全国高分辨全覆盖CO2柱浓度数据集
收藏资源简介：
本数据集是针对现有单一碳卫星观测存在数据缺口和空间分辨率不足的问题，创新研发的一套高时空分辨率、无缝覆盖的中国区域CO₂柱浓度融合产品。通过集成OCO-2、GOSAT等多源卫星的XCO₂观测数据和ERA5高分辨率气象再分析资料，并采用DeepForest等先进的深度学习模型与时空统计降尺度技术，成功生成了2019年至2022年间覆盖中国全域的月均及日均XCO₂数据产品，空间分辨率高达1公里。该产品克服了单一卫星观测的空间不连续性问题，实现了100%的空间覆盖，同时将原始卫星产品的空间分辨率提升了一个数量级。经过地基观测网的交叉验证，融合产品在保持高精度的同时，显著增强了数据的时空连续性与可用性。这套数据集为在国家与区域尺度上开展精细化的碳排放监测、溯源分析、以及评估自然碳汇的空间分布提供了前所未有的高分辨率数据基础，有力支撑了我国“双碳”目标的科学评估与管理决策。数据集为栅格格式。(协议共享)
This dataset is an innovatively developed fusion product of XCO₂ (column-averaged atmospheric CO₂ concentration) over China, featuring high spatiotemporal resolution and seamless coverage, addressing the problems of data gaps and insufficient spatial resolution in existing single carbon satellite observations. By integrating XCO₂ observation data from multi-source satellites including OCO-2 and GOSAT, as well as high-resolution ERA5 meteorological reanalysis data, and adopting advanced deep learning models such as DeepForest and spatiotemporal statistical downscaling techniques, it successfully generates monthly and daily averaged XCO₂ datasets covering the entire territory of China from 2019 to 2022, with a spatial resolution of up to 1 km. This product overcomes the spatial discontinuity issue of single satellite observations, achieves 100% spatial coverage, and improves the spatial resolution of the original satellite products by an order of magnitude. Cross-validated via ground-based observation networks, the fused product maintains high accuracy while significantly enhancing the spatiotemporal continuity and usability of the data. This dataset provides an unprecedented high-resolution data foundation for conducting fine-grained carbon emission monitoring, traceability analysis, and assessment of the spatial distribution of natural carbon sinks at national and regional scales, strongly supporting the scientific assessment and management decisions for China's "dual carbon" goals. The dataset is in raster format. (Shared under agreement)
