结合陆地/海洋遥感数据与模型模拟，基于开发和测试的堆叠机器学习方法，重建了2000至2020年间空间分辨率为0.05°的全球连续8天XCO2（干空气二氧化碳柱平均摩尔分数）产品（GCXCO2）。GCXCO2产品与OCO-2卫星观测具有相似的空间分布特征，但实现了全球无缝覆盖，其空间分辨率和精度均优于CarbonTracker和CAMS模型模拟数据。该产品是基于遥感技术的全球高精度长期XCO2数据集之一，不仅有助于推进对气候变化和碳平衡的理解，也是检测二氧化碳浓度异常的重要工具。", "ds_source": "
数据来源于 https://zenodo.org/records/10083103 。", "ds_process_way": "
数据处理、模型训练和验证以及XCO2制图和时空分析。", "ds_quality": "
高时空分辨率（8 天，0.05°）全局 GCXCO2生产了涵盖2000年至2020年的产品。10 倍交叉验证结果 （R2= 0.974，RMSE = 0.551 ppm）和TCCON站验证结果（R2= 0.988，RMSE = 1.140 ppm）证实了该模型和产品具有整体良好的性能和准确性。", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "全球", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": -90.0, "ds_acq_lon_west": -180.0, "ds_acq_lat_north": 90.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 42667767365, "ds_files_count": 22, "ds_format": "*.nc", "ds_space_res": "0.05°", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "86b63615-42d2-4e63-8b4a-10a540ed9bc7.jpg", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2025-09-29 21:25:24", "last_updated": "2026-01-14 10:30:24", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ZENODO.DB7053.2025", "i18n": { "en": { "title": "Global continuous 0.05 degree atmospheric carbon dioxide dataset (GCXCO2) based OCO-2 satellite, CAMS and CarbonTracker simulation data from 2000 to 2020", "ds_format": "*.nc", "ds_source": "
The data is sourced from https://zenodo.org/records/10083103 .", "ds_quality": "
High spatiotemporal resolution (8 days, 0.05 °) global GCXCO2 production covers products from 2000 to 2020. The 10 fold cross validation results (R2=0.974, RMSE=0.551 ppm) and TCCON station validation results (R2=0.988, RMSE=1.140 ppm) confirm that the model and product have overall good performance and accuracy.", "ds_ref_way": "", "ds_abstract": "
Based on the development and testing of stacked machine learning methods, combined with land/ocean remote sensing data and model simulations, a global continuous 8-day XCO2 (dry air carbon dioxide column average mole fraction) product (GCXCO2) with a spatial resolution of 0.05 ° between 2000 and 2020 was reconstructed. The GCXCO2 product shares similar spatial distribution characteristics with OCO-2 satellite observations, but achieves seamless global coverage. Its spatial resolution and accuracy are superior to CarbonTracker and CAMS model simulation data. This product is one of the global high-precision long-term XCO2 datasets based on remote sensing technology, which not only helps to promote understanding of climate change and carbon balance, but also serves as an important tool for detecting abnormal carbon dioxide concentrations.
", "ds_time_res": "年", "ds_acq_place": "global", "ds_space_res": "0.05°", "ds_projection": "", "ds_process_way": "Data processing, model training and validation, as well as XCO2 mapping and spatiotemporal analysis.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "belong_to_nieer": false, "ds_topic_tags": [ "OCO-2", "0.05°", "全球" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "全球" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020 ], "ds_contributors": [ { "true_name": "沈焕锋", "email": "shenhf@whu.edu.cn", "work_for": "武汉大学资源与环境科学学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "沈焕锋", "email": "shenhf@whu.edu.cn", "work_for": "武汉大学资源与环境科学学院", "country": "中国" } ], "ds_managers": [ { "true_name": "沈焕锋", "email": "shenhf@whu.edu.cn", "work_for": "武汉大学资源与环境科学学院", "country": "中国" } ], "category": "气象" }