{"title":"Inter-comparison and evaluation of global satellite XCO<sub>2</sub> products","authors":"Hongji Yang, Tongwen Li, Jingan Wu, Lingfeng Zhang","doi":"10.1080/10095020.2023.2252017","DOIUrl":null,"url":null,"abstract":"Carbon dioxide (CO2) is one of the main greenhouse gases and has become a major concern as its concentration has been growing in recent years. Satellite remote sensing is an efficient way to monitor CO2 in the atmosphere, and several satellites are already used for CO2 monitoring. It is imperative to investigate the spatial coverage and spatio-temporal trends of satellite products, as well as identify the satellites with higher levels of accuracy. Additionally, examining the disparities between the older and new generations of satellites would be meaningful. Therefore, this paper provides a comprehensive evaluation and inter-comparison for the commonly used satellite column-averaged dry-air mole fraction of CO2 (XCO2) products. Specifically, the temporal trends and monthly coverage of the Greenhouse Gases Observing SATellite (GOSAT), Greenhouse Gases Observing SATellite-2 (GOSAT-2), Orbiting Carbon Observatory-2 (OCO-2), Orbiting Carbon Observatory-3 (OCO-3), and SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) are investigated. The accuracy of these satellite products is evaluated and analyzed based on Total Carbon Column Observing Network (TCCON) data. The results indicate that the XCO2 of all the satellite products show a year-by-year increase, with seasonal periodicity. In terms of overall accuracy, the OCO series satellites exhibit a slightly higher level of accuracy compared to the GOSAT series. The products of the new generation of satellites are less stable than those of the older generation, probably due to the impacts of the inversion algorithm and platforms.","PeriodicalId":48531,"journal":{"name":"Geo-spatial Information Science","volume":"362 1","pages":"0"},"PeriodicalIF":4.4000,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geo-spatial Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/10095020.2023.2252017","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
Carbon dioxide (CO2) is one of the main greenhouse gases and has become a major concern as its concentration has been growing in recent years. Satellite remote sensing is an efficient way to monitor CO2 in the atmosphere, and several satellites are already used for CO2 monitoring. It is imperative to investigate the spatial coverage and spatio-temporal trends of satellite products, as well as identify the satellites with higher levels of accuracy. Additionally, examining the disparities between the older and new generations of satellites would be meaningful. Therefore, this paper provides a comprehensive evaluation and inter-comparison for the commonly used satellite column-averaged dry-air mole fraction of CO2 (XCO2) products. Specifically, the temporal trends and monthly coverage of the Greenhouse Gases Observing SATellite (GOSAT), Greenhouse Gases Observing SATellite-2 (GOSAT-2), Orbiting Carbon Observatory-2 (OCO-2), Orbiting Carbon Observatory-3 (OCO-3), and SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) are investigated. The accuracy of these satellite products is evaluated and analyzed based on Total Carbon Column Observing Network (TCCON) data. The results indicate that the XCO2 of all the satellite products show a year-by-year increase, with seasonal periodicity. In terms of overall accuracy, the OCO series satellites exhibit a slightly higher level of accuracy compared to the GOSAT series. The products of the new generation of satellites are less stable than those of the older generation, probably due to the impacts of the inversion algorithm and platforms.
期刊介绍:
Geo-spatial Information Science was founded in 1998 by Wuhan University, and is now published in partnership with Taylor & Francis. The journal publishes high quality research on the application and development of surveying and mapping technology, including photogrammetry, remote sensing, geographical information systems, cartography, engineering surveying, GPS, geodesy, geomatics, geophysics, and other related fields. The journal particularly encourages papers on innovative applications and theories in the fields above, or of an interdisciplinary nature. In addition to serving as a source reference and archive of advancements in these disciplines, Geo-spatial Information Science aims to provide a platform for communication between researchers and professionals concerned with the topics above. The editorial committee of the journal consists of 21 professors and research scientists from different regions and countries, such as America, Germany, Switzerland, Austria, Hong Kong and China.