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Evaluation of Atmospheric River Predictions by the WRF Model Using Aircraft and Regional Mesonet Observations of Orographic Precipitation and Its Forcing

机译:利用飞机和地区思科观测的WRF模型评估WRF模型的大气河预测及其迫使

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Accurate forecasts of precipitation during landfalling atmospheric rivers (ARs) are critical because ARs play a large role in water supply and flooding for many regions. In this study, we have used hundreds of observations to verify global and regional model forecasts of atmospheric rivers making landfall in Northern California and offshore in the midlatitude northeast Pacific Ocean. We have characterized forecast error and the predictability limit in AR water vapor transport, static stability, onshore precipitation, and standard atmospheric fields. Analysis is also presented that apportions the role of orographic forcing and precipitation response in driving errors in forecast precipitation after AR landfall. It is found that the global model and the higher-resolution regional model reach their predictability limit in forecasting the atmospheric state during ARs at similar lead times, and both present similar and important errors in low-level water vapor flux, moist-static stability, and precipitation. However, the relative contribution of forcing and response to the incurred precipitation error is very different in the two models. It can be demonstrated using the analysis presented herein that improving water vapor transport accuracy can significantly reduce regional model precipitation errors during ARs, while the same cannot be demonstrated for the global model.
机译:在登陆大气河流(ARS)期间的准确降水预测至关重要,因为ARS在许多地区的供水和洪水中发挥着大量作用。在这项研究中,我们使用了数百个观察来验证大气河流在东北太平洋中北北部加利福尼亚州和离岸的全球和区域模型预测。我们具有特征的预测误差和AR水蒸气运输,静稳定性,陆上降水和标准大气领域的可预测性极限。还提出了分析,分析了在AR登陆后预测降水中的驾驶误差中的风格迫使和降水反应的作用。结果发现,全球模型和更高分辨率的区域模型达到预测在类似的交货时间内的大气状态下的可预测性极限,并且在低水平的水蒸气通量,潮湿的稳定性中,这两个都存在类似和重要的误差,和降水。然而,两种模型中强制和响应所产生的降水误差的相对贡献。可以使用本文提出的分析证明,提高水蒸气传输精度可以显着降低ARS期间的区域模型降水误差,而全球模型也无法对此进行说明。

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