以用户为导向的交互式预报系统及应用研究

基于近年来涌现的有关新一代气象预报系统发展的认识,本文提出用户导向的交互式预报系统的概念模型。新系统强调在用户信息分析的基础上,发展从用户出发再回到用户不断自我改善的预报流程。系统组成的关键模块包括：用户端风险决策动态需求分析模块、物理预测模块、用户目标量的降尺度模块,用户端专业耦合模块及用户风险决策模块。文中阐述了系统中各模块间的联系、用户端信息在系统中的反馈作用以及具体的“交互式”方式。以临沂地区水文用户为例,以引发洪涝的降水事件为预报对象,利用TIGGE全球超集合预报,初步构建了一个临沂水文用户导向的可能致洪降水交互式预报系统。这个具备迭代式自我完善功能的新型预报系统包含了汛期随时变化的用户决策信息、由前期影响雨量和当前水文条件决定的可变致洪降水阈值以及一个动态的用户端预报水平和不确定性评估模块。初步结果表明,结合用户端信息的预报优于未考虑用户信息的预报结果,从而更直接地帮助用户进行防汛决策。个例研究也为发展更完整的用户导向预报系统提供了参考。     

Improving multimodel weather forecast of monsoon rain over China using FSU superensemble

In this paper we present the current capabilities for numerical weather prediction of precipitation over China using a suite of ten multimodels and our superensemble based forecasts. Our suite of models includes the operational suite selected by NCARs TIGGE archives for the THORPEX Program. These are: ECMWF, UKMO, JMA, NCEP, CMA, CMC, BOM, MF, KMA and the CPTEC models. The superensemble strategy includes a training and a forecasts phase, for these the periods chosen for this study include the months February through September for the years 2007 and 2008. This paper addresses precipitation forecasts for the medium range i.e. Days 1 to 3 and extending out to Day 10 of forecasts using this suite of global models. For training and forecasts validations we have made use of an advanced TRMM satellite based rainfall product. We make use of standard metrics for forecast validations that include the RMS errors, spatial correlations and the equitable threat scores. The results of skill forecasts of precipitation clearly demonstrate that it is possible to obtain higher skills for precipitation forecasts for Days 1 through 3 of forecasts from the use of the multimodel superensemble as compared to the best model of this suite. Between Days 4 to 10 it is possible to have very high skills from the multimodel superensemble for the RMS error of precipitation. Those skills are shown for a global belt and especially over China. Phenomenologically this product was also found very useful for precipitation forecasts for the Onset of the South China Sea monsoon, the life cycle of the mei-yu rains and post typhoon landfall heavy rains and flood events. The higher skills of the multimodel superensemble make it a very useful product for such real time events.     

THORPEX国际科学研究新进展

2009年9月14—18日,第三届THORPEX国际科学研讨会在美国加州蒙特利市顺利召开。大会就五个专题进行学术交流,分别是全球交互式预报系统,区域活动和交叉研究主题,可预报性和动力过程,资料同化和观测策略,社会和经济效益研究及应用。本文简要总结了参与此次研讨会的各区域、各工作组及与会专家的最新研究成果。从会议的报告来看,THORPEX的进展主要表现在改善高影响天气外场观测活动以及对如何设计全球观测系统的认识、面向TIGGE的集合预报技术的研究等。     

适应性观测与集合变换卡尔曼滤波方法介绍

给出适应性观测理论和集合变换卡尔曼滤波方法及其研究现状的综述。重点介绍了集合变换卡尔曼滤波方法及其相关的一些问题。在数值预报领域,一种新的途径是利用数值预报系统信息在预报时效内确定出某些区域,如果在这些区域进行补充观测,可以最有效地改进预报技能。这种方法被称为适应性或目标观测,所确定的观测区域称为敏感区,敏感区内增加观测后分析质量将得到改善,对后续的预报技能可产生最大的预期影响。目前适应性观测研究已经成为世界气象组织(WMO)组织的THORPEX计划的一个子计划。集合变换卡尔曼滤波(The Ensemble Transform Kalman Filer,简称ETKF)是一种次优的卡尔曼滤波方案,最早是作为一种适应性观测算法提出的,现在还被用于集合预报初始扰动的生成。ETKF方法不仅可以同化观测资料,而且可以估计出观测对预报误差的影响。它与其它集合卡尔曼滤波方案不同之处在于:ETKF利用集合变换和无量纲化的思想求解与观测有关的误差协方差矩阵,可以快速估计出不同附加观测造成的预报误差协方差的减少量,预报误差减少最多的一组观测所对应的区域就是所寻找的敏感区。     

Large-Scale Weather Systems： A Future Research Priority

A brief assessment is provided of both the case against and the case for assigning priority to research on large-scale weather systems (LSWS). The three-fold case against is based upon: the emergence of new overarching themes in environmental science; the fresh emphasis upon other sub-disciplines of the atmospheric science; and the mature state of research and prediction of LSWS. The case for is also supported by three arguments. First is the assertion that LSWS research should not merely be an integral but a major component of future research related to both the new overarching themes and the other sub-disciplines. Second recent major developments in LSWS research, as epitomized by the paradigm shifts in the prediction strategy for LSWS and the emergence of the potential vorticity perspective, testify to the theme’s on-going vibrancy. Third the field’s future development, as exemplified by the new international THORPEX (The Observing System Research and Predictability Experiment) programme, embodies a perceptive dovetailing of intellectually challenging fundamental research with directed application(s) of societal and economic benefit. It is thus inferred that LSWS research, far from being in demise, will feature at the forefront of the new relationship between science and society.