{"title":"改进1900年至2011年海平面变化的估计","authors":"B. Hamlington, R. Leben, K.‐Y. Kim","doi":"10.1109/OCEANS.2012.6405061","DOIUrl":null,"url":null,"abstract":"A new method for reconstructing sea level involving cyclostationary empirical orthogonal functions (CSEOFs) is presented. The focus is on how other ocean observations such as sea surface temperature can be leveraged to create an improved reconstructed sea level dataset spanning the time period from 1900 to present. Basis functions are computed using satellite measurements of sea surface temperature, and using a simple regression technique, these basis functions are transformed to represent a similar temporal evolution to corresponding satellite altimeter-derived sea level basis functions. The resulting sea level and sea surface temperature basis functions are fit to tide gauge data and historical sea surface temperature data, respectively, to produce a reconstructed sea level dataset spanning the period from 1900 to present. We present a detailed explanation of this technique and demonstrate how it can be used for improved climate monitoring over the last century.","PeriodicalId":434023,"journal":{"name":"2012 Oceans","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving estimates of sea level variability from 1900 to 2011\",\"authors\":\"B. Hamlington, R. Leben, K.‐Y. Kim\",\"doi\":\"10.1109/OCEANS.2012.6405061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new method for reconstructing sea level involving cyclostationary empirical orthogonal functions (CSEOFs) is presented. The focus is on how other ocean observations such as sea surface temperature can be leveraged to create an improved reconstructed sea level dataset spanning the time period from 1900 to present. Basis functions are computed using satellite measurements of sea surface temperature, and using a simple regression technique, these basis functions are transformed to represent a similar temporal evolution to corresponding satellite altimeter-derived sea level basis functions. The resulting sea level and sea surface temperature basis functions are fit to tide gauge data and historical sea surface temperature data, respectively, to produce a reconstructed sea level dataset spanning the period from 1900 to present. We present a detailed explanation of this technique and demonstrate how it can be used for improved climate monitoring over the last century.\",\"PeriodicalId\":434023,\"journal\":{\"name\":\"2012 Oceans\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Oceans\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OCEANS.2012.6405061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Oceans","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCEANS.2012.6405061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving estimates of sea level variability from 1900 to 2011
A new method for reconstructing sea level involving cyclostationary empirical orthogonal functions (CSEOFs) is presented. The focus is on how other ocean observations such as sea surface temperature can be leveraged to create an improved reconstructed sea level dataset spanning the time period from 1900 to present. Basis functions are computed using satellite measurements of sea surface temperature, and using a simple regression technique, these basis functions are transformed to represent a similar temporal evolution to corresponding satellite altimeter-derived sea level basis functions. The resulting sea level and sea surface temperature basis functions are fit to tide gauge data and historical sea surface temperature data, respectively, to produce a reconstructed sea level dataset spanning the period from 1900 to present. We present a detailed explanation of this technique and demonstrate how it can be used for improved climate monitoring over the last century.