Jong-Min Kim;Hyun-Cheol Kim;Jeong-Won Park;Jinku Park;Minji Seo;Sang-Moo Lee
{"title":"北极海冰融化开始连续检测的先进算法","authors":"Jong-Min Kim;Hyun-Cheol Kim;Jeong-Won Park;Jinku Park;Minji Seo;Sang-Moo Lee","doi":"10.1109/TGRS.2025.3560261","DOIUrl":null,"url":null,"abstract":"Expansion of the Arctic melting season with an earlier melt onset date (MOD) is a well-known indicator of Arctic warming. Since 1979, the pan-Arctic MOD distributions usually have been estimated using passive satellite microwave radiometer observations. However, there is a poor agreement in MOD between previous MOD detection algorithms based on passive microwave measurements, raising doubts regarding the accuracy of their MOD products. Thus, this study developed a new MOD algorithm, namely TBmax algorithm, to improve the estimation accuracy of continuous melt onset. The TBmax algorithm utilizes the microwave radiation characteristics of sea ice, and the daily brightness temperature time series shows their maximum brightness temperature on MOD. By using AMSR2 brightness temperature data, the pan-Arctic MOD distributions estimated from 2013 to 2021 using the TBmax algorithm successfully reproduced a feature of sea ice melting that mainly during May or June over the Arctic, including the late melting tendency of ice at high latitudes and multiyear ice (MYI). Validation with independent dataset (ice mass balance (IMB) buoy data) suggested that the TBmax MODs showed superior performance compared to other previous algorithms (biases of 0.1 days versus −2.7 and 13.9 days). As MOD can provide information about surface emissivity and the energy budget of the sea ice, the improved MOD may contribute to a more precise analysis of Arctic environment change and enhanced estimation of sea ice parameters.","PeriodicalId":13213,"journal":{"name":"IEEE Transactions on Geoscience and Remote Sensing","volume":"63 ","pages":"1-14"},"PeriodicalIF":7.5000,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advanced Algorithm for Continuous Melt Onset Detection on Arctic Sea Ice\",\"authors\":\"Jong-Min Kim;Hyun-Cheol Kim;Jeong-Won Park;Jinku Park;Minji Seo;Sang-Moo Lee\",\"doi\":\"10.1109/TGRS.2025.3560261\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Expansion of the Arctic melting season with an earlier melt onset date (MOD) is a well-known indicator of Arctic warming. Since 1979, the pan-Arctic MOD distributions usually have been estimated using passive satellite microwave radiometer observations. However, there is a poor agreement in MOD between previous MOD detection algorithms based on passive microwave measurements, raising doubts regarding the accuracy of their MOD products. Thus, this study developed a new MOD algorithm, namely TBmax algorithm, to improve the estimation accuracy of continuous melt onset. The TBmax algorithm utilizes the microwave radiation characteristics of sea ice, and the daily brightness temperature time series shows their maximum brightness temperature on MOD. By using AMSR2 brightness temperature data, the pan-Arctic MOD distributions estimated from 2013 to 2021 using the TBmax algorithm successfully reproduced a feature of sea ice melting that mainly during May or June over the Arctic, including the late melting tendency of ice at high latitudes and multiyear ice (MYI). Validation with independent dataset (ice mass balance (IMB) buoy data) suggested that the TBmax MODs showed superior performance compared to other previous algorithms (biases of 0.1 days versus −2.7 and 13.9 days). As MOD can provide information about surface emissivity and the energy budget of the sea ice, the improved MOD may contribute to a more precise analysis of Arctic environment change and enhanced estimation of sea ice parameters.\",\"PeriodicalId\":13213,\"journal\":{\"name\":\"IEEE Transactions on Geoscience and Remote Sensing\",\"volume\":\"63 \",\"pages\":\"1-14\"},\"PeriodicalIF\":7.5000,\"publicationDate\":\"2025-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Geoscience and Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10964354/\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Geoscience and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10964354/","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Advanced Algorithm for Continuous Melt Onset Detection on Arctic Sea Ice
Expansion of the Arctic melting season with an earlier melt onset date (MOD) is a well-known indicator of Arctic warming. Since 1979, the pan-Arctic MOD distributions usually have been estimated using passive satellite microwave radiometer observations. However, there is a poor agreement in MOD between previous MOD detection algorithms based on passive microwave measurements, raising doubts regarding the accuracy of their MOD products. Thus, this study developed a new MOD algorithm, namely TBmax algorithm, to improve the estimation accuracy of continuous melt onset. The TBmax algorithm utilizes the microwave radiation characteristics of sea ice, and the daily brightness temperature time series shows their maximum brightness temperature on MOD. By using AMSR2 brightness temperature data, the pan-Arctic MOD distributions estimated from 2013 to 2021 using the TBmax algorithm successfully reproduced a feature of sea ice melting that mainly during May or June over the Arctic, including the late melting tendency of ice at high latitudes and multiyear ice (MYI). Validation with independent dataset (ice mass balance (IMB) buoy data) suggested that the TBmax MODs showed superior performance compared to other previous algorithms (biases of 0.1 days versus −2.7 and 13.9 days). As MOD can provide information about surface emissivity and the energy budget of the sea ice, the improved MOD may contribute to a more precise analysis of Arctic environment change and enhanced estimation of sea ice parameters.
期刊介绍:
IEEE Transactions on Geoscience and Remote Sensing (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.