海洋环流模式NEMO数据同化方法及其在俄罗斯北极地区海洋特征计算中的应用

K. Belyaev, A. Kuleshov, I. Smirnov
{"title":"海洋环流模式NEMO数据同化方法及其在俄罗斯北极地区海洋特征计算中的应用","authors":"K. Belyaev, A. Kuleshov, I. Smirnov","doi":"10.1109/ISPRAS47671.2019.00019","DOIUrl":null,"url":null,"abstract":"Based on the GKF (Generalized Kalman Filter) data assimilation method, which we have proposed earlier, jointly with the NEMO (Nucleus for European Modelling of the Ocean) model of ocean circulation, the spatial-temporal variability of several model characteristics, in particular, the ocean level field and the water temperature field in the Arctic Zone of Russia, is studied in numerical experiments. The ocean level data taken from the AVISO (Archiving, Validating and Interpolation Satellite Observation) archive are assimilated into the NEMO model. The ocean level and temperature are calculated both with and without data assimilation (the control run). The results of calculations are analyzed and it is shown that the main spatial variability of the characteristics after data assimilation is in a good agreement with the localization of currents in the Northern Atlantics and the Arctic Zone of Russia. The authors have performed the installation and adaptation of the NEMO software package on the K-60 high-performance computer (HPC) in the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences (Moscow, Russia). The qualitative estimate of this variability is presented and it is shown at what time interval the dependence of the calculated characteristics on the observation data manifests itself.","PeriodicalId":154688,"journal":{"name":"2019 Ivannikov Ispras Open Conference (ISPRAS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Data Assimilation Method for the Ocean Circulation Model NEMO and Its Application for the Calculation of Ocean Characteristics in the Arctic Zone of Russia\",\"authors\":\"K. Belyaev, A. Kuleshov, I. Smirnov\",\"doi\":\"10.1109/ISPRAS47671.2019.00019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the GKF (Generalized Kalman Filter) data assimilation method, which we have proposed earlier, jointly with the NEMO (Nucleus for European Modelling of the Ocean) model of ocean circulation, the spatial-temporal variability of several model characteristics, in particular, the ocean level field and the water temperature field in the Arctic Zone of Russia, is studied in numerical experiments. The ocean level data taken from the AVISO (Archiving, Validating and Interpolation Satellite Observation) archive are assimilated into the NEMO model. The ocean level and temperature are calculated both with and without data assimilation (the control run). The results of calculations are analyzed and it is shown that the main spatial variability of the characteristics after data assimilation is in a good agreement with the localization of currents in the Northern Atlantics and the Arctic Zone of Russia. The authors have performed the installation and adaptation of the NEMO software package on the K-60 high-performance computer (HPC) in the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences (Moscow, Russia). The qualitative estimate of this variability is presented and it is shown at what time interval the dependence of the calculated characteristics on the observation data manifests itself.\",\"PeriodicalId\":154688,\"journal\":{\"name\":\"2019 Ivannikov Ispras Open Conference (ISPRAS)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Ivannikov Ispras Open Conference (ISPRAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPRAS47671.2019.00019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Ivannikov Ispras Open Conference (ISPRAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPRAS47671.2019.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

基于本文提出的GKF (Generalized Kalman Filter)数据同化方法,结合NEMO (Nucleus for European Modelling of the Ocean)海洋环流模式,通过数值实验研究了俄罗斯北极地区几种模式特征,特别是海平面场和水温场的时空变异性。来自AVISO(存档、验证和插值卫星观测)存档的海平面数据被同化到NEMO模型中。在数据同化和不同化的情况下计算海平面和温度(对照运行)。对计算结果进行了分析,结果表明,同化后的主要空间变异性与北大西洋和俄罗斯北极地区的海流局域化具有较好的一致性。作者在俄罗斯科学院Keldysh应用数学研究所(莫斯科,俄罗斯)的K-60高性能计算机(HPC)上进行了NEMO软件包的安装和适配。本文给出了这种变率的定性估计,并说明了计算特征对观测数据的依赖性在什么时间间隔内表现出来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Assimilation Method for the Ocean Circulation Model NEMO and Its Application for the Calculation of Ocean Characteristics in the Arctic Zone of Russia
Based on the GKF (Generalized Kalman Filter) data assimilation method, which we have proposed earlier, jointly with the NEMO (Nucleus for European Modelling of the Ocean) model of ocean circulation, the spatial-temporal variability of several model characteristics, in particular, the ocean level field and the water temperature field in the Arctic Zone of Russia, is studied in numerical experiments. The ocean level data taken from the AVISO (Archiving, Validating and Interpolation Satellite Observation) archive are assimilated into the NEMO model. The ocean level and temperature are calculated both with and without data assimilation (the control run). The results of calculations are analyzed and it is shown that the main spatial variability of the characteristics after data assimilation is in a good agreement with the localization of currents in the Northern Atlantics and the Arctic Zone of Russia. The authors have performed the installation and adaptation of the NEMO software package on the K-60 high-performance computer (HPC) in the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences (Moscow, Russia). The qualitative estimate of this variability is presented and it is shown at what time interval the dependence of the calculated characteristics on the observation data manifests itself.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信