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Examination of errors in near-surface temperature and wind from WRF numerical simulations in regions of complex terrain

机译:通过WRF数值模拟在复杂地形区域中检查近地表温度和风的误差

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The performance of an advanced research version of the Weather Research and Forecasting Model (WRF) in predicting near-surface atmospheric temperature and wind conditions under various terrain and weather regimes is examined. Verification of 2-m temperature and 10-m wind speed and direction against surface Mesonet observations is conducted. Three individual events under strong synoptic forcings (i.e., a frontal system, a low-level jet, and a persistent inversion) are first evaluated. It is found that theWRFmodel is able to reproduce these weather phenomena reasonably well. Forecasts of near-surface variables in flat terrain generally agree well with observations, but errors also occur, depending on the predictability of the loweratmospheric boundary layer. In complex terrain, forecasts not only suffer from the model's inability to reproduce accurate atmospheric conditions in the lower atmosphere but also struggle with representative issues due to mismatches between the model and the actual terrain. In addition, surface forecasts at finer resolutions do not always outperform those at coarser resolutions. Increasing the vertical resolution may not help predict the near-surface variables, although it does improve the forecasts of the structure of mesoscale weather phenomena. A statistical analysis is also performed for 120 forecasts during a 1-month period to further investigate forecast error characteristics in complex terrain. Results illustrate that forecast errors in nearsurface variables depend strongly on the diurnal variation in surface conditions, especially when synoptic forcing is weak. Under strong synoptic forcing, the diurnal patterns in the errors break down, while the flowdependent errors are clearly shown.
机译:研究了天气研究和预测模型(WRF)的高级研究版本在各种地形和天气状况下预测近地表大气温度和风况的性能。对照地面Mesonet观测值验证了2米温度和10米风速和风向。首先评估在强天气强迫下的三个独立事件(即额叶系统,低空急流和持续倒转)。发现WRF模型能够很好地再现这些天气现象。在平坦地形中对近地表变量的预测通常与观测结果非常吻合,但根据较低大气边界层的可预测性,也会发生误差。在复杂的地形中,预测不仅会遭受模型无法在低层大气中准确再现大气条件的困扰,而且还会因模型与实际地形之间的不匹配而遇到具有代表性的问题。此外,在较高分辨率下的地表预测并不总是优于在较高分辨率下的地表预测。垂直分辨率的提高虽然可以改善对中尺度天气现象结构的预测,但可能无法帮助预测近地表变量。在1个月内还对120个预测进行了统计分析,以进一步调查复杂地形中的预测误差特征。结果表明,近地表变量的预报误差在很大程度上取决于地表条件的日变化,特别是在天气强迫弱的情况下。在强天气推动下,误差的昼夜模式分解,而流量相关的误差清晰显示。

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