暗目标法的Himawari-8静止卫星数据气溶胶反演
Study on aerosol optical depth retrieval over land from Himawari-8 data based on dark target method
- 2018年22卷第1期 页码:38-50
纸质出版日期: 2018-1 ,
录用日期: 2017-5-15
DOI: 10.11834/jrs.20187033
扫 描 看 全 文
浏览全部资源
扫码关注微信
纸质出版日期: 2018-1 ,
录用日期: 2017-5-15
扫 描 看 全 文
葛邦宇, 杨磊库, 陈兴峰, 李正强, 梅笑冬, 刘李. 2018. 暗目标法的Himawari-8静止卫星数据气溶胶反演. 遥感学报, 22(1): 38–50
Ge B Y, Yang L K, Chen X F, Li Z Q, Mei X D and Liu L. 2018. Study on aerosol optical depth retrieval over land from Himawari-8 data based on dark target method. Journal of Remote Sensing, 22(1): 38–50
Himawari-8 (H8) 是由日本气象厅发射的新一代静止气象卫星,可实现10 min/次的高频次对地观测,搭载的AHI (Advanced Himawari Imager) 传感器设置有与MODIS暗目标气溶胶反演算法所需的类似波段。本文参考暗目标算法构建了针对该卫星传感器的陆地气溶胶反演算法:首先,通过基于地基站点观测数据的精确大气校正,统计得到短波红外与可见光波段的地表反射率比值关系,将此作为先验知识用于地—气解耦时的反射率估计;然后,初步假设大陆型气溶胶类型,利用辐射传输模型建立查找表;最后,通过模拟与卫星观测的表观反射率误差最小实现气溶胶光学厚度反演解算。选取2016年5月覆盖京津冀地区的观测数据进行测试,将反演结果与对应时间的MODIS气溶胶光学厚度产品进行对比验证,空间分布趋势一致、相关性较高,相关系数
R
达到0.852;通过与地基观测网AERONET站点实测数据对比验证,所有站点的相关系数
R
2
均大于0.88,精度较高。利用反演的高时间分辨率产品,分析了京津冀地区的大气空间分布和日变化情况,结果表明:采用暗目标法对H8静止卫星陆地气溶胶光学厚度反演具有一定的潜力和可行性,能反映气溶胶的高时间变化信息,有望成为大气环境污染变化监测新的重要手段。
Himawari-8 (H8)
as a new generation of geostationary meteorological satellites that observes full-disk images (images of the Earth as seen from the satellite) per 10 min
was launched by Japan Meteorological Agency to investigate aerosol characteristics. The Advanced Himawari Imager (AHI) onboard Himawari-8 has similar spectral bands with Moderate Resolution Imaging Spectroradiometer (MODIS). This study applies the Dark Target (DT) method for Aerosol Optical Depth (AOD) retrieval from AHI data. The atmospheric effect is established for the AHI data over AErosol RObotic NETwork sites. The ratio of surface reflectance between the shortwave infrared and visible bands is then obtained. This ratio serves as a priori knowledge for the surface reflectance estimation in the atmosphere-surface coupling model. Assuming that the aerosol type is continental
we build a look-up table through the radiative transfer model. With the retrieval algorithm
the AOD is determined in the case of a minimum difference between simulated apparent reflectance and satellite observations. The algorithm was used to retrieve AOD over the Beijing-Tianjing-Hebei area of China in May 2016. H8 AOD products were compared with MODIS products
and the results revealed a good spatial coincidence
with the correlation coefficient
R
being 0.852. The H8 AOD products were validated with AERONET observations
and they showed good linear relations
with the correlation coefficient
R
2
being better than 0.88. The high temporal resolution products were used to analyze aerosol spatial distribution and diurnal variation in the Beijing-Tianjin-Hebei region. Results show that H8 AOD retrieval based on the DT method has certain feasibility and potential. AOD products can express the high temporal variation of aerosol and are thus potentially useful in atmospheric environmental pollution monitoring.
葵花8 (Himawari-8)暗目标法地表反射率气溶胶光学厚度京津冀
Himawari-8dark target methodsurface reflectanceaerosol optical depthBeijing-Tianjin-Hebei area
Bessho K, Date K, Hayashi M, Ikeda A, Imai T, Inoue H, Kumagai Y, Miyakawa T, Murata H, Ohno T, Okuyama A, Oyama R, Sasaki Y, Shimazu Y, Shimoji K, Sumida Y, Suzuki M, Taniguchi H, Tsuchiyama H, Uesawa D, Yokota H and Yoshida R. 2016. An introduction to Himawari-8/9—Japan’s new-generation geostationary meteorological satellites. Journal of the Meteorological Society of Japan Serise II, 94(2): 151–183
陈良富, 李莘莘, 陶金花, 王中挺. 2011. 气溶胶遥感定量反演研究与应用. 北京: 科学出版社
Chen L F, Li S S, Tao J H and Wang Z T. 2011. Research and Application of Aerosol Remote Sensing Quantitative Inversion. Beijing: Science Press
Chu D A, Kaufman Y J, Zibordi G, Chern J D, Mao J T, Li C C and Holben B N. 2003. Global monitoring of air pollution over land from the Earth Observing System-Terra Moderate Resolution Imaging Spectroradiometer (MODIS). Journal of Geophysical Research Atmosphere, 108(D21): 4661
Eck T F, Holben B N, Reid J S, Dubovik O, Smirnov A, O’Neill N T, Slutsker I and Kinne S. 1999. Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols. Journal of Geophysical Research: Atmospheres, 104(D24): 31333–31349
高玲, 任通, 李成才, 杨东伟, 石光明, 毛节泰. 2012. 利用静止卫星MTSAT反演大气气溶胶光学厚度. 气象学报, 70(3): 598–608
Gao L, Ren T, Li C C, Yang D W, Shi G M and Mao J T. 2012. A retrieval of the atmospheric aerosol optical depth from MTSAT. Acta Meteorologica Sinica, 70(3): 598–608 (
Guerrieri L, Corradini S, Pugnaghi S and Santangelo R. 2007. An aerosol optical thickness retrieval algorithm for Meteosat Second Generation (MSG) data over land: applications to the Mediterranean area//Proceedings of the SPIE Volume 6745, Remote Sensing of Clouds and the Atmosphere XII. Florence, Italy: SPIE: 67450D [DOI: 10.1117/12.736648]
Gupta P, Levy R C, Mattoo S, Remer L A and Munchak L A. 2016. A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm. Atmospheric Measurement Techniques, 9(7): 3293–3308
Hansen J, Sato M, Kharecha P and von Schuckmann K. 2011. Earth’s energy imbalance and implications. Atmospheric Chemistry and Physics Discussions, 11(9): 27031–27105
贺克斌, 杨复沫, 段凤魁, 马永亮. 2011. 大气颗粒物与区域复合污染. 北京: 科学出版社
He K B, Yang F M, Duan F K and Ma Y L. 2011. Atmospheric Particulate Matter and Regional Complex Pollution. Beijing: Science Press
Herman M, Deuzé J L, Devaux C, Goloub P, Bréon F M and Tanré D. 1997. Remote sensing of aerosols over land surfaces including polarization measurements and application to POLDER measurements. Journal of Geophysical Research: Atmospheres, 102(D14): 17039–17049
Ignatov A and Stowe L. 2000. Physical basis, premises, and self-consistency checks of aerosol retrievals from TRMM VIRS. Journal of Applied Meteorology, 39(12): 2259–2277
IPCC. 2014. Climate Change 2013: The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York: Cambridge University Press
Kaufman Y J, Tanré D, Remer L A, Vermote E F, Chu A and Holben B N. 1997. Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer. Journal of Geophysical Research: Atmospheres, 102(D14): 17051–17067
Kotchenova S Y, Vermote E F, Levy R and Lyapustin A. 2008. Radiative transfer codes for atmospheric correction and aerosol retrieval: intercomparison study. Applied Optics, 47(13): 2215–2226
Kurihara Y, Murakami H and Kachi M. 2016. Sea surface temperature from the new Japanese geostationary meteorological Himawari-8 satellite. Geophysical Research Letters, 43(3): 1234–1240
Levy R C, Mattoo S, Munchak L A, Remer L A, Sayer A M and Hsu N C. 2013. The Collection 6 MODIS aerosol products over land and ocean. Atmospheric Measurement Techniques Discussions, 6(11): 159–259
Levy R C, Remer L A, Mattoo S, Vermote E F and Kaufman Y J. 2007. Second-generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance. Journal of Geophysical Research Atmospheres, 112: D13211
Li K T, Li Z Q, Li D H, Li W, Blarel L, Goloub P, Benjamin T, Xu H, Xie Y S, Hou W Z, Li L and Chen X F. 2015. Transfer method to calibrate the normalized radiance for a CE318 Sun/sky radiometer. Chinese Optics Letters, 13(4): 041001
Liu Y, Sarnat J A, Coull B A, Koutrakis P and Jacob D J. 2004. Validation of Multiangle Imaging Spectroradiometer (MISR) aerosol optical thickness measurements using Aerosol Robotic Network (AERONET) observations over the contiguous United States. Journal of Geophysical Research: Atmospheres, 109(D6): D06205
毛节泰, 刘莉, 张军华. 2001. GMS5卫星遥感气溶胶光学厚度的试验研究. 气象学报, 59(3): 352–359
Mao J T, Liu L and Zhang J H. 2001. GMS5 remote sensing of aerosol optical thickness over chaohu lake. Acta Meteorologica Sinica, 59(3): 352–359 (
Moulin C F, Guillard F, Dulac and Lambert C E. 1997. Long-term daily monitoring of Saharan dust load over ocean using Meteosat ISCCP-B2 data: 1. Methodology and preliminary results for 1983–1994 in the Mediterranean. Journal of Geophysical Research: Atmospheres, 102(D14): 16947–16958
Prados A I, Kondragunta S, Ciren P and Knapp K R. 2007. GOES Aerosol/Smoke Product (GASP) over North America: comparisons to AERONET and MODIS observations. Journal of Geophysical Research: Atmospheres, 112(D15): D15201
Remer L A, Kaufman Y J, Tanré D, Mattoo S, Chu D A, Martins J V, Li R R, Ichoku C, Levy R C, Kleidman R G, Eck T F, Vermote E and Holben B N. 2005. The MODIS aerosol algorithm, products, and validation. Journal of the Atmospheric Sciences, 62(4): 947–973
Sekiyama T T, Yumimoto K, Tanaka T Y, Nagao T, Kikuchi M and Murakami H. 2016. Data assimilation of Himawari-8 aerosol observations: Asian dust forecast in June 2015. Scientific Online Letters on the Atmosphere Sola, 12: 86–90
Shang H Z, Chen L F, Letu H, Zhao M, Li S S and Bao S H. 2017. Development of a daytime cloud and haze detection algorithm for Himawari-8 satellite measurements over central and eastern China. Journal of Geophysical Research: Atmospheres, 122(6): 3528–3543
Uesawa D. 2016. Aerosol Optical Depth product derived from Himawari-8 data for Asian dust monitoring[DB/OL].
Wang J, Christopher S A, Reid J S, Maring H, Savoie D, Holben B N, Livingston J M, Russell P B and Yang S K. 2003. GOES 8 retrieval of dust aerosol optical thickness over the Atlantic Ocean during PRIDE. Journal of Geophysical Research: Atmospheres, 108(D19): 8595
王新强, 杨世植, 朱永豪, 易维宁. 2003. 基于6S模型从MODIS图像反演陆地上空大气气溶胶光学厚度. 量子电子学报, 20(5): 629–634
Wang X Q, Yang S Z, Zhu Y H and Yi W N. 2003. Aerosol optical thickness retrieval over land from MODIS data based on the inversion of the 6S model. Chinese Journal of Quantum Electronics, 20(5): 629–634 (
王跃思, 张军科, 王莉莉, 胡波, 唐贵谦, 刘子锐, 孙扬, 吉东生. 2014. 京津冀区域大气霾污染研究意义、现状及展望. 地球科学进展, 29(3): 388–396
Wang Y S, Zhang J K, Wang L L, Hu B, Tang G Q, Liu Z R, Sun Y and Ji D S. 2014. Researching significance, status and expectation of haze in Beijing-Tianjin-Hebei Region. Advances in Earth Science, 29(3): 388–396 (
王中挺, 辛金元, 贾松林, 厉青, 陈良富, 赵少华. 2015. 利用暗目标法从高分一号卫星16m相机数据反演气溶胶光学厚度. 遥感学报, 19(3): 530–538
Wang Z T, Xin J Y, Jia S L, Li Q, Chen L F and Zhao S H. 2015. Retrieval of AOD from GF-1 16 m camera via DDV algorithm. Journal of Remote Sensing, 19(3): 530–538 (
Yu F F and Wu X Q. 2016. Radiometric inter-calibration between Himawari-8 AHI and S-NPP VIIRS for the solar reflective bands. Remote Sensing, 8(3): 165
Yumimoto K, Nagao T M, Kikuchi M, Sekiyama T T, Murakami H, Tanaka T Y, Ogi A, Irie H, Khatri P, Okumura H, Arai K, Morino I, Uchino O and Maki T. 2016. Aerosol data assimilation using data from Himawari-8, a next-generation geostationary meteorological satellite. Geophysical Research Letters, 43(11): 5886–5894
张军华, 斯召俊, 毛节泰, 王美华. 2003. GMS卫星遥感中国地区气溶胶光学厚度. 大气科学, 27(1): 23–35
Zhang J H, Si Z J, Mao J T and Wang M H. 2003. Remote sensing aerosol optical depth over China with GMS-5 satellite. Chinese Journal of Atmospheric Sciences, 27(1): 23–35 (
张婷媛, 林文鹏, 陈家治, 宗玮. 2009. 基于FLAASH和6S模型的Spot 5大气校正比较研究. 光电子·激光, 20(11): 1471–1473
Zhang T Y, Lin W P, Chen J Z and Zong W. 2009. Comparative study on atmospheric correction methods of FLAASH and 6S model based on Spot 5. Journal of Optoelectronics·Laser, 20(11): 1471–1473 (
Zou X, Zhuge X and Weng F. 2016. Characterization of bias of advanced himawari imager infrared observations from NWP background simulations using CRTM and RTTOV. Journal of Atmospheric and Oceanic Technology, 33(12): 2553–2567
相关作者
相关机构