| 集合预报的现状和前景 |
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| 引用本文： | 杜钧.集合预报的现状和前景[J].应用气象学报,2002,13(1):16-28. |
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| 作者姓名： | 杜钧 |
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| 作者单位： | 美国国家海洋大气局国家环境预报中心 |
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| 摘 要： | 综合论述了近年来已在国际上引起高度重视的新一代动力随机预报方法 ——— 集合预报。 随着计算机技术的迅猛发展和由于大气初值和数值模式中物理过程存在着不确定性的事实, 这一方法无疑代表了数值天气预报未来演变发展的方向。 未来的天气预报产品预计将从“决定论”的预报转变为“随机论”的预报来正确地表达气象科学中这一所谓“可预报性问题”, 以便更好地为用户服务。 文中扼要地叙述了集合预报的概念、基本问题及其最新的研究动态和发展, 包括(1)如何建立和评估一个集合预报系统;(2)如何正确地表征大气初值和模式物理过程的不确定性与随机性;(3)如何从集合预报中提炼有用的预报信息和合理地解释、检验集合预报的产品, 特别是概率预报。 除了直接在天气预报上的应用, 还提到集合预报在气象观测和资料同化方面应用的动态, 以引起有关研究人员的注意。
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| 关 键 词： | 集合预报 随机性 确定性 可预报性和概率预报 |
| 收稿时间： | 2001-05-02 |
| 修稿时间： | 2001年5月2日 |
Present Situation and Prospects of Ensemble Numerical Prediction |
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| Jun Du.Present Situation and Prospects of Ensemble Numerical Prediction[J].Quarterly Journal of Applied Meteorology,2002,13(1):16-28. |
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| Authors: | Jun Du |
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| Affiliation: | National Centers for Environmental Prediction/ NOAA, Washington DC, USA |
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| Abstract: | Over the past few years ensemble prediction has come to the fore as a major element in defining the future of numerical weather prediction (NWP) and operational weather forecasting. This stems basically from convergence of increasing recognition of the importance of explicitly addressing the intrinsic uncertainties in forecasts (originated from both initial conditions and model physics) with rapid advance in expanding capability to provide quantitative estimates of those uncertainties. It is widely agreed that ensemble based probabilities and measures of confidence hold the best potential for enhancing the ability to make user dependent informed decisions. Indeed, the U.S. National Weather Service is requiring that many forecast products evolve to become probabilistic in nature, especially for quantitative precipitation forecasting. In this paper, the basic concepts, outstanding issues and recent development of ensemble technique are briefly described, which include (1) how to establish and validate an ensemble forecasting system; (2) how to correctly represent intrinsic uncertainties in both initial conditions and model physics; and (3) how to extract useful information out of an ensemble of forecasts and how to interpret and evaluate ensemble products especially probabilistic forecasts. Besides its application to direct weather forecasting, application of ensemble technique to adaptive observation and data assimilation are also mentioned. |
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| Keywords: | Ensemble prediction Deterministic Stochastic Uncertainties |
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