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Forecast Divergences of a Global Wave Model

机译:预测整体波动模型的差异

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One of the main limitations to current wave data assimilation systems is the lack of an accurate representation of the structure of the background errors. One method that may be used to determine background errors is the "NMC method." This method examines the forecast divergence component of the background error growth by considering differences between forecasts of different ranges valid at the same time. In this paper, the NMC method is applied to global forecasts of significant wave height (SWH) and surface wind speed (U10). It is found that the isotropic correlation length scale of the SWH forecast divergence (L_(SWH)) has considerable geographical variability, with the longest scales just to the south of the equator in the eastern Pacific Ocean, and the shortest scales at high latitudes. The isotropic correlation length scale of the U10 forecast divergence (L_(U10)) has a similar distribution with a stronger latitudinal dependence. It is found that both L_(SWH) and L_(U10) increase as the forecast period increases. The increase in L_(SWH) is partly due to L_(U10) also increasing. Another explanation is that errors in the analysis or the short-range SWH forecast propagate forward in time and disperse and their scale becomes larger. It is shown that the forecast divergence component of the background error is strongly anisotropic with the longest scales perpendicular to the likely direction of propagation of swell. In addition, in regions where the swell propagation is seasonal, the forecast divergence component of the background error shows a similar strong seasonal signal. It is suggested that the results of this study provide a lower bound to the description of the total background error in global wave models.
机译:电流数据同化系统的主要限制之一是缺乏对背景误差结构的准确表示。可以用来确定背景误差的一种方法是“ NMC方法”。该方法通过考虑同时有效的不同范围的预测之间的差异,来检查背景误差增长的预测差异成分。本文将NMC方法应用于对重要波高(SWH)和地表风速(U10)的全球预报。研究发现,西南太平洋预报散度(L_(SWH))的各向同性相关长度尺度具有相当大的地理变异性,最长尺度仅在东太平洋赤道以南,而在高纬度地区尺度最短。 U10预测散度(L_(U10))的各向同性相关长度尺度具有相似的分布,纬度依赖性更强。发现L_(SWH)和L_(U10)都随着预测周期的增加而增加。 L_(SWH)的增加部分是由于L_(U10)也增加了。另一个解释是,分析误差或短期SWH预测会随时间向前传播并分散,其规模会变大。结果表明,背景误差的预测散度分量是强烈各向异性的,其最长尺度垂直于膨胀的可能传播方向。另外,在涌浪传播是季节性的地区,背景误差的预测散度分量显示出类似的强季节性信号。建议这项研究的结果为整体波动模型中总背景误差的描述提供了一个下限。

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