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Significantly improved representation of the stratospheric quasi-biennial oscillation in the CMA-RA V1.5 reanalysis dataset

Jinggao Hu Zixu Wang Jing-Jia Luo Xinrui Li Rongjun Wang

大气和海洋科学快报(英文版)2026,Vol.19Issue(4):34-39,6.
大气和海洋科学快报(英文版)2026,Vol.19Issue(4):34-39,6.DOI:10.1016/j.aosl.2025.100692

Significantly improved representation of the stratospheric quasi-biennial oscillation in the CMA-RA V1.5 reanalysis dataset

Significantly improved representation of the stratospheric quasi-biennial oscillation in the CMA-RA V1.5 reanalysis dataset

Jinggao Hu 1Zixu Wang 2Jing-Jia Luo 3Xinrui Li 1Rongjun Wang1

作者信息

  • 1. State Key Laboratory of Environment Characteristics and Effects for Near-space(ECEN)/Key Laboratory of Meteorological Disaster,Ministry of Education(KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD),Nanjing University of Information Science and Technology,Nanjing,China
  • 2. Key Laboratory of Mesoscale Severe Weather,Ministry of Education,and School of Atmospheric Sciences,Nanjing University,Nanjing,China
  • 3. State Key Laboratory of Climate System Prediction and Risk Management(CPRM)/Institute for Climate and Application Research(ICAR),Nanjing University of Information Science and Technology,Nanjing,China
  • 折叠

摘要

Abstract

迄今为止,中国气象局先后发布了两套全球大气再分析数据,分别被称为CRA-40和CMA-RA V1.5.以往研究表明,CRA-40对平流层准两年振荡(QBO)现象的刻画与国际上广泛使用的ERA5再分析数据相比还存在较大的偏差.本研究评估了CMA-RA V1.5再分析数据对QBO的表征能力.结果表明,该套数据对QBO的刻画技巧已有了显著提升,并且已与ERA5相当.具体而言,在QBO指数,周期和振幅的表征方面,CMA-RA V1.5与ERA5之间的误差分别为CRA-40与ERA5之间误差的2%,7%和12%.CMA-RA V1.5中更为先进的资料同化技术可能是其数据质量得到提升的重要原因.

关键词

CMA-RA V1.5/CRA-40/ERA5/平流层准两年振荡/再分析数据比较

Key words

CMA-RA V1.5/CRA-40/ERA5/Stratospheric quasi-biennial oscillation/Reanalysis intercomparison

引用本文复制引用

Jinggao Hu,Zixu Wang,Jing-Jia Luo,Xinrui Li,Rongjun Wang..Significantly improved representation of the stratospheric quasi-biennial oscillation in the CMA-RA V1.5 reanalysis dataset[J].大气和海洋科学快报(英文版),2026,19(4):34-39,6.

基金项目

This work was supported by the National Natural Science Foundation of China[grant numbers 42088101 and 42361144843]. ()

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