大气气溶胶消光后向散射比反演方法研究 -

姓名
邮箱
手机号码
标题
留言内容
验证码

大气气溶胶消光后向散射比反演方法研究

doi:10.37188/CO.2021-0135

浙江大学光电科学与工程学院现代光学仪器国家重点实验室，浙江杭州 310027

基金项目:国家重点研发计划（No. 2016YFC1400900）；国家自然科学基金（No. 41775023）；浙江省自然科学基金杰出青年项目(No. LR19D050001)；中央高校基础科研项目(No. 2021XZZX019)；现代光学仪器国家重点实验室创新项目(No. MOI2021ZD01)

详细信息

作者简介:
陈　洁（1995—），女，浙江绍兴人，硕士研究生，2018年于山东大学获得学士学位，主要从事大气遥感雷达方面的研究。E-mail：21830064@zju.edu.cn
刘　东（1982—），男，辽宁大连人，博士，教授，博士生导师，2005年、2010年于浙江大学分别获得学士、博士学位，主要从事光电检测与雷达等方面的研究。E-mail：liudongopt@zju.edu.cn

中图分类号:TP958.98
计量
- 文章访问数:1148
- HTML全文浏览量:374
- PDF下载量:193
- 被引次数:0
出版历程
- 收稿日期:2021-07-05
- 修回日期:2021-08-13
- 网络出版日期:2021-09-10
- 刊出日期:2021-11-19

Retrieval methods for extinction-to-backscatter ratio of atmospheric aerosols

State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China

Funds:Supported by National Key Research and Development Program of China (No. 2016YFC1400900); National Natural Science Foundation of China (No. 41775023); Excellent Young Scientist Program of Zhejiang Provincial Natural Science Foundation of China (No. LR19D050001); Fundamental Research Funds for the Central Universities (No. 2021XZZX019); State Key Laboratory of Modern Optical Instrumentation Innovation Program (No. MOI2021ZD01)

More Information

Corresponding author:liudongopt@zju.edu.cn

摘要

摘要:气溶胶消光后向散射比是与气溶胶类型相关的一个重要光学参数，且是米散射雷达反演中的关键误差来源之一，近年来，雷达在大气气溶胶探测领域内的发展迅猛，因此调研消光后向散射比的反演方法对于气溶胶的探测与研究具有很大意义。本文根据使用的仪器及反演原理，对多种大气气溶胶消光后向散射比的反演算法进行了整理归纳，并从光学特性和微物理特性入手将这些方法联系起来。其中，光散射模型法、被动光学遥感法与雷达法联系紧密、应用广泛，为大气气溶胶的探测与研究提供了重要支撑。文章重点介绍了这3大类较为主流的反演方法，综述了相关方法的发展历程并分析了适用情况及优缺点，最后展望了未来大气气溶胶消光后向散射比反演技术的发展趋势。
- 气溶胶/
- 消光后向散射比/
- 光散射模型/
- 被动光学遥感/
- 雷达
Abstract:The extinction-to-backscatter ratio is an important optical parameter of aerosols, which is dependent on the type of aerosol. In addition, it is an important source of error in the retrieval of Mie-scattering Lidar. Nowadays, with the rapid development of Lidar in atmospheric aerosol detection, it has become a focus of research. Therefore, it is of great significance to investigate the retrieval methods of the extinction-to-backscatter ratio for aerosol detection and research. According to the choice of instruments and the retrieval principles, this paper summarizes various methods and compares them in terms of optical and microphysical properties. Among them, the light scattering model method, passive optical remote sensing method and Lidar method are closely related and widely used, which provide important support for the detection and research of atmospheric aerosols. This paper mainly introduces these three kinds of relatively mainstream retrieval methods and summarizes the development of related methods. The application, advantages and disadvantages of these methods are analyzed, and their future trends of development are forecasted.
- aerosol/
- extinction-to-backscatter ratio/
- light scattering model/
- passive optical remote sensing/
- Lidar

HTML全文

图 1各类气溶胶EBR反演法之间的联系框图

Figure 1.Block diagram of relationship between various aerosol EBR inversion methods

下载: 全尺寸图片幻灯片

图 2不同粒子对光的散射示意图

Figure 2.Schematic diagram of light scattering by different particles

下载: 全尺寸图片幻灯片

图 3大气辐射传输示意图

Figure 3.Schematic diagram of radiation transmission

下载: 全尺寸图片幻灯片

图 4入射波长为354.7 nm时的雷达大气回波信号光谱分布

Figure 4.Spectral distribution of return signals of Lidar when incident wavelength is 354.7 nm

下载: 全尺寸图片幻灯片

图 5CALIOP版本4的平流层气溶胶分类算法

Figure 5.Stratosphere aerosol classification algorithm for CALIOP version 4

下载: 全尺寸图片幻灯片

图 6 雷达后向散射信号频谱。(a)标准后向散射雷达；(b)HSRL中附加的频谱识别

Figure 6.Spectra of lidar backscatter signal. (a) Standard backscatter lidar; (b) additional spectral discrimination in HSRL

下载: 全尺寸图片幻灯片

参考文献 (36)

[1]	陈良富, 李莘莘, 陶金花, 等. 气溶胶遥感定量反演研究与应用[M]. 北京: 科学出版社, 2011. CHEN L F, LI SH SH, TAO J H,et al..Research and Application of Aerosol Remote Sensing Quantitative Inversion[M]. Beijing: Science Press, 2001. (in Chinese)
[2]	EVANS B T N. Sensitivity of the backscatter/extinction ratio to changes in aerosol properties: implications for lidar[J].Applied Optics, 1988, 27(15): 3299-3305.doi:10.1364/AO.27.003299
[3]	FERNALD F G. Analysis of atmospheric lidar observations: some comments[J].Applied Optics, 1984, 23(5): 652-653.doi:10.1364/AO.23.000652
[4]	KIM M H, OMAR A H, TACKETT J L,et al. The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm[J].Atmospheric Measurement Techniques, 2018, 11(11): 6107-6135.doi:10.5194/amt-11-6107-2018
[5]	SALGUEIRO V, COSTA M J, GUERRERO-RASCADO J L,et al. Characterization of forest fire and Saharan desert dust aerosols over south-western Europe using a multi-wavelength Raman lidar and Sun-photometer[J].Atmospheric Environment, 2021, 252: 118346.doi:10.1016/j.atmosenv.2021.118346
[6]	ZHAO G, ZHAO CH SH, KUANG Y,et al. Impact of aerosol hygroscopic growth on retrieving aerosol extinction coefficient profiles from elastic-backscatter lidar signals[J].Atmospheric Chemistry and Physics, 2017, 17(19): 12133-12143.doi:10.5194/acp-17-12133-2017
[7]	DIONISI D, BARNABA F, DIÉMOZ H,et al. A multiwavelength numerical model in support of quantitative retrievals of aerosol properties from automated lidar ceilometers and test applications for AOT and PM₁₀estimation[J].Atmospheric Measurement Techniques, 2018, 11(11): 6013-6042.doi:10.5194/amt-11-6013-2018
[8]	GASTEIGER J, WIEGNER M. MOPSMAP v1.0: a versatile tool for the modeling of aerosol optical properties[J].Geoscientific Model Development, 2018, 11(7): 2739-2762.doi:10.5194/gmd-11-2739-2018
[9]	DOHERTY S J, ANDERSON T L, CHARLSON R J. Measurement of the lidar ratio for atmospheric aerosols with a 180° backscatter nephelometer[J].Applied Optics, 1999, 38(9): 1823-1832.doi:10.1364/AO.38.001823
[10]	童奕澄, 童学东, 张凯, 等. 偏振雷达增益比定标方法对比研究[J]. 中国光学,2021,14(3):685-703.doi:10.37188/CO.2020-0136 TONG Y CH, TONG X D, ZHANG K,et al. Polarization lidar gain ratio calibration method: a comparison[J].Chinese Optics, 2021, 14(3): 685-703. (in Chinese)doi:10.37188/CO.2020-0136
[11]	曲艺. 大气光学遥感监测技术现状与发展趋势[J]. 中国光学,2013,6(6):834-840. QU Y. Technical status and development tendency of atmosphere optical remote and monitoring[J].Chinese Optics, 2013, 6(6): 834-840. (in Chinese)
[12]	DUBOVIK O, SINYUK A, LAPYONOK T,et al. Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust[J].Journal of Geophysical Research:Atmospheres, 2006, 111(D11): D11208.doi:10.1029/2005JD006619
[13]	YANG P, KATTAWAR G W, LIOU K N,et al. Comparison of Cartesian grid configurations for application of the finite-difference time-domain method to electromagnetic scattering by dielectric particles[J].Applied Optics, 2004, 43(23): 4611-4624.doi:10.1364/AO.43.004611
[14]	张朝阳, 苏林, 陈良富. 中国典型地区气溶胶雷达比反演与分析[J]. 中国 ,2013,40(5):0513002.doi:10.3788/CJL201340.0513002 ZHANG ZH Y, SU L, CHEN L F. Retrieval and analysis of aerosol lidar ratio at several typical regions in China[J].Chinese Journal of Lasers, 2013, 40(5): 0513002. (in Chinese)doi:10.3788/CJL201340.0513002
[15]	WU M X, LIU X H, YU H B,et al. Understanding processes that control dust spatial distributions with global climate models and satellite observations[J].Atmospheric Chemistry and Physics, 2020, 20(22): 13835-13855.doi:10.5194/acp-20-13835-2020
[16]	陶金花, 李小英, 王子峰, 等. 大气遥感定量反演算法与系统[M]. 北京: 科学出版社, 2014. TAO J H, LI X Y, WANG Z F,et al..Atmospheric Remote Sensing Quantitative Inversion Algorithm and System[M]. Beijing: Science Press, 2014. (in Chinese)
[17]	李正强, 谢一凇, 洪津, 等. 星载对地观测偏振传感器及其大气遥感应用[J]. 大气与环境光学学报,2019,14(1):2-17. LI ZH Q, XIE Y S, HONG J,et al. Polarimetric satellite sensors for earth observation and applications in atmospheric remote sensing[J].Journal of Atmospheric and Environmental Optics, 2019, 14(1): 2-17. (in Chinese)
[18]	马小雨, 陈正华, 宿鑫, 等. GF-4增强型地表反射率库支持法的气溶胶光学厚度反演[J]. 遥感学报,2020,24(5):578-595. MA X Y, CHEN ZH H, SU X,et al. GF-4 aerosol retrieval study of enhanced surface reflectance library support algorithm[J].Journal of Remote Sensing, 2020, 24(5): 578-595. (in Chinese)
[19]	CHEN X F, DE LEEUW G, AROLA A. et al. Joint retrieval of the aerosol fine mode fraction and optical depth using MODIS spectral reflectance over northern and eastern China: artificial neural network method[J].Remote Sensing of Environment, 2020, 249: 112006.doi:10.1016/j.rse.2020.112006
[20]	BRÉON F M. Aerosol extinction-to-backscatter ratio derived from passive satellite measurements[J].Atmospheric Chemistry and Physics, 2013, 13(17): 8947-8954.doi:10.5194/acp-13-8947-2013
[21]	COMERÓN A, MUÑOZ-PORCAR C, ROCADENBOSCH F,et al. Current research in lidar technology used for the remote sensing of atmospheric aerosols[J].Sensors, 2017, 17(6): 1450.doi:10.3390/s17061450
[22]	田晓敏, 刘东, 徐继伟, 等. 大气探测雷达技术综述[J]. 大气与环境光学学报,2018,13(5):321-341. TIAN X M, LIU D, XU J W,et al. Review of lidar technology for atmosphere monitoring[J].Journal of Atmospheric and Environmental Optics, 2018, 13(5): 321-341. (in Chinese)
[23]	刘东, 刘群, 白剑, 等. 星载雷达CALIOP数据处理算法概述[J]. 红外与工程,2017,46(12):1202001.doi:10.3788/IRLA201746.1202001 LIU D, LIU Q, BAI J,et al. Data processing algorithms of the space-borne lidar CALIOP: a review[J].Infrared and Laser Engineering, 2017, 46(12): 1202001. (in Chinese)doi:10.3788/IRLA201746.1202001
[24]	JOSSET D, ROGERS R, PELON J,et al. CALIPSO lidar ratio retrieval over the ocean[J].Optics Express, 2011, 19(19): 18696-18706.doi:10.1364/OE.19.018696
[25]	SU J, MCCORMICK M P. Using multi-wavelength Mie-Raman lidar to measure low-level cloud properties[J].Journal of Quantitative Spectroscopy and Radiative Transfer, 2019, 237: 106610.doi:10.1016/j.jqsrt.2019.106610
[26]	BOVCHALIUK V, GOLOUB P, PODVIN T,et al. Comparison of aerosol properties retrieved using GARRLiC, LIRIC, and Raman algorithms applied to multi-wavelength lidar and sun/sky-photometer data[J].Atmospheric Measurement Techniques, 2016, 9(7): 3391-3405.doi:10.5194/amt-9-3391-2016
[27]	CÓRDOBA-JABONERO C, LOPES F J S, LANDULFO E,et al. Diversity on subtropical and polar cirrus clouds properties as derived from both ground-based lidars and CALIPSO/CALIOP measurements[J].Atmospheric Research, 2017, 183: 151-165.doi:10.1016/j.atmosres.2016.08.015
[28]	华雯丽, 韩颖, 乔瀚洋, 等. 敦煌沙尘气溶胶质量浓度垂直特征个例分析[J]. 高原气象,2018,37(5):1428-1439. HUA W L, HAN Y, QIAO H Y,et al. Profiling of dust aerosol mass concentration over Dunhuang: case studies[J].Plateau Meteorology, 2018, 37(5): 1428-1439. (in Chinese)
[29]	TAO Z M, LIU ZH Y, WU D,et al. Determination of aerosol extinction-to-backscatter ratios from simultaneous ground-based and spaceborne lidar measurements[J].Optics Letters, 2008, 33(24): 2986-2988.doi:10.1364/OL.33.002986
[30]	SASANO Y, BROWELL E V. Light scattering characteristics of various aerosol types derived from multiple wavelength lidar observations[J].Applied Optics, 1989, 28(9): 1670-1679.doi:10.1364/AO.28.001670
[31]	KIM D, CHA H. Rotational Raman lidar for obtaining aerosol scattering coefficients[J].Optics Letters, 2005, 30(13): 1728-1730.doi:10.1364/OL.30.001728
[32]	ANSMANN A, WANDINGER U, RIEBESELL M,et al. Independent measurement of extinction and backscatter profiles in cirrus clouds by using a combined Raman elastic-backscatter lidar[J].Applied Optics, 1992, 31(33): 7113-7131.doi:10.1364/AO.31.007113
[33]	POVEY A C, GRAINGER R G, PETERS D M,et al. Retrieval of aerosol backscatter, extinction, and lidar ratio from Raman lidar with optimal estimation[J].Atmospheric Measurement Techniques, 2014, 7(3): 757-776.doi:10.5194/amt-7-757-2014
[34]	LI S W, DI H G, WANG Q Y,et al. Retrieval of the aerosol extinction coefficient of 1064 nm based on high-spectral-resolution lidar[J].Journal of Quantitative Spectroscopy and Radiative Transfer, 2020, 256: 107298.doi:10.1016/j.jqsrt.2020.107298
[35]	刘东, 周雨迪, 朱小磊, 等. 大气海洋高光谱分辨率雷达鉴频特性研究[J]. 大气与环境光学学报,2020,15(1):48-54. LIU D, ZHOU Y D, ZHU X L,et al. Investigation on discrimination characteristics of atmospheric and oceanic high-spectral-resolution lidar[J].Journal of Atmospheric and Environmental Optics, 2020, 15(1): 48-54. (in Chinese)
[36]	戎宇航, 沈雪, 王南朝, 等. 双波长高光谱分辨率雷达光谱鉴频器设计[J]. 光学学报,2021,41(4):0401001.doi:10.3788/AOS202141.0401001 RONG Y H, SHEN X, WANG N CH,et al. Design of dual-wavelength spectral discriminator for high-spectral-resolution lidar[J].Acta Optica Sinica, 2021, 41(4): 0401001. (in Chinese)doi:10.3788/AOS202141.0401001