的沿海地形中的风预测分辨率

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摘要

The results from a hybrid approach that combines the forecasts of a mesoscale model with a diagnostic wind model to produce high-resolution wind forecasts in complex coastal orography are evaluated. The simple diagnostic wind model [Winds on CriticalStreamline Surfaces (WOCSS)] was driven with forecasts (on a 9-km grid) from the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) to obtain detailed near-surface wind forecasts with 3-km horizontal spacing. Forecasts were produced by this hybrid model for four cold-season cases—two frontal and two nonfrontal—over the central California coastal region. They were compared with 3-km forecasts from the innermost COAMPS full physics model nest and with winds observed at 35 surface sites scattered throughout the study domain. The evaluation sought to determine the conditions for which the hybrid approach performs well and those for which it does not. The performance (in terms of bias and root-mean-square error) was evaluated 1) when there were and were not fronts and 2) for the early (6–18 h) and late (21–36 h) periods of the mesoscale model forecasts. The geographic distribution of performance was also examined to see if forecasts were affected by mountains and oceans. The hybrid approachperformed best during stable, nonfrontal conditions. There were no clearly defined geographic effects on hybrid performance. The computation requirements of the full physics mesoscale model nested down to 3 km are substantially greater than those of thehybrid approach. Suggestions are given for further improvements.
机译:分析了与诊断风模型的混合方法的结果,以便在复杂的沿海地区产生高分辨率风预测的诊断风模型。简单的诊断风模型[icriticleStreamline(WOCS)上的风力(Quocsstreamline(Wocs)]由来自耦合的海洋气氛Messcale预测系统(助塑料)的预测(在9公里网格上)驱动,以获得3公里的详细近表面风预测水平间距。这款混合模型为四个寒冷季节案例 - 两个非正面和加州中央沿海地区的两次非公共区域产生了预测。将它们与3公里的预期与最内涂层全部物理模型巢相比,并且在散落在整个研究结构域的35个表面点观察到风。评估试图确定混合方法的表现良好的条件以及它没有的条件。当初期(6-18小时)和Mesoscale的早期(21-36小时)和后期(21-36小时)和后期(21-36小时)和后期(21-36小时)时,评估表现(偏见和根均方误差)1)模型预测。还研究了绩效的地理分布,看看是否受到山脉和海洋的预测。在稳定,非野蛮条件下,杂交地接近最佳。对混合性能没有明确定义的地理效应。嵌套在3km的完整物理Mesoscale模型的计算要求基本上大于yhybrid方法。提供进一步改进的建议。

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