地表气压对温室气体柱总量反演的敏感性分析及敦煌地区温室气体的柱总量观测

刘丹丹; 黄印博; 孙宇松; 卢兴吉; 曹振松

doi:doi:10.3788/ope.20202803.0573

光学精密工程, 2020, 28 (3): 573, 网络出版: 2020-05-12

地表气压对温室气体柱总量反演的敏感性分析及敦煌地区温室气体的柱总量观测

Analysis of earth surface pressure sensitivity on inversion of greenhouse gases columns and observation of greenhouse gases columns in Dunhuang in China

论文大纲

刘丹丹 ^1,2,3,*黄印博 ¹孙宇松 ^1,2卢兴吉 ¹曹振松 ¹

作者单位

¹ 中国科学院安徽光学精密机械研究所中国科学院大气光学重点实验室, 安徽合肥 230031

² 中国科学技术大学研究生院科学岛分院, 安徽合肥 230026

³ 皖西学院电气与光电工程学院, 安徽六安 237012

摘要

地表气压对温室气体浓度反演具有非常重要的影响。利用地基便携式傅里叶变换光谱仪EM27/SUN观测了敦煌地区H2O, CO2, CH4及CO气体分子的浓度, 获得了2018年6月27日到7月21日敦煌地区大气中XH2O, XCO2, XCH4及XCO的时间序列, 结合敦煌观测数据, 定量分析了地表气压对气体柱-平均摩尔分数Xgas(column-averaged dry air mole fractions, DMFs)反演的影响。结果表明: XH2O, XCO2, XCH4及XCO与地表气压密切相关, 相关系数均高于0.99, 柱总量随地表气压的变化快慢决定柱-平均摩尔分数随地表气压的变化趋势。相比较CO2, CH4及CO 分子, XH2O对地表气压的敏感性较弱, 地表气压改变1 hPa, XH2O, XCO2, XCH4及XCO分别变化0.027 8%, 0.065 9%, 0068 6%和0.062%; 观测期间, H2O, CO2的浓度变化幅度波动较大, XCH4, XCO变化较小, XH2O平均值在2 000×10-6~6 000×10-6变化, 而 XCO2平均值在407.27×10-6~417.60×10-6变化, 敦煌站点XH2O, XCO2, XCH4及XCO的测量精度分别为2.3%, 0.14%, 0.12%及1.7%, XCO2及XCH4的测量精度均优于TCCON网的测量精度; 与GOSAT卫星数据对比结果显示, 地基反演的XCO2, XCH4值均偏大, XCO2的绝对偏差为7.07×10-6, XCH4的绝对偏差为0.025×10-6; 与WACCM数据对比显示, 地基反演XCO2结果多数大于WACCM值, 最大绝对偏差可以达到80×10-6, 地基反演XCH4值小于WACCM值, 最大绝对偏差为0.032×10-6。实时观测数据更能反映当地的具体情况, 研究结果可为我国温暖带干旱性气候温室气体源与汇的研究提供数据支撑和理论基础。

Abstract

Surface pressure has a significant impact on the inversion of greenhouse gas concentrations. Observations of the column-averaged dry air mole fractions of water vapor, carbon dioxide, carbon monoxide, and methane in Dunhuang are presented based on ground-based Fourier transform infrared spectrometer (EM27/SUN). The time series of XH2O, XCO2, XCH4, and XCO from June 27 to July 21 (2018) in Dunhuang were obtained, and the sensitivity of surface pressure to the column-averaged dry air mole fractions retrieval was analyzed. The main results are as follows: The surface pressure has a significant influence on the inversion results, and the underestimated surface pressure results in low inversion results. XH2O, XCO2, XCH4, and XCO are sensitive to changes in surface pressure, and their correlation coefficients with surface pressure are higher than 0.99. The change in the total column volume with surface pressure determines the trend of column-average mole fraction with surface pressure. Compared with CO2, CH4, and CO molecules, XH2O is less sensitive to surface pressure. When the local pressure is changed by 1 hPa, ΔXH2O, ΔXCO2, ΔXCH4 and ΔXCO are 0027 8%, 0.065 9%, 0.068 6%, and 0.062%, respectively. The daily averages variation range of XH2O and XCO2 are 2 000×10-6—6 000×10-6 and 407.27×10-6—417.60×10-6, respectively. The measurement accuracies of XH2O, XCO2, XCH4, and XCO at Dunhuang site are 2.3%, 0.14%, 012%, and 1.7%, respectively. The measurement accuracies of XCO2 and XCH4 are within the requirement of TCCON. Comparing daily averaged XCO2 and XCH4 based on EM27/SUN with GOSAT, the results show that the value of XCO2 and XCH4 based on GOSAT satellite data are lower than our observations, and deviations of 7.07 (XCO2) and 0.025×10-6 (XCH4). The value of XCO2 based on WACCM data are lower than our observations with a deviation of 8×10-6 while the value of XCH4 based on WACCM data are higher than our observations with a deviation of 0.032×10-6, indicating that WACCM data does not reflect the invasion of foreign sources. These results provide a theoretical basis and first-hand observation data to understand the space-time distribution and changes of greenhouse gases in Dunhuang, China.

参考文献

[1] 李晶, 王跃思, 刘强, 等. 北京市两种主要温室气体浓度的日变化［J］. 气候与环境研究, 2006, 11(1): 49-56.

LI J, WANG Y S, LIU Q, et al.. Diurnal variation of two greenhouse gases in Beijing ［J］.Climatic and Environmental Research, 2006, 11(1): 49-56.(in Chinese)

[2] FREY M. Technische Aspekte der berwachung der akustischen Qualitt der Fahrwege im Straenverkehr Abschlussbericht ［D］. Karlsruhe Institute of Technology, 2018.

[3] 高学杰, 李栋梁, 赵宗慈, 等. 温室效应对青藏高原及青藏铁路沿线气候影响的数值模拟［J］. 高原气象, 2003, 22(5): 458-463.

GAO X J, LI D L, ZHAO Z C, et al.. Numerical simulation for influence of greenhouse effects on climatic change of Qinghai-Xizang plateau along Qinghai-Xizang railway ［J］. Plateau Meteorology, 2003, 22(5): 458-463.(in Chinese)

[4] 单昌功, 刘诚, 王薇, 等. 高分辨率太阳吸收光谱二氧化碳反演中参数的敏感性分析［J］. 光谱学与光谱分析, 2017, 37(7): 1997-2003.

SHAN CH G, LIU CH, WANG W, et al.. Analysis of sensitivity of the parameters on carbon dioxide retrieval using high-resolution solar absorption spectra ［J］.Spectroscopy and Spectral Analysis, 2017, 37(7): 1997-2003.(in Chinese)

[5] 田园, 孙友文, 谢品华, 等. 高分辨率傅里叶变换红外光谱反演环境大气中CO2浓度的质量优化方法［J］. 光谱学与光谱分析, 2017, 37(1): 48-53.

TIAN Y, SUN Y W, XIE P H, et al.. Quality optimization method for ambient CO2 inversion of high resolution Fourier transform infrared spectrum ［J］. Pectroscopy and Spectral Analysis, 2017, 37(1): 48-53.(in Chinese)

[6] 赵敏杰, 司福祺, 江宇, 等. 星载大气痕量气体差分吸收光谱仪的实验室定标［J］. 光学精密工程, 2013, 21(3): 567-574.

ZHAO M J, SI F Q, JIANG Y, et al.. In-lab calibration of space-borne differential optical absorption spectrometer ［J］. Opt. Precision Eng., 2013, 21(3): 567-574.(in Chinese)

[7] 李春光, 董磊, 王一丁, 等. 基于TDLAS和ICL的紧凑中红外痕量气体探测系统［J］. 光学精密工程, 2018, 26(8): 1855-1861.

LI CH G, DONG L, WANG Y D, et al.. Compact mid-infrared trace gas detection system based on TDLAS and ICL ［J］. Opt. Precision Eng., 2018, 26(8): 1855-1861.(in Chinese)

[8] 徐兴伟, 王薇, 刘诚, 等. 基于太阳吸收光谱观测大气一氧化碳柱总量［J］. 光谱学与光谱分析, 2018, 38(5): 1329-1334.

XU X W, WANG W, LIU C, et al.. Observations of total columns of CO based on solar absorption spectra ［J］.Spectrosc Spect Anal。 2018, 38(5): 1329-1334.(in Chinese)

[9] 程巳阳, 高闽光, 徐亮, 等. 基于直射太阳光红外吸收光谱技术的大气中CH4柱浓度遥测研究［J］.量子电子学报, 2014, 31(1): 18-24.

CHENG S Y, GAO M G, XU L, et al.. Remote sensing of CH4 column concentration in atmosphere based on direct-sun infrared absorption spectroscopy ［J］. Chinese Journal of Quantum Electronics, 2014, 31(1): 18-24.(in Chinese)

[10] KIEL M, HASE F, BLUMENSTOCK T, et al.. Comparison of XCO abundances from the total carbon column observing network and the network for the detection of atmospheric composition change measured in karlsruhe ［J］. Atmos. Meas. Tech, 2016, 9(5): 2223-2239.

[11] KIEL M, WUNCH D, WENNBERG P O, et al.. Improved retrieval of gas abundances from near-infrared solar FTIR spectra measured at the Karlsruhe TCCON station ［J］. Atmos. Meas. Tech, 2016, 9(2): 669-682.

[12] HASE F, FREY M, KIEL M, et al.. Addition of a channel for XCO observations to a portable FTIR spectrometer for greenhouse gas measurements ［J］. Atmos. Meas. Tech, 2016, 9(5): 2303-2313.

[13] FREY M, HASE F, BLUMENSTOCK T, et al.. Calibration and instrumental line shape characterization of a set of portable FTIR spectrometers for detecting greenhouse gas emissions ［J］. Atmos. Meas. Tech, 2015, 8(7): 3047-3057.

[14] GISI M, HASE F, DOHE S, et al.. XCO2-measurements with a tabletop FTS using solar absorption spectroscopy ［J］. Atmos. Meas. Tech, 2012, 5(11): 2969-2980.

[15] HASE F, HANNIGAN J W, COFFEY M T, et al.. Intercomparison of retrieval codes used for the analysis of high-resolution, ground-based FTIR measurements ［J］. Journal of Quantitative Spectroscopy and Radiative Transfer, 2004, 87(1): 25-52.

[16] 田园. 基于地基高分辨率傅里叶变换红外光谱的大气甲烷反演及应用研究［D］. 安徽: 中国科学院合肥物质科学研究院, 2018.

TIAN Y. Research on Inversion and Application of CH4 Based on Groundbased Hyperresolution Fourier Transform Infrared Spectra ［D］. Anhui: Heifei Institutes of Physical Science, Chinese Academy of Sciences, 2018. (in Chinese)

[17] WUN CH D, TOON G C, WENNBERG P O, et al.. Calibration of the total carbon column observing network using aircraft profile data ［J］. Atmos. Meas. Tech., 2010, 3: 1351-1362.

[18] WUNCH D, WENNBERG P O, TOON G C, et al.. A method for evaluating bias in global measurements of CO2 total columns from space ［J］. Atmos. Chem. Phys., 2011, 11(23): 12317-12337.

[19] 燕振宁, 马学谦. 青海高原不同地区大气水汽含量的对比分析［C］. 第35届中国气象学会年会论文集.合肥, 2018: 240-248.

YAN ZH N, MA X Q. Comparison and analysis of precipitation water vapor in different regions of Qinghai Plateau ［C］.The 35th China Academic Journal Electronic Publishing House. Hefei, 2018: 240-248.(in Chinese)

刘丹丹, 黄印博, 孙宇松, 卢兴吉, 曹振松. 地表气压对温室气体柱总量反演的敏感性分析及敦煌地区温室气体的柱总量观测[J]. 光学精密工程, 2020, 28(3): 573. LIU Dan-dan, HUANG Yin-bo, SUN Yu-song, LU Xing-ji, CAO Zhen-song. Analysis of earth surface pressure sensitivity on inversion of greenhouse gases columns and observation of greenhouse gases columns in Dunhuang in China[J]. Optics and Precision Engineering, 2020, 28(3): 573.

地表气压对温室气体柱总量反演的敏感性分析及敦煌地区温室气体的柱总量观测

关于本站 Cookie 的使用提示

全站搜索

地表气压对温室气体柱总量反演的敏感性分析及敦煌地区温室气体的柱总量观测

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索