Global land 1° mapping dataset of XCO_(2) from satellite observations of GOSAT and OCO-2 from 2009 to 2020  

作　　者：Mengya Sheng Liping Lei Zhao-Cheng Zeng Weiqiang Rao Hao Songd Changjiang Wu 

机构地区：[1]Key Laboratory of Digital Earth Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing,China [2]College of Resources and Environment,University of Chinese Academy of Sciences,Beijing,China [3]Division of Geological and Planetary Sciences,California Institute of Technology,Pasadena,California,USA [4]School of Earth Sciences,China University of Geosciences,Beijing,China

出　　处：《Big Earth Data》2023年第1期170-190,共21页地球大数据（英文）

基　　金：This work was supported by the National Key Research and Development Program of China(Grant No.2020YFA0607503);the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA19080303);the Key Program of the Chinese Academy of Sciences(Grant No.ZDRW-ZS-2019-1-3).

摘　　要：A global mapping data of atmospheric carbon dioxide(CO_(2))concen-trations can help us to better understand the spatiotemporal varia-tions of CO_(2) and the driving factors of the variations to support the actions for emissions reduction and control.Greenhouse gases satel-lites that measure atmospheric CO_(2),such as the Greenhouse Gases Observing Satellite(GOSAT)and Orbiting Carbon Observatory(OCO-2),have been providing global observations of the column averaged dry-air mole fractions of CO_(2)(XCO_(2))since 2009.However,these XCO_(2) retrievals are irregular in space and time with many gaps.In this paper,we mapped a global spatiotemporally continuous XCO_(2) data-set(Mapping-XCO_(2))using the XCO_(2) retrievals from GOSAT and OCO-2 during the period from April 2009 to December 2020 based on a geostatistical approach that fills those data gaps.The dataset covers a geographic range from 56°S to 65°N and 169°W to 180°E for a 1°grid interval in space and 3-day time interval.The uncer-tainties of the mapped XCO_(2) values are generally less than 1.5 parts per million(ppm).The spatiotemporal characteristics of global XCO_(2) that are revealed by the Mapping-XCO_(2) are similar to the model data obtained from CarbonTracker.Compared to the ground observa-tions,the overall standard bias is 1.13 ppm.The results indicate that this long-term Mapping-XCO_(2) dataset can be used to investigate the spatiotemporal variations of global atmospheric XCO_(2) and can support studies related to the carbon cycle and anthropogenic CO_(2) emissions.The dataset is available at http://www.doi.org/10.7910/DVN/4WDTD8 and https://www.scidb.cn/en/detail?dataSetId=c2c3111b421043fc8d9b163c39e6f56e.

关 键 词：Global land mapping atmospheric CO_(2)column concentration satellite observation GOSAT OCO-2 

分 类 号：P41[天文地球—大气科学及气象学]