###
气象:2015,41(8):986-996
本文二维码信息
码上扫一扫!
数值天气预报中分析同化基本方法的历史发展脉络和评述
(国家气象中心, 北京 100081)
Remarks on Development of Basic Methods of Atmospheric Data Assimilation for Numerical Weather Prediction
(National Meteorological Centre, Beijing 100081)
摘要
图/表
参考文献
相似文献
本文已被:浏览 1498次   下载 2754
投稿时间:2015-01-08    修订日期:2015-05-05
中文摘要: 数值天气预报中分析同化的基本方法先后经历了多项式函数拟合方法、逐步订正方法、最优插值方法、变分方法和集合卡尔曼滤波方法。本文首先根据相关的经典文献力求本色地介绍这些方法的基本思想和实施的具体要点;然后,着重于它们的上下承接关系,试图阐述同化的历史发展脉络,评述这些方法的显著特征和创新性,以期清晰地理解资料同化的循序渐进的内在发展逻辑。此外,从起源上阐明“主观分析”与“客观分析”、“初猜场”与“背景场”、“分析”与“同化”、以及“更新”、“新息”等基本概念,以期准确地理解和把握“大气资料同化”的由来和内涵。
Abstract:Main basic methods of analysis and assimilation for numerical weather prediction (NWP) has gone through the polynomial function fitting method, the successive correction method (SCM), the optimum interpolation (OI), the variational method (Var) and the ensemble Kalman filter (EnKF). This article tries to present a concise and true description with their basic ideas and implementation approaches based on original classical references to these methods. Then remarks on their distinct characteristics and innovative development are made, and it is highlighted, from these remarks, that we can see a step by step expansion of useful information and cutdown on limitations along the historical progress of atmospheric data assimilation, which is clearly endowed with a fore and aft connection and a cognitively simple internal logic of development. Also, an effort is taken to precisely understand the concept of “atmospheric data assimilation”, along its historical progress and on basis of some essential terms “subjective analysis” and “objective analysis”, “first guess field” and “background field”, “analysis” and “assimilation”, “update”, and “innovation”.
文章编号:     中图分类号:    文献标志码:
基金项目:公益性行业(气象)科研专项(GYHY201206007)和国家自然科学基金面上项目(41175034)共同资助
引用文本:
朱国富,2015.数值天气预报中分析同化基本方法的历史发展脉络和评述[J].气象,41(8):986-996.
ZHU Guofu,2015.Remarks on Development of Basic Methods of Atmospheric Data Assimilation for Numerical Weather Prediction[J].Meteor Mon,41(8):986-996.