GOSAT卫星二氧化碳遥感产品的验证与分析
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摘要
本文利用全球地基二氧化碳柱浓度观测站点(Total Carbon Column Observing Network,TCCON)18个站点CO_2地基观测数据对GOSAT(Greenhouse gases Observing Satellite)2009—2017年的大气CO_2遥感反演产品进行验证分析,结果显示卫星CO_2遥感产品与地基遥感观测结果较为一致,在东亚、北美、欧洲和大洋洲四个区域内卫星遥感产品与地基观测的平均偏差分别为2. 23±2. 69、2. 19±2. 19、2. 01±2. 49、1. 59±1. 79 ppm,相关系数不低于0. 75。卫星在30°S～60°N范围内的产品精度较高,而在高纬地区产品精度稍低。本文进一步利用GOSAT L2 XCO_2遥感反演产品对全球大气CO_2的长时间序列变化进行了分析,结果表明2009—2017年全球大气CO_2浓度呈持续上升趋势,全球年平均增长率为2. 22 ppm·a~(-1),增长较快的国家和地区包括中国、美国、印度和非洲,受与厄尔尼诺有关的自然排放影响,2016年相对上一年的增长量最多,年均CO_2绝对增量在3 ppm以上。
The data from 18 sites of TCCON are used for the validation of GOSAT XCO_2 products from2009 to 2017, which show a consistency between satellite data and ground-based measurements. Biases between the satellite data and ground-based measurements in East Asia, North America, Europe and Oceania are 2. 23 ± 2. 69, 2. 19 ± 2. 19, 2. 01 ± 2. 49, 1. 59±1. 79 ppm, respectively, and the correlation coefficient is not less than 0. 75. The accuracy of satellite products is higher in the range of 30°S-60°N, but slightly lower in high latitudes. In addition, authors also use GOSAT L2 XCO_2 products to analyze the change of global atmospheric CO_2 in long-term sequence. The results show that the concentration of global atmospheric CO_2 shows a continuous upward trend from 2009 to 2017, and the global average annual growth rate is 2. 22 ppm · a~(-1). There are some fast-growing countries and regions, including China, the United States, India, and Africa. Influenced by natural emissions of El Nino, the concentration of atmospheric CO_2 grew the fastest in 2016, with the growth rate being more than 3 ppm · a~(-1).
The data from 18 sites of TCCON are used for the validation of GOSAT XCO_2 products from2009 to 2017, which show a consistency between satellite data and ground-based measurements. Biases between the satellite data and ground-based measurements in East Asia, North America, Europe and Oceania are 2. 23 ± 2. 69, 2. 19 ± 2. 19, 2. 01 ± 2. 49, 1. 59±1. 79 ppm, respectively, and the correlation coefficient is not less than 0. 75. The accuracy of satellite products is higher in the range of 30°S-60°N, but slightly lower in high latitudes. In addition, authors also use GOSAT L2 XCO_2 products to analyze the change of global atmospheric CO_2 in long-term sequence. The results show that the concentration of global atmospheric CO_2 shows a continuous upward trend from 2009 to 2017, and the global average annual growth rate is 2. 22 ppm · a~(-1). There are some fast-growing countries and regions, including China, the United States, India, and Africa. Influenced by natural emissions of El Nino, the concentration of atmospheric CO_2 grew the fastest in 2016, with the growth rate being more than 3 ppm · a~(-1).
引文
白文广,张兴赢,张鹏,2010.卫星遥感监测中国地区对流层二氧化碳时空变化特征分析[J].科学通报,55(30):2953-2960.
布然,雷莉萍,郭丽洁,等,2015.大气CO_2浓度时空变化卫星遥感监测的应用潜力分析[J].遥感学报,19(1):34-45.
贾凡,2014.全球变暖背景下热带太平洋的响应及其机制[D].青岛:中国海洋大学.
李雪,石大山,牛超,2016. 2015:超强厄尔尼诺之年[J].生态经济,32(3):6-9.
林伟立,徐晓斌,2011.卫星遥感NO_2资料地面验证对中国大气本底观测的潜在需求[J].气象,37(5):571-575.
刘瑞霞,张兴赢,刘杰,等,2014.卫星遥感CO_2时空分布特征分析[C] 2014中国环境科学学会学术年会论文集.成都:中国环境科学学会:1-2.
祁承经,曹福祥,曹受金,2010.热带森林碳汇或碳源之争[J].生态学报,30(23):6613-6623.
王明星,曾庆存,1986.大气中的二氧化碳含量[J].大气科学,10(2):212-219.
吴军,方勇华,叶函函,等,2013.基于高分辨率地基FTS光谱的大气CO_2反演方法研究[J].光谱学与光谱分析,32(5):1281-1284.
邢如楠,王彰贵,2001.热带太平洋表面水中CO_2对El Nino事件响应的数值模拟[J].气象学报,59(3):308-317.
徐永福,赵亮,浦一芬,等,2004.二氧化碳海气交换通量估计的不确定性[J].地学前缘,11(2):565-571.
张淼,张兴赢,刘瑞霞,2014.卫星高光谱大气CO_2遥感反演精度地基验证研究[J].气候变化研究进展,10(6):427-432.
张兴赢,张鹏,方宗义,等,2007.应用卫星遥感技术监测大气痕量气体的研究进展[J].气象,33(7):3-14.
张兴赢,张鹏,廖宏,等,2009.地基傅里叶红外高光谱遥感观测大气成分平台建设及其反演技术研究[J].气象,35(1):9-17.
周敏强,张兴赢,王普才,等,2015.二氧化碳柱浓度的卫星反演试验及地基验证[J].中国科学D辑:地球科学,45(6):856-863.
周涛,仪垂祥,Bakwin P S,等,2008.大气CO_2浓度变化与生物群系气候异常之间的关联分析[J].中国科学D辑:地球科学,38(2):224-231.
Buschmann M,Deutscher N M, Sherlock V,et al,2016. Retrieval of xCO_2 from ground-based mid-infrared(NDACC)solar absorption spectra and comparison to TCCON[J]. Atmos Meas Tech,9(2):577-585.
Butz A, Guerlet S, IIasekamp O,et al.2011. Toward accurate CO_2and CII4 observations from GOSAT[J]. Geophys Res Lett,38:L14812.
Crisp D,Fisher B M,O'Dell C,et al.2012. The ACOS CO_2 retrieval algorithm-Part II:Global XCO_2 data characterization[J]. Atmos Meas Tech,5(4):687-707.
Inoue M, Morino I,Uchino O,et al, 2013. Validation of XCO_2 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data[J]. Atmos Chem Phys,13(19):9771-9788.
Kulawik S,Wunch D,O'Dell C,et al,2016. Consistent evaluation of ACOS-GOSAT,BESD-SCIAMACIIY, CarbonTracker, and MACC through comparisons to TCCON[J]. Atmos Meas Tech,9(2):683-709.
Kuze A,Suto II,Nakajima M,et al,2009. Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring[J]. Appl Opt,48(35):6716-6733.
Liu Ruixia,Zhang Xingying,Liu Jie,et al,2015. A spatial-temporal distribution characteristics study on the atmospheric carbon dioxide observed by gosat satellite remote sensing[J]. J Trop Meteor, 21(4):408-416.
Morino I,Uchino O, Inoue M,et al.2011. Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra[J]. Atmos Meas Tech,4(6):1061-1076.
Qu Yan, Zhang Chunmin, Wang Dingyi,et al,2013. Comparison of atmospheric CO_2 observed by GOSAT and two ground stations in China[J]. Int J Remote Sens,34(11):3938-3946.
WMO,2014. Global Atmosphere. 2014. WMO Greenhouse Gas Bulletin(GIIG Bulletin)-N°10-Climate Summit edition:The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2013[M].
WMO,2016. Global Atmosphere. 2016. WMO GREENHOUSE GAS BULLETIN:The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2015[M].
WMO,2017. Global Atmosphere. 2017. WMO GREENHOUSE GAS BULLETIN:The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2016[M].
Wunch D,Toon G C,Blavier J F L,et al,2011. The total carbon column observing network[J]. Philos Trans A Math Phys Eng Sci,369(1943):2087-2112.
Wunch D,Toon G C,Sherlock V,et al.2015. The Total Carbon Column Observing Network's GGG2014 Data Version[M]. Oak Ridge:Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory.
Wunch D,Wennberg P O,Osterman G,et al.2017. Comparisons of the Orbiting Carbon Observatory-2(OCO-2)XCO_2 measurements with TCCON[J]. Atmos Meas Tech, 10(6):2209-2238.
Yang Zhonghua, Toon G C, Margolis J S,et al.2002. Atmospheric CO_2 retrieved from ground-based near IR solar spectra[J]. Geophys Res Lett,29(9):53-1-53-4.
Yoshida Y,Kikuchi N,Morino I,et al.2013. Improvement of the retrieval algorithm for GOSAT SWIR XCO_2 and XCII4 and their validation using TCCON data[J]. Atmos Meas Tech, 6(6):1533-1547.
Yoshida Y,Ota Y,Eguchi N,et al,2011. Retrieval algorithm for CO_2and CII4 column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite[J]. Atmos Meas Tech,4(4):717-734.
Zhang Huifang, Chen Baozhang,Xu Guang, et al,2015. Comparing simulated atmospheric carbon dioxide concentration with GOSAT retrievals[J]. Sci Bull,60(3):380-386.
布然,雷莉萍,郭丽洁,等,2015.大气CO_2浓度时空变化卫星遥感监测的应用潜力分析[J].遥感学报,19(1):34-45.
贾凡,2014.全球变暖背景下热带太平洋的响应及其机制[D].青岛:中国海洋大学.
李雪,石大山,牛超,2016. 2015:超强厄尔尼诺之年[J].生态经济,32(3):6-9.
林伟立,徐晓斌,2011.卫星遥感NO_2资料地面验证对中国大气本底观测的潜在需求[J].气象,37(5):571-575.
刘瑞霞,张兴赢,刘杰,等,2014.卫星遥感CO_2时空分布特征分析[C] 2014中国环境科学学会学术年会论文集.成都:中国环境科学学会:1-2.
祁承经,曹福祥,曹受金,2010.热带森林碳汇或碳源之争[J].生态学报,30(23):6613-6623.
王明星,曾庆存,1986.大气中的二氧化碳含量[J].大气科学,10(2):212-219.
吴军,方勇华,叶函函,等,2013.基于高分辨率地基FTS光谱的大气CO_2反演方法研究[J].光谱学与光谱分析,32(5):1281-1284.
邢如楠,王彰贵,2001.热带太平洋表面水中CO_2对El Nino事件响应的数值模拟[J].气象学报,59(3):308-317.
徐永福,赵亮,浦一芬,等,2004.二氧化碳海气交换通量估计的不确定性[J].地学前缘,11(2):565-571.
张淼,张兴赢,刘瑞霞,2014.卫星高光谱大气CO_2遥感反演精度地基验证研究[J].气候变化研究进展,10(6):427-432.
张兴赢,张鹏,方宗义,等,2007.应用卫星遥感技术监测大气痕量气体的研究进展[J].气象,33(7):3-14.
张兴赢,张鹏,廖宏,等,2009.地基傅里叶红外高光谱遥感观测大气成分平台建设及其反演技术研究[J].气象,35(1):9-17.
周敏强,张兴赢,王普才,等,2015.二氧化碳柱浓度的卫星反演试验及地基验证[J].中国科学D辑:地球科学,45(6):856-863.
周涛,仪垂祥,Bakwin P S,等,2008.大气CO_2浓度变化与生物群系气候异常之间的关联分析[J].中国科学D辑:地球科学,38(2):224-231.
Buschmann M,Deutscher N M, Sherlock V,et al,2016. Retrieval of xCO_2 from ground-based mid-infrared(NDACC)solar absorption spectra and comparison to TCCON[J]. Atmos Meas Tech,9(2):577-585.
Butz A, Guerlet S, IIasekamp O,et al.2011. Toward accurate CO_2and CII4 observations from GOSAT[J]. Geophys Res Lett,38:L14812.
Crisp D,Fisher B M,O'Dell C,et al.2012. The ACOS CO_2 retrieval algorithm-Part II:Global XCO_2 data characterization[J]. Atmos Meas Tech,5(4):687-707.
Inoue M, Morino I,Uchino O,et al, 2013. Validation of XCO_2 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data[J]. Atmos Chem Phys,13(19):9771-9788.
Kulawik S,Wunch D,O'Dell C,et al,2016. Consistent evaluation of ACOS-GOSAT,BESD-SCIAMACIIY, CarbonTracker, and MACC through comparisons to TCCON[J]. Atmos Meas Tech,9(2):683-709.
Kuze A,Suto II,Nakajima M,et al,2009. Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring[J]. Appl Opt,48(35):6716-6733.
Liu Ruixia,Zhang Xingying,Liu Jie,et al,2015. A spatial-temporal distribution characteristics study on the atmospheric carbon dioxide observed by gosat satellite remote sensing[J]. J Trop Meteor, 21(4):408-416.
Morino I,Uchino O, Inoue M,et al.2011. Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra[J]. Atmos Meas Tech,4(6):1061-1076.
Qu Yan, Zhang Chunmin, Wang Dingyi,et al,2013. Comparison of atmospheric CO_2 observed by GOSAT and two ground stations in China[J]. Int J Remote Sens,34(11):3938-3946.
WMO,2014. Global Atmosphere. 2014. WMO Greenhouse Gas Bulletin(GIIG Bulletin)-N°10-Climate Summit edition:The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2013[M].
WMO,2016. Global Atmosphere. 2016. WMO GREENHOUSE GAS BULLETIN:The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2015[M].
WMO,2017. Global Atmosphere. 2017. WMO GREENHOUSE GAS BULLETIN:The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2016[M].
Wunch D,Toon G C,Blavier J F L,et al,2011. The total carbon column observing network[J]. Philos Trans A Math Phys Eng Sci,369(1943):2087-2112.
Wunch D,Toon G C,Sherlock V,et al.2015. The Total Carbon Column Observing Network's GGG2014 Data Version[M]. Oak Ridge:Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory.
Wunch D,Wennberg P O,Osterman G,et al.2017. Comparisons of the Orbiting Carbon Observatory-2(OCO-2)XCO_2 measurements with TCCON[J]. Atmos Meas Tech, 10(6):2209-2238.
Yang Zhonghua, Toon G C, Margolis J S,et al.2002. Atmospheric CO_2 retrieved from ground-based near IR solar spectra[J]. Geophys Res Lett,29(9):53-1-53-4.
Yoshida Y,Kikuchi N,Morino I,et al.2013. Improvement of the retrieval algorithm for GOSAT SWIR XCO_2 and XCII4 and their validation using TCCON data[J]. Atmos Meas Tech, 6(6):1533-1547.
Yoshida Y,Ota Y,Eguchi N,et al,2011. Retrieval algorithm for CO_2and CII4 column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite[J]. Atmos Meas Tech,4(4):717-734.
Zhang Huifang, Chen Baozhang,Xu Guang, et al,2015. Comparing simulated atmospheric carbon dioxide concentration with GOSAT retrievals[J]. Sci Bull,60(3):380-386.