基于CO<sub>2</sub>测量数据的大气辐射传输模型LBLRTM优化

张炳炎; 闫召爱; 郭文杰; 胡雄

doi:10.11728/cjss2021.06.905

基于CO₂测量数据的大气辐射传输模型LBLRTM优化

doi: 10.11728/cjss2021.06.905

张炳炎^1,2,3,
闫召爱^1,2,3,
郭文杰^1,2,
胡雄^1,2

1. 中国科学院国家空间科学中心北京 100190;
2. 中国科学院空间环境态势感知技术重点实验室北京 100190;
3. 中国科学院大学北京 100049

基金项目:

中国科学院战略性先导科技专项（XDA17010303）和国家自然科学基金青年科学基金项目（41905038）共同资助

详细信息

作者简介:
张炳炎,E-mail:yanza@nssc.ac.cn

中图分类号: P351
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- 被引次数: 0
出版历程
- 收稿日期: 2020-03-20
- 修回日期: 2021-01-22
- 刊出日期: 2021-11-15

Optimization of Atmospheric Radiative Transfer Model LBLRTM Based on Measured CO₂ Data

ZHANG Bingyan^1,2,3,
YAN Zhaoai^1,2,3,
GUO Wenjie^1,2,
HU Xiong^1,2

1. National Space Science Center, Chinese Academy of Sciences, Beijing 100190;
2. Key Laboratory of Science and Technology on Environmental Space Situation Awareness, Chinese Academy of Sciences, Beijing 100190;
3. University of Chinese Academy of Science of Sciences, Beijing 100049

摘要

摘要: 根据TIMED/SABER 2002—2018年的CO₂观测数据，分析CO₂浓度的变化特征.依据变化特征给出了CO₂浓度随时间、高度、纬度变化的月平均拟合公式，利用非线性最小二乘拟合法，对不同高度和不同纬度的CO₂浓度数据分别进行拟合，生成相应的拟合参数.然后，将所有拟合参数汇总并生成拟合参数文件，结合拟合公式构建全球CO₂浓度经验计算模块，并将该模块应用到大气辐射传输模型LBLRTM中，对该模型进行优化.将优化前与优化后的LBLRTM模型模拟结果分别与TIMED/SABER观测数据进行比较发现，优化前的LBLRTM模型模拟结果与观测值的均方根误差为15.4%，而优化后的LBLRTM模型模拟结果与观测值的均方根误差由15.4%下降至8.91%.结果表明该优化方法可以提高LBLRTM模型在红外波段的辐射模拟精度.
- 大气辐射传输 /
- 红外辐射 /
- CO₂浓度
Abstract: According to the CO2 observation data of TIMED/SABER from 2002 to 2018, analyze the variation characteristics of CO2 concentration, gives the monthly average fitting formula of CO2 concentration varying with time, height and latitude according to the various characteristics, and uses the nonlinear least square fitting method to fit the CO2 concentration data of different heights and latitudes respectively to generate corresponding fitting parameters, Then, summarize all fitting parameters and generate the fitting parameter file. Combined with the fitting formula, the empirical calculation module of global CO2 concentration is constructed, and the module is applied to the atmospheric radiative transfer model LBLRTM to optimize LBLRTM. Comparing the simulation results of the optimized LBLRTM model with the TIMED/SABER observation data, the root mean square error between the simulation results of the not optimized LBLRTM model and the observation value is 15.4%, while the root mean square error between the simulation results of the optimized LBLRTM model and the observation value is reduced to 8.91%. The results show that this optimization method can further improve the radiation simulation accuracy of the LBLRTM model in the infrared band.
- Atmospheric radiative transfer /
- Infrared radiation /
- CO₂ concentration

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参考文献(8)

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