Analogue correction method of errors and its application to numerical weather prediction
Gao Li (高丽)ad, Ren Hong-Li (任宏利)bc, Li Jian-Ping (李建平)a, Chou Ji-Fan (丑纪范)c
a State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; b Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081, China; c College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; d Graduate School of the Chinese Academy of Sciences, Beijing 100039, China
Abstract In this paper, an analogue correction method of errors (ACE) based on a complicated atmospheric model is further developed and applied to numerical weather prediction (NWP). The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model. Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.
Received: 17 August 2005
Revised: 01 November 2005
Accepted manuscript online:
Fund: Project supported by the National
Natural Science Foundation of China (Grant Nos 40575036 and 40325015).
Cite this article:
Gao Li (高丽), Ren Hong-Li (任宏利), Li Jian-Ping (李建平), Chou Ji-Fan (丑纪范) Analogue correction method of errors and its application to numerical weather prediction 2006 Chinese Physics 15 882
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
