A Three-Dimensional Multivariate Modal Analysis of Atmospheric Predictability with Application to the ECMWF Ensemble
A Three-Dimensional Multivariate Modal Analysis of Atmospheric Predictability with Application to the ECMWF Ensemble
复制标题
大气可预测性的三维多元模态分析及其在 ECMWF 系综中的应用
DOI：
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发表时间：
2015
期刊：
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通讯作者：
J. Tribbia
中科院分区：
文献类型：
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作者：
N. Žagar;R. Buizza;J. Tribbia
摘要提出了一种新的集合预测系统分析方法，并将其应用于ECMWF 1个月（2014年12月）的业务集合预报。该方法依赖于将全局三维风场和位势场分解为正态函数。在每12小时至7天的预报范围内，用与平衡和惯性-重力（IG）模式相关的50个集合扩展来量化集合特性。定义了平衡模式和IG模式的集成可靠性，并将每个尺度的集成扩展与控制分析进行比较。模态分析表明，ECMWF系统的初始不确定性在热带大尺度模态中最大，其空间分布与短期预报误差的分布相似。最初，在最小尺度和IG模态的天气范围内，集合扩展增长最多，但总体增长主要是平衡模态扩展的增加。
AbstractA new methodology for the analysis of ensemble prediction systems (ENSs) is presented and applied to 1 month (December 2014) of ECMWF operational ensemble forecasts. The method relies on the decomposition of the global three-dimensional wind and geopotential fields onto the normal-mode functions. The ensemble properties are quantified in terms of the 50-member ensemble spread associated with the balanced and inertio-gravity (IG) modes for forecast ranges every 12 h up to 7 days. Ensemble reliability is defined for the balanced and IG modes comparing the ensemble spread with the control analysis in each scale.Modal analysis shows that initial uncertainties in the ECMWF ENS are largest in the tropical large-scale modes and their spatial distribution is similar to the distribution of the short-range forecast errors. Initially the ensemble spread grows most in the smallest scales and in the synoptic range of the IG modes but the overall growth is dominated by the increase of spread in balanced modes i...