Pardeep Pall, Alexandre S. Gagnon, Massimo A. Bollasina, Colin M. Zarzycki, Yuner Huang, Christopher T. S. Beckett, Harinaivo Ramanantoanina, Thomas P. S. Reynolds
{"title":"评估 HighResMIP 模拟中的南印度洋热带气旋特征","authors":"Pardeep Pall, Alexandre S. Gagnon, Massimo A. Bollasina, Colin M. Zarzycki, Yuner Huang, Christopher T. S. Beckett, Harinaivo Ramanantoanina, Thomas P. S. Reynolds","doi":"10.1002/joc.8609","DOIUrl":null,"url":null,"abstract":"<p>Several damaging tropical cyclones (TCs) have occurred recently over the South Indian Ocean (SIO) region, causing enormous social and economic losses. Yet, while many studies have examined SIO TC characteristics using observations and reanalysis, only a few have assessed these characteristics specifically for this region in climate models, and fewer have investigated their projections under climate change. Here we do this for a historical (1980–2010) and future (2020–2050) period, using multimodel simulations from the High Resolution Model Intercomparison Project, as well as examine biases in the historical period relative to a reanalysis (ERA5). The models have horizontal resolutions of 25–50 km, which has enabled an improved ability to represent tropical cyclones globally in previous studies. TempestExtremes software is employed to detect tropical storm and cyclone tracks. In cases where TempestExtremes cannot be applied due to a lack of requisite variables in a dataset, we instead examine extreme wind speeds in that dataset. For the historical period, we find considerable variation in model biases compared to ERA5, which itself exhibits realistic spatial patterns of tracks and their monthly distribution. Models do at least agree on positive biases in track frequency east of Madagascar and somewhat in the Mozambique Channel. However, the models and ERA5 only produce Category 3 tropical cyclones at best. Wind speeds for 25 km resolution models have much larger positive biases than for 50 km ones, suggesting the former can simulate even higher-category tropical cyclones. Considerable intermodel variation is also found in track changes between the future and historical periods. No systematic intercategory pattern of change exists, and low signal-to-noise may obscure any such patterns in the limited timespan of available data. Thus, no meaningful conclusions can be drawn regarding changes in track intensity. Nevertheless, track frequency broadly decreases across models for the region, as does accumulated cyclone energy. An east-to-west shift in track location from east of Madagascar toward the Mozambique Channel is also implied by track frequency and wind speed changes. Our findings provide information to potentially improve storm resiliency in this vulnerable region.</p>","PeriodicalId":13779,"journal":{"name":"International Journal of Climatology","volume":"44 13","pages":"4792-4808"},"PeriodicalIF":3.5000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8609","citationCount":"0","resultStr":"{\"title\":\"Assessing South Indian Ocean tropical cyclone characteristics in HighResMIP simulations\",\"authors\":\"Pardeep Pall, Alexandre S. Gagnon, Massimo A. Bollasina, Colin M. Zarzycki, Yuner Huang, Christopher T. S. Beckett, Harinaivo Ramanantoanina, Thomas P. S. Reynolds\",\"doi\":\"10.1002/joc.8609\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Several damaging tropical cyclones (TCs) have occurred recently over the South Indian Ocean (SIO) region, causing enormous social and economic losses. Yet, while many studies have examined SIO TC characteristics using observations and reanalysis, only a few have assessed these characteristics specifically for this region in climate models, and fewer have investigated their projections under climate change. Here we do this for a historical (1980–2010) and future (2020–2050) period, using multimodel simulations from the High Resolution Model Intercomparison Project, as well as examine biases in the historical period relative to a reanalysis (ERA5). The models have horizontal resolutions of 25–50 km, which has enabled an improved ability to represent tropical cyclones globally in previous studies. TempestExtremes software is employed to detect tropical storm and cyclone tracks. In cases where TempestExtremes cannot be applied due to a lack of requisite variables in a dataset, we instead examine extreme wind speeds in that dataset. For the historical period, we find considerable variation in model biases compared to ERA5, which itself exhibits realistic spatial patterns of tracks and their monthly distribution. Models do at least agree on positive biases in track frequency east of Madagascar and somewhat in the Mozambique Channel. However, the models and ERA5 only produce Category 3 tropical cyclones at best. Wind speeds for 25 km resolution models have much larger positive biases than for 50 km ones, suggesting the former can simulate even higher-category tropical cyclones. Considerable intermodel variation is also found in track changes between the future and historical periods. No systematic intercategory pattern of change exists, and low signal-to-noise may obscure any such patterns in the limited timespan of available data. Thus, no meaningful conclusions can be drawn regarding changes in track intensity. Nevertheless, track frequency broadly decreases across models for the region, as does accumulated cyclone energy. An east-to-west shift in track location from east of Madagascar toward the Mozambique Channel is also implied by track frequency and wind speed changes. Our findings provide information to potentially improve storm resiliency in this vulnerable region.</p>\",\"PeriodicalId\":13779,\"journal\":{\"name\":\"International Journal of Climatology\",\"volume\":\"44 13\",\"pages\":\"4792-4808\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joc.8609\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Climatology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/joc.8609\",\"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.8609","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}
Assessing South Indian Ocean tropical cyclone characteristics in HighResMIP simulations
Several damaging tropical cyclones (TCs) have occurred recently over the South Indian Ocean (SIO) region, causing enormous social and economic losses. Yet, while many studies have examined SIO TC characteristics using observations and reanalysis, only a few have assessed these characteristics specifically for this region in climate models, and fewer have investigated their projections under climate change. Here we do this for a historical (1980–2010) and future (2020–2050) period, using multimodel simulations from the High Resolution Model Intercomparison Project, as well as examine biases in the historical period relative to a reanalysis (ERA5). The models have horizontal resolutions of 25–50 km, which has enabled an improved ability to represent tropical cyclones globally in previous studies. TempestExtremes software is employed to detect tropical storm and cyclone tracks. In cases where TempestExtremes cannot be applied due to a lack of requisite variables in a dataset, we instead examine extreme wind speeds in that dataset. For the historical period, we find considerable variation in model biases compared to ERA5, which itself exhibits realistic spatial patterns of tracks and their monthly distribution. Models do at least agree on positive biases in track frequency east of Madagascar and somewhat in the Mozambique Channel. However, the models and ERA5 only produce Category 3 tropical cyclones at best. Wind speeds for 25 km resolution models have much larger positive biases than for 50 km ones, suggesting the former can simulate even higher-category tropical cyclones. Considerable intermodel variation is also found in track changes between the future and historical periods. No systematic intercategory pattern of change exists, and low signal-to-noise may obscure any such patterns in the limited timespan of available data. Thus, no meaningful conclusions can be drawn regarding changes in track intensity. Nevertheless, track frequency broadly decreases across models for the region, as does accumulated cyclone energy. An east-to-west shift in track location from east of Madagascar toward the Mozambique Channel is also implied by track frequency and wind speed changes. Our findings provide information to potentially improve storm resiliency in this vulnerable region.
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