摘要
CO_(2)是温室效应的主要成因,掌握CO_(2)的浓度及变化可为实现碳中和与碳达峰的双碳目标提供支持。短波近红外通道对近地层CO_(2)浓度变化敏感,通过模拟大气辐射传输的整个物理过程,构建正演模型,并基于最优化方法和牛顿迭代法对GOSAT卫星获取的短波红外辐亮度数据进行处理和分析,实现了对全球范围内CO_(2)浓度的高精度反演。将算法反演的CO_(2)柱平均干空气混合比(XCO_(2))与GOSAT卫星二级产品和碳柱浓度观测网络TC-CON站点XCO_(2)数据进行对比验证。结果表明,算法反演精度为-0.397%,与卫星产品的平均绝对误差为1.32 ppm,相对误差为0.235%;与TCCON站点数据对比平均绝对误差为1.67 ppm,相对误差为-0.397%,优于1%的应用要求。
Carbon dioxide(CO_(2))is the main cause of the greenhouse effect.Understanding the concentration and change of CO_(2)can support the realization of carbon neutrality and carbon peaking.Short-wave near-infrared channel is sensitive to changes in CO_(2)concentration near the ground.By simulating the whole physical process of atmospheric radi-ation transmission,a forward model is constructed.Based on the optimization method and Newton iteration method,the short-wave infrared radiance data obtained by Greenhouse gases Observing Satellite(GOSAT)are processed and ana-lyzed,and the high-precision inversion of CO_(2)concentration on a global scale is successfully realized.The CO_(2)Column average dry air mixing ratio(XCO_(2))retrieved by the algorithm is compared with the XCO_(2)data of GOSAT satellite sec-ondary products and total carbon column observing network(TCCON)stations.The results show that the retrieval accu-racy of the algorithm is-0.397%,the average absolute error is 1.32 ppm and the relative error is 0.235%.Compared with TCCON site data,the average absolute error is 1.67 ppm and the relative error is-0.397%,which is better than 1%application requirement.
作者
李聪
邓小波
刘海磊
袁杰
LI Cong;DENG Xiaobo;LIU Hailei;YUAN Jie(College of Electronic Engineering,Chengdu University of Information Technology,Chengdu 610225,China)
出处
《成都信息工程大学学报》
2025年第4期478-483,共6页
Journal of Chengdu University of Information Technology
关键词
卫星遥感
短波红外
CO_(2)
物理反演
satellite remote sensing
shortwave Infrared
CO_(2)
physical retrieval
