大气CO2反演方法影响因子分析

大气与环境光学学报 ›› 2014, Vol. 9 ›› Issue (6): 448-456.

大气CO2反演方法影响因子分析

刘启明1，麻金继1，王先华2，江新华2

(1.安徽师范大学国土资源与旅游学院，安徽芜湖 241003；
2.中国科学院安徽光学精密机械研究所通用光学定标与表征技术重点实验室，安徽合肥　230031)

收稿日期:2013-11-21 修回日期:2014-01-08 发布日期:2014-11-14
通讯作者: 刘启明（1982-），男，安徽庐江人, 研究生，研究方向为遥感应用. E-mail:liuqiming_2010@126.com
作者简介:刘启明（1982-），男，安徽庐江人, 研究生，研究方向为遥感应用.
基金资助:
国家自然基金（41271377）资助

Analysis of Influence Factors of Retrieval Method for Atmospheric CO2

LIU Qi-ming1, MA Jin-ji1,WANG Xian-hua2, JIANG Xin-hua2

(1. The College of Territorial Resources and Tourism, Anhui Normal University ,Wuhu 241003, China;
2. Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China )

Received:2013-11-21 Revised:2014-01-08 Online:2014-11-14

摘要/Abstract

摘要：

如果卫星遥感反演大气精度要求达到1%，则可以通过全球连续高精度观测弥补地面观测的不足。在实际反演中，反演精度不仅受到卷云和气溶胶的影响，还受到其它诸多因素（地表温度，地表压力，地表反照率，大气湿度等）的影响。讨论分析了这些因子的影响：在以 US1976 美国标准大气为背景，观测高度是100 km条件下，运用最优非线性反演算法，使用逐线积分辐射传输模型LBLRTM模拟计算，模拟分析出地表温度、地表压力、地表反射率、大气湿度各增加1%和减小1%的情况下，对反演结果的影响，以及各典型气溶胶对反演结果的影响。结果显示：海洋型，沙漠型，城市型，乡村型四种典型气溶胶对反演结果的影响都比较大，影响最大的为海洋型气溶胶，能见度为5 km，影响百分比相对于初始值(380 ppm)降低了27.18%，影响最小的为乡村型气溶胶，能见度为23 km，影响百分比相对于初始值(380 ppm)减小了7.78%；地表反射率，地表温度，地表压力对反演结果也有很大的影响，而大气湿度对反演结果的影响很小，基本可忽略不计。

关键词: CO2, LBLRTM, 影响因子, 反演方法

Abstract:

If retrieval accuracy for using the satellite remote sensing reached 1%, then the deficiency of ground observation can be made up through the global continuous high precision observation. In the retrieval algorithm, the retrieval accuracy is not only affected by the cirrus clouds and aerosols, but also by effects of other factors (surface temperature, surface pressure, surface albedo and atmospheric humidity). The influence on the retrieval results for , as well as the influence of typical aerosols on the retrieval results were analyzed when surface temperature, surface pressure, surface albedo, atmospheric humidity respectively increased by 1% and reduce by 1%, under the background of US1976 America Standard Atmosphere and the observation height of 100 km, based on the optimum nonlinear retrieval algorithm, using a line by line integral radiation transfer model (LBLRTM) simulation. The results showed that effects of the four kinds of typical aerosol (marine, desert, city , rural) on the retrieval results are relatively large. The maximal impact corresponded to the marine aerosol, if the visibility is 5 km, the influence percentage relative to the initial value (380 ppm) decreased by 27.18%. The minimal impact corresponded to rural aerosol, if the visibility is 23 km, the influence percentage relative to the initial value (380 ppm) decreased by 7.78%. The surface reflectance, surface temperature, and surface pressure have great influences on the retrieval results for , but have little influence of atmospheric humidity on the retrieval results, which can be ignored.

Key words: CO2, LBLRTM, influencing factors, retrieval method

中图分类号:

TP751

刘启明麻金继王先华江新华. 大气CO2反演方法影响因子分析[J]. 大气与环境光学学报, 2014, 9(6): 448-456.

LIU Qi-Ming, MA Jin-Ji, WANG Xian-Hua, JIANG Xin-Hua. Analysis of Influence Factors of Retrieval Method for Atmospheric CO2[J]. Journal of Atmospheric and Environmental Optics, 2014, 9(6): 448-456.

参考文献

[1] International Panel Climate Change (IPCC). Climate Change 2007: Synthesis Report [R]. IPCC Fourth Assessment Report. 2007.
[2] Bousquet P, Peylin P, Ciais P, et al. Regional changes in carbon dioxide fluxes of land and oceans since 1980 [J]. Science, 2000, 290(5495): 1342-1346.
[3] Rayner P J, O'Brien D M. The utility of remotely sensed CO2 concentration data in surface source inversions [J]. Geophys. Res. Lett., 2001, 28: 2429.
[4] Hu Zhenhua, Fang Fang, Gu Xuejun, et al. Sensitivity research of CO2 retrieval of infrared radiative spectra [J]. Journal of Atmospheric and Environmental Optics, 2010, 5(4): 269-275(in Chinese). 胡振华, 方芳, 顾学军, 等红外辐射光谱反演CO2浓度的敏感性研究 [J]. 大气与环境光学学报, 2010, 5(4): 269-275.
[5] Yang D X, Liu Y, Cai Z N. Simulations of aerosol optical properties to top of atmospheric reflected sunlight in the near infrared CO2 weak absorption band [J]. Atmospheric And Oceanic Science Letters, 2013, (6): 60-64.
[6] Aben I, Hasekamp O, Hartmann W. Uncertainties in the space-based measurements of CO2 columns due to scattering in the Earth's atmosphere [J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2007, 104: 450-459.
[7] Yoshifumi O, Yukio Y A, Tatsuya Y A. Study of retrieving colunm amount of carbon dioxide from satellite-based near-infrared observation of solar scattered light in clear sky condition-error estimation and optimization of vertical pressure grid [J]. Journal of The Romote Sensing Society of Japan, 2008, 28(2): 152-160.
[8] Zhou mingmin, Chen liangfu, Tao jinhua, et al. Temperature sensitivity analysis of carbon dioxide measurement in SWIR band [J]. Journal of Infrared and Millimeter Waves, 2012, 31(5): 455-461(in Chinese).
皱铭敏, 陈良富, 陶金花, 等. 短波红外通道 CO2观测的温度敏感性分析 [J]. 红外与毫米波学报, 2012, 31(5): 455-461.
[9] Hu zhenhua, Huang teng, Wang Yingping, et al. Study on the effect of solar spectra on the retrieval of atmospheric CO2 concentration using high resolution absorption spectra [J]. Spectroscopy and Spectral Analysis, 2011, 31(6): 1683-1687(in Chinese).
胡振华, 黄腾, 王颖萍, 等. 太阳光谱对高分辨吸收光谱反演大气CO2浓度影响的研究 [J]. 光谱学与光谱分析, 2011, 31(6): 1683-1687.
[10]Rodgers C D. Inverse Methods for Atmospheric Sounding: Theory and Practice [M]. Singapore: World Scientific, 2000: 81-100.
[11]Liu yi,Yang dong-xu,Cai zhao-nan et al. retrieval method for atmospheric CO2 Using China carbon satellite:Preliminary application of GOSAT data.Science China Press,2013,58(11)996-999.
刘毅,杨东旭,蔡兆男等.中国碳卫星大气CO2反演方法: GOSAT 数据初步应用 [J]. 中国科学, 2013, 58(11): 996-999.
[12] Ru fei, Lei Liping, Hou Shanshan, et al. Evaluation of retrieval errors of greenhouse gas concentrations from GOSAT [J]. Remote Sensing Information, 2013, 28(1): 65-70(in Chinese).
茹菲, 雷莉萍, 侯姗姗, 等. GOSAT卫星温室气体浓度反演误差的分析与评价 [J]. 遥感信息, 2013, 28(1): 65-70.
[13] Yoshida Y, Ota Y, Eguchi N, et al. Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite
[J]. Atmospheric Measurement Techniques, 2011, (4): 717-734.