兰州大学机构库 >大气科学学院
An Online Model Correction Method Based on an Inverse Problem: Part I-Model Error Estimation by Iteration
Xue, HL; Shen, XS; Chou, JF; Xue, HL (reprint author), Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China.
2015-10
Source PublicationADVANCES IN ATMOSPHERIC SCIENCES
ISSN0256-1530
Volume32Issue:10Pages:1329-1340
AbstractErrors inevitably exist in numerical weather prediction (NWP) due to imperfect numeric and physical parameterizations. To eliminate these errors, by considering NWP as an inverse problem, an unknown term in the prediction equations can be estimated inversely by using the past data, which are presumed to represent the imperfection of the NWP model (model error, denoted as ME). In this first paper of a two-part series, an iteration method for obtaining the MEs in past intervals is presented, and the results from testing its convergence in idealized experiments are reported. Moreover, two batches of iteration tests were applied in the global forecast system of the Global and Regional Assimilation and Prediction System (GRAPES-GFS) for July-August 2009 and January-February 2010. The datasets associated with the initial conditions and sea surface temperature (SST) were both based on NCEP (National Centers for Environmental Prediction) FNL (final) data. The results showed that 6th h forecast errors were reduced to 10% of their original value after a 20-step iteration. Then, off-line forecast error corrections were estimated linearly based on the 2-month mean MEs and compared with forecast errors. The estimated error corrections agreed well with the forecast errors, but the linear growth rate of the estimation was steeper than the forecast error. The advantage of this iteration method is that the MEs can provide the foundation for online correction. A larger proportion of the forecast errors can be expected to be canceled out by properly introducing the model error correction into GRAPES-GFS.
Keywordmodel error past data inverse problem error estimation model correction GRAPES-GFS
Subject AreaMeteorology & Atmospheric Sciences
PublisherSCIENCE CHINA PRESS
DOI10.1007/s00376-015-4261-1
Publication PlaceBEIJING
Indexed BySCIE ; CSCD
Language英语
First Inst
Funding Project国家自然科学基金项目 ; 国家科技支撑计划
Host of Journal中国科学院大气物理研究所
Project NumberNational Natural Science Foundation Science Fund for Youth [41405095] ; Key Projects in National Science and Technology Pillar Program during the Twelfth Five-year Plan Period [2012BAC22B02] ; National Natural Science Foundation Science Fund for Creative Research Groups [41221064]
WOS IDWOS:000359011900002
CSCD IDCSCD:5488255
Funding OrganizationNSFC ; MOST
SubtypeArticle
IRIDWOS:000359011900002
Department[Xue Haile;
Shen Xueshun] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China;
[Shen Xueshun] China Meteorol Adm, Ctr Numer Predict, Beijing 100081, Peoples R China;
[Xue Haile;
Chou Jifan] Lanzhou Univ, Sch Atmospher Sci, Lanzhou 730000, Peoples R China
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Cited Times:1[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.lzu.edu.cn/handle/262010/182624
Collection大气科学学院
Corresponding AuthorXue, HL (reprint author), Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China.
Recommended Citation
GB/T 7714
Xue, HL,Shen, XS,Chou, JF,et al. An Online Model Correction Method Based on an Inverse Problem: Part I-Model Error Estimation by Iteration[J]. ADVANCES IN ATMOSPHERIC SCIENCES,2015,32(10):1329-1340.
APA Xue, HL,Shen, XS,Chou, JF,&Xue, HL .(2015).An Online Model Correction Method Based on an Inverse Problem: Part I-Model Error Estimation by Iteration.ADVANCES IN ATMOSPHERIC SCIENCES,32(10),1329-1340.
MLA Xue, HL,et al."An Online Model Correction Method Based on an Inverse Problem: Part I-Model Error Estimation by Iteration".ADVANCES IN ATMOSPHERIC SCIENCES 32.10(2015):1329-1340.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Altmetrics Score
Google Scholar
Similar articles in Google Scholar
[Xue, HL]'s Articles
[Shen, XS]'s Articles
[Chou, JF]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xue, HL]'s Articles
[Shen, XS]'s Articles
[Chou, JF]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xue, HL]'s Articles
[Shen, XS]'s Articles
[Chou, JF]'s Articles
Terms of Use
No data!
Social Bookmark/Share
No comment.
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.