Ensemble forecasting
Ensemble forecasting
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DOI：
10.1016/j.jcp.2007.02.014
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发表时间：
2008-03-20
影响因子：
4.1
通讯作者：
Palmer, T. N.
中科院分区：
文献类型：
--
作者：
Leutbecher, M.;Palmer, T. N.
数值天气预报模式和大气本身都可以看作是一个演化敏感地依赖于初始条件的非线性动力系统。对当前状态的估计是不准确的，而数字模型有不足之处，这导致预测误差随着预测提前期的增加而增加。误差的增长取决于流程本身。集合预报旨在量化这种与流量相关的预报不确定性。讨论了天气预报中不确定性的来源。然后，对概率预测的评估及其与单一预测的有用性进行了概述。然后，回顾了集合预报中不确定性的表示，重点讨论了初始条件扰动。对欧洲中期天气预报中心(ECMWF)的集合预报系统(EPS)产生初始条件扰动的方法进行了详细的描述，以补充审查工作。这些扰动是基于描述有限时间间隔上的线性化动力学的算子的奇异值分解的前导部分。随着非线性预报模式解的线性化，扰动是与气流有关的。对于中纬度大尺度气流，评估了当前ECMWF集合预报系统在多大程度上能够预测不确定性与气流有关的变化。(C)2007 Elsevier Inc.保留所有权利。
Numerical weather prediction models as well as the atmosphere itself can be viewed as nonlinear dynamical systems in which the evolution depends sensitively on the initial conditions. The fact that estimates of the current state are inaccurate and that numerical models have inadequacies, leads to forecast errors that grow with increasing forecast lead time. The growth of errors depends on the flow itself. Ensemble forecasting aims at quantifying this flow-dependent forecast uncertainty.The sources of uncertainty in weather forecasting are discussed. Then, an overview is given on evaluating probabilistic forecasts and their usefulness compared with single forecasts. Thereafter, the representation of uncertainties in ensemble forecasts is reviewed with an emphasis on the initial condition perturbations. The review is complemented by a detailed description of the methodology to generate initial condition perturbations of the Ensemble Prediction System (EPS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). These perturbations are based on the leading part of the singular value decomposition of the operator describing the linearised dynamics over a finite time interval. The perturbations are flow-dependent as the linearisation is performed with respect to a solution of the nonlinear forecast model.The extent to which the current ECMWF ensemble prediction system is capable of predicting flow-dependent variations in uncertainty is assessed for the large-scale flow in mid-latitudes. (c) 2007 Elsevier Inc. All rights reserved.