A Performance Evaluation of CMIP6 Wind Fields for Robust Forcing in Indian Ocean Wave Climate Studies

IF 3.5 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Meenakshi Sreejith, P. G. Remya, S. Sreelakshmi, B. Praveen Kumar, S. Malavika, T. M. Balakrishnan Nair, T. Srinivasa Kumar
{"title":"A Performance Evaluation of CMIP6 Wind Fields for Robust Forcing in Indian Ocean Wave Climate Studies","authors":"Meenakshi Sreejith,&nbsp;P. G. Remya,&nbsp;S. Sreelakshmi,&nbsp;B. Praveen Kumar,&nbsp;S. Malavika,&nbsp;T. M. Balakrishnan Nair,&nbsp;T. Srinivasa Kumar","doi":"10.1002/joc.8744","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The Coupled Model Intercomparison Project phase Six (CMIP6) lacks wave climate projections, emphasising the critical need to select the most accurate CMIP6 model winds for projecting wave climate. This study focuses on evaluating and selecting the optimal CMIP6 model wind fields for the Indian Ocean wave climate projections. A 35-year (1980–2014) wind-wave climate simulation of the Indian Ocean (IO) using the third-generation wave model WAVEWATCH-III (WW3), forced with seven CMIP6 Global Climate Models (BCC-CSM2-HR, EC-Earth3, CMCC-CM2-SR, GFDL-ESM4, CNRM-CM6-1-HR, HadGEM3-GC31-MM and MPI-ESM1-2-HR), is generated and validated against in situ buoy observations and ERA5 reanalysis data. Statistical analyses revealed that MPI, BCC and EC are the most accurate in representing wave characteristics in the IO, exhibiting strong correlations with observations and effectively capturing inter-annual variability. Extreme wave analysis shows that MPI, BCC and EC model wind-forced wave simulations match well with ERA5 data. The top three models (MPI, BCC and EC) are then selected for the composite analysis to assess their capability to reproduce the climate mode impacts on IO wave climate. EC performs best in capturing wave fields under El-Nino Southern Oscillation, Southern Annular Mode, and Indian Ocean Dipole influences, followed by BCC and MPI. Thus, the study identifies BCC, MPI and EC as the optimal CMIP6 models for the Indian Ocean wave projections.</p>\n </div>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"45 4","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Climatology","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/joc.8744","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The Coupled Model Intercomparison Project phase Six (CMIP6) lacks wave climate projections, emphasising the critical need to select the most accurate CMIP6 model winds for projecting wave climate. This study focuses on evaluating and selecting the optimal CMIP6 model wind fields for the Indian Ocean wave climate projections. A 35-year (1980–2014) wind-wave climate simulation of the Indian Ocean (IO) using the third-generation wave model WAVEWATCH-III (WW3), forced with seven CMIP6 Global Climate Models (BCC-CSM2-HR, EC-Earth3, CMCC-CM2-SR, GFDL-ESM4, CNRM-CM6-1-HR, HadGEM3-GC31-MM and MPI-ESM1-2-HR), is generated and validated against in situ buoy observations and ERA5 reanalysis data. Statistical analyses revealed that MPI, BCC and EC are the most accurate in representing wave characteristics in the IO, exhibiting strong correlations with observations and effectively capturing inter-annual variability. Extreme wave analysis shows that MPI, BCC and EC model wind-forced wave simulations match well with ERA5 data. The top three models (MPI, BCC and EC) are then selected for the composite analysis to assess their capability to reproduce the climate mode impacts on IO wave climate. EC performs best in capturing wave fields under El-Nino Southern Oscillation, Southern Annular Mode, and Indian Ocean Dipole influences, followed by BCC and MPI. Thus, the study identifies BCC, MPI and EC as the optimal CMIP6 models for the Indian Ocean wave projections.

Abstract Image

CMIP6 风场在印度洋波浪气候研究中的鲁棒强迫性能评估
耦合模式比对项目第六阶段(CMIP6)缺乏波浪气候预测,强调了选择最准确的CMIP6模式风来预测波浪气候的关键必要性。对CMIP6模式风场进行了评价和优选,以预测印度洋波浪气候。基于CMIP6全球气候模式(BCC-CSM2-HR、EC-Earth3、CMCC-CM2-SR、GFDL-ESM4、CNRM-CM6-1-HR、HadGEM3-GC31-MM和MPI-ESM1-2-HR),利用第三代波浪模式WAVEWATCH-III (WW3)生成了印度洋35年(80 - 2014)风浪气候模拟数据,并与现场浮标观测和ERA5再分析数据进行了验证。统计分析表明,MPI、BCC和EC最准确地代表了IO的波浪特征,与观测值表现出很强的相关性,并有效地捕获了年际变化。极端波分析表明,MPI、BCC和EC模式的风强迫波模拟结果与ERA5数据吻合较好。然后选择前三种模式(MPI、BCC和EC)进行综合分析,以评估其重现气候模式对IO波气候影响的能力。在厄尔尼诺-南方涛动、南环模和印度洋偶极子影响下,EC对波场的捕获效果最好,其次是BCC和MPI。因此,本研究确定BCC、MPI和EC为预测印度洋海浪的最佳CMIP6模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
International Journal of Climatology
International Journal of Climatology 地学-气象与大气科学
CiteScore
7.50
自引率
7.70%
发文量
417
审稿时长
4 months
期刊介绍: The International Journal of Climatology aims to span the well established but rapidly growing field of climatology, through the publication of research papers, short communications, major reviews of progress and reviews of new books and reports in the area of climate science. The Journal’s main role is to stimulate and report research in climatology, from the expansive fields of the atmospheric, biophysical, engineering and social sciences. Coverage includes: Climate system science; Local to global scale climate observations and modelling; Seasonal to interannual climate prediction; Climatic variability and climate change; Synoptic, dynamic and urban climatology, hydroclimatology, human bioclimatology, ecoclimatology, dendroclimatology, palaeoclimatology, marine climatology and atmosphere-ocean interactions; Application of climatological knowledge to environmental assessment and management and economic production; Climate and society interactions
×
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:481959085
Book学术官方微信