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首页> 外文期刊>Quarterly Journal of the Royal Meteorological Society >Processes governing the amplification of ensemble spread in a medium‐range forecast with large forecast uncertainty
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Processes governing the amplification of ensemble spread in a medium‐range forecast with large forecast uncertainty

机译:管理集团扩增的流程在大型预测不确定性的中等预测中传播

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This study provides a process‐based perspective on the amplification of forecast uncertainty and forecast errors in ensemble forecasts. A case from the North Atlantic Waveguide and Downstream Impact Experiment that exhibits large forecast uncertaintyis analysed. Two aspects of the ensemble behaviour are considered: (a) the mean divergence of the ensemble members, indicating the general amplification of forecast uncertainty, and (b) the divergence of the best and worst members, indicating extremes in possible error‐growth scenarios. To analyse the amplification of forecast uncertainty, a tendency equation for the ensemble variance of potential vorticity (PV) is derived and partitioned into the contributions from individual processes. The amplification of PV variance is, on average for the midlatitudes of the Northern Hemisphere, dominated by near‐tropopause dynamics. Locally, however, other processes can dominate the variance amplification, for example, in the region where tropical storm Karl interacts with the Rossby‐wave pattern during extratropical transition. In this region, the variance amplification is dominated by upper‐tropospheric divergence and tropospheric–deep interaction and is thereby mostly related to (moist baroclinic) cyclone development. The differences between the error growth in the best and worst ensemble members can, to a large part, be attributed to differences in the representation of cut‐off evolution around 3days, which subsequently amplifies substantially in thehighly nonlinear region of the Rossby‐wave pattern until 5days. In terms of the processes, the differences in error growth are dominated by differences in the error growth by near‐tropopause dynamics. The approach presented provides flow‐dependent insight into the dynamics of forecast uncertainty and forecast errors and helps to understand better the different contributions of specific weather systems to the medium‐range amplification of ensemble spread.
机译:本研究提供了基于过程的视角,可以在集合预测中的预测不确定性和预测误差的放大。北大西洋波导和下游影响实验的案例分析了大型预测不确定性。集合行为的两个方面被认为是:(a)集合成员的平均分歧,表明预测不确定性的一般放大,以及(b)最佳和最差成员的分歧,表明极端在可能的误差增长场景中。为了分析预测不确定性的放大,导出潜在涡度(PV)的集合方差的趋势方程,并将其划分为单个过程的贡献。 PV方差的扩增平均为北半球的中期,由近代近代动态主导。然而,当地,其他过程可以在例如热带风暴卡尔在卓越转变期间与Rossby波图案相互作用的区域中的方差放大。在该地区,方差扩增是由上层散发性和对流层深度相互作用的,从而主要与(湿氨基核)旋风发育有关。最佳和最差集合构件的误差生长之间的差异可以归因于3天的截止演化的表示的差异,这随后在rossby波模式的高度非线性区域中基本上放大到5天。就该过程而言,误差生长的差异是通过近代动态误差增长的差异的主导。该方法提供了进入预测不确定性和预测错误的动态的流动依赖性洞察力,并有助于了解特定天气系统对集合扩散的中距离放大的更好的不同贡献。

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