Meenakshi Sreejith, P. G. Remya, S. Sreelakshmi, B. Praveen Kumar, S. Malavika, T. M. Balakrishnan Nair, T. Srinivasa Kumar
{"title":"CMIP6 风场在印度洋波浪气候研究中的鲁棒强迫性能评估","authors":"Meenakshi Sreejith, P. G. Remya, S. Sreelakshmi, B. Praveen Kumar, S. Malavika, T. M. Balakrishnan Nair, 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":"{\"title\":\"A Performance Evaluation of CMIP6 Wind Fields for Robust Forcing in Indian Ocean Wave Climate Studies\",\"authors\":\"Meenakshi Sreejith, P. G. Remya, S. Sreelakshmi, B. Praveen Kumar, S. Malavika, T. M. Balakrishnan Nair, 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}","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}
A Performance Evaluation of CMIP6 Wind Fields for Robust Forcing in Indian Ocean Wave Climate Studies
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.
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