{"title":"AIRS、SCIAMACHY和GOSAT与基于全球二氧化碳浓度的地面数据的精度比较","authors":"Linjing Zhang, Xiuying Zhang, Hong Jiang","doi":"10.1109/Geoinformatics.2013.6626159","DOIUrl":null,"url":null,"abstract":"Global warming has become one of the most important and far-reaching global environmental problems. In order to make reliable predictions of future climate, there has been a series of remote sensing detectors launched into the space. In this manuscript, characteristics of the present common observing platform and their product data are compared and analyzed. The results indicate that: GOSAT is inferior in systematic errors and provides limited of quantity of data. SCIAMACHY is systemically slightly higher than ground-based data and limited in coverage. CO2 concentration retrieved from AIRS is in excellent agreement with the ground-based data. Most correlation coefficients are more than 0.9, which has shown that AIRS retrieved results have the ability to reflect real distribution and changes of CO2 very well.","PeriodicalId":286908,"journal":{"name":"2013 21st International Conference on Geoinformatics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Accuracy comparisons of AIRS, SCIAMACHY and GOSAT with ground-based data based on global CO2 concentration\",\"authors\":\"Linjing Zhang, Xiuying Zhang, Hong Jiang\",\"doi\":\"10.1109/Geoinformatics.2013.6626159\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Global warming has become one of the most important and far-reaching global environmental problems. In order to make reliable predictions of future climate, there has been a series of remote sensing detectors launched into the space. In this manuscript, characteristics of the present common observing platform and their product data are compared and analyzed. The results indicate that: GOSAT is inferior in systematic errors and provides limited of quantity of data. SCIAMACHY is systemically slightly higher than ground-based data and limited in coverage. CO2 concentration retrieved from AIRS is in excellent agreement with the ground-based data. Most correlation coefficients are more than 0.9, which has shown that AIRS retrieved results have the ability to reflect real distribution and changes of CO2 very well.\",\"PeriodicalId\":286908,\"journal\":{\"name\":\"2013 21st International Conference on Geoinformatics\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 21st International Conference on Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/Geoinformatics.2013.6626159\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 21st International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Geoinformatics.2013.6626159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Accuracy comparisons of AIRS, SCIAMACHY and GOSAT with ground-based data based on global CO2 concentration
Global warming has become one of the most important and far-reaching global environmental problems. In order to make reliable predictions of future climate, there has been a series of remote sensing detectors launched into the space. In this manuscript, characteristics of the present common observing platform and their product data are compared and analyzed. The results indicate that: GOSAT is inferior in systematic errors and provides limited of quantity of data. SCIAMACHY is systemically slightly higher than ground-based data and limited in coverage. CO2 concentration retrieved from AIRS is in excellent agreement with the ground-based data. Most correlation coefficients are more than 0.9, which has shown that AIRS retrieved results have the ability to reflect real distribution and changes of CO2 very well.