{"title":"考虑海平面压力主成分分析的全球平均波高统计模拟及其在未来波高预测中的应用","authors":"R. Kishimoto, T. Shimura, N. Mori, H. Mase","doi":"10.3178/HRL.11.51","DOIUrl":null,"url":null,"abstract":"Future wave climate projection is important for climate impact assessment of the coastal hazards and environment. In this study, monthly averaged wave heights are estimated by a linear multi-regression model using atmospheric data as explanatory variables. The present statistical model considers local atmospheric information (wind speed at 10 m height, sea level pressure) and large scale atmospheric information obtained from principal component analysis (PCA) of the global sea level pressure field. The representation of swell in the lower latitude is greatly improved by introducing the large scale atmospheric information from the PCA. The present statistical model was applied to the results of the Japan Meteorological Research Institute’s Atmospheric General/Global Circulation Model (MRI-AGCM) climate change projection. The future change of wave heights shows an increase in the northern North Pacific Ocean and a decrease in the North Atlantic Ocean, middle latitude and tropics of the Pacific Ocean.","PeriodicalId":13111,"journal":{"name":"Hydrological Research Letters","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3178/HRL.11.51","citationCount":"4","resultStr":"{\"title\":\"Statistical modeling of global mean wave height considering principal component analysis of sea level pressures and its application to future wave height projection\",\"authors\":\"R. Kishimoto, T. Shimura, N. Mori, H. Mase\",\"doi\":\"10.3178/HRL.11.51\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Future wave climate projection is important for climate impact assessment of the coastal hazards and environment. In this study, monthly averaged wave heights are estimated by a linear multi-regression model using atmospheric data as explanatory variables. The present statistical model considers local atmospheric information (wind speed at 10 m height, sea level pressure) and large scale atmospheric information obtained from principal component analysis (PCA) of the global sea level pressure field. The representation of swell in the lower latitude is greatly improved by introducing the large scale atmospheric information from the PCA. The present statistical model was applied to the results of the Japan Meteorological Research Institute’s Atmospheric General/Global Circulation Model (MRI-AGCM) climate change projection. The future change of wave heights shows an increase in the northern North Pacific Ocean and a decrease in the North Atlantic Ocean, middle latitude and tropics of the Pacific Ocean.\",\"PeriodicalId\":13111,\"journal\":{\"name\":\"Hydrological Research Letters\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.3178/HRL.11.51\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hydrological Research Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3178/HRL.11.51\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrological Research Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3178/HRL.11.51","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"WATER RESOURCES","Score":null,"Total":0}
Statistical modeling of global mean wave height considering principal component analysis of sea level pressures and its application to future wave height projection
Future wave climate projection is important for climate impact assessment of the coastal hazards and environment. In this study, monthly averaged wave heights are estimated by a linear multi-regression model using atmospheric data as explanatory variables. The present statistical model considers local atmospheric information (wind speed at 10 m height, sea level pressure) and large scale atmospheric information obtained from principal component analysis (PCA) of the global sea level pressure field. The representation of swell in the lower latitude is greatly improved by introducing the large scale atmospheric information from the PCA. The present statistical model was applied to the results of the Japan Meteorological Research Institute’s Atmospheric General/Global Circulation Model (MRI-AGCM) climate change projection. The future change of wave heights shows an increase in the northern North Pacific Ocean and a decrease in the North Atlantic Ocean, middle latitude and tropics of the Pacific Ocean.
期刊介绍:
Hydrological Research Letters (HRL) is an international and trans-disciplinary electronic online journal published jointly by Japan Society of Hydrology and Water Resources (JSHWR), Japanese Association of Groundwater Hydrology (JAGH), Japanese Association of Hydrological Sciences (JAHS), and Japanese Society of Physical Hydrology (JSPH), aiming at rapid exchange and outgoing of information in these fields. The purpose is to disseminate original research findings and develop debates on a wide range of investigations on hydrology and water resources to researchers, students and the public. It also publishes reviews of various fields on hydrology and water resources and other information of interest to scientists to encourage communication and utilization of the published results. The editors welcome contributions from authors throughout the world. The decision on acceptance of a submitted manuscript is made by the journal editors on the basis of suitability of subject matter to the scope of the journal, originality of the contribution, potential impacts on societies and scientific merit. Manuscripts submitted to HRL may cover all aspects of hydrology and water resources, including research on physical and biological sciences, engineering, and social and political sciences from the aspects of hydrology and water resources.