Review of cloud polarimetric remote sensing

  • role: First author第一作者
  • Affiliation:

    College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241003, China

    Engineering Technology Research Center of Resources Environment and GIS, Wuhu 241003, China

  • Email:wangyuyao@ahnu.edu.cn
  • Introduction:E-mail wangyuyao@ahnu.edu.cn
WANG Yuyao14,  
  • role: Corresponding author通信作者
  • Affiliation:

    College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241003, China

    Engineering Technology Research Center of Resources Environment and GIS, Wuhu 241003, China

  • Email:jinjima@ahnu.edu.cn
  • Introduction:E-mail jinjima@ahnu.edu.cn
MA Jinji14*,  
  • Affiliation:

    College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241003, China

    Engineering Technology Research Center of Resources Environment and GIS, Wuhu 241003, China

LI Jinghan14,  
  • Affiliation:

    Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China

HONG Jin2,  
  • Affiliation:

    State Environmental Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

LI Zhengqiang3

ملخص

Clouds are collections of water droplets or ice crystal colloids suspended in the atmosphere. They are a visible manifestation of the Earth’s massive water cycle, which play an important role in global climate. Since the radiation intensity signal cannot accurately detect the internal physical characteristics of thick clouds, especially convective clouds, high-quality cloud observations cannot be achieved only by using this signal. Polarimetric remote sensing can describe the spectral characteristics of intensity, directions, phase positions, and polarization states of light, so as to expand the volumes and dimensions of the information observed. It can detect the size, shape, and other microphysical parameters, showing unique application advantages in cloud remote sensing.A wealth of literature on the development of polarimetric sensors can be found, for example, POLDER launched by France, ASP designed by the United States, and DPC developed by China. This paper summarizes the characteristics of internationally developed landmark polarimetric sensors and introduces the polarimetric sensor that will be launched soon. It is found that the development of polarimetric sensors underwent three main periods. During the first period, polarimetric sensors had low spatial resolution, fewer polarization spectrums, fewer angles, and low polarimetric accuracy. During the second period, the four elements mentioned above have been improved. In the third period, the sensors were developed into products with high spatial resolution, more polarization spectrum, large angles, and high polarimetric accuracy. The accessible spatial resolution, polarization data, and polarimetric accuracy were all greatly improved.In addition, this paper discusses the research on polarization data of cloud detection, physical characteristics, and optical characteristics of clouds. Starting from a series of problems existing in traditional remote sensing observation methods in cloud research, including poor cloud detection of accuracy, physical and optical characteristics, etc., the advantages of polarization detection are revealed through a detailed introduction to the classical polarization cloud parameter algorithms. Moreover, the development history of cloud polarimetric remote sensing research and the critical role played by the application of polarization data in cloud-related studies are explored.By reviewing the development of polarimetric sensors and the evolution of cloud remote sensing algorithms in the past three decades, we found that the polarimetric accuracy, and spatial and time resolution were improved as the number of polarimetric sensors increased. However, the acquired polarimetric signal is increasingly complex. Therefore, when designing the algorithm of cloud remote sensing, the factors we should consider will be fewer. In contrast, the algorithm will be more rigorous, and the inversion accuracy of cloud parameters will be higher. Considering that with the accumulation of experience and the development of instruments, it is believed that the polarization data will make significant progress in optimizing cloud parameters.

مفهوم

atmospheric remote sensing;polarization;POLDER;APS;DPC;cloud;vector radiative transfer;inversion algorithm

References

  1. 1.
    Alexandrov M D, Cairns B and Mishchenko M I. 2012. Rainbow Fourier transform. Journal of Quantitative Spectroscopy and Radiative Transfer, 113(18): 2521-2535
  2. 2.
    Alexandrov M D, Cairns B, Sinclair K, Wasilewski A P, Ziemba L, Crosbie E, Moore R, Hair J, Scarino A J, Hu Y X, Stamnes S, Shook M A and Chen G. 2018. Retrievals of cloud droplet size from the research scanning polarimeter data: validation using in situ measurements. Remote Sensing of Environment, 210: 76-95
  3. 3.
    Alexandrov M D, Cairns B, Wasilewski A P, Ackerman A S, Mcgill M J, Yorks J E, Hlavka D L, Platnick S E, Arnold G T, van Diedenhoven B, Chowdhary J, Ottaviani M and Knobelspiesse K D. 2015. Liquid water cloud properties during the Polarimeter Definition Experiment (PODEX). Remote Sensing of Environment, 169: 20-36
  4. 4.
    Alexandrov M D, Miller D J, Rajapakshe C, Fridlind A, van Diedenhoven B, Cairns B, Ackerman A S and Zhang Z B. 2020. Vertical profiles of droplet size distributions derived from cloud-side observations by the research scanning polarimeter: tests on simulated data. Atmospheric Research, 239: 104924
  5. 5.
    Andre Y and Li L. 1997. Instrumental concept and performances of the POLDER instrument. (PART 1). Infrared, (11): 1-8
  6. 6.
    Baum B A, Frey R A, Mace G G, Harkey M K and Yang P. 2003. Nighttime multilayered cloud detection using MODIS and ARM data. Journal of Applied Meteorology and Climatology, 42(7): 905-919
  7. 7.
    Bréon F M and Colzy S. 1999. Cloud detection from the spaceborne POLDER instrument and validation against surface synoptic observations. Journal of Applied Meteorology, 38(6): 777-785
  8. 8.
    Bréon F M and Doutriaux-Boucher M. 2005. A comparison of cloud droplet radii measured from space. IEEE Transactions on Geoscience and Remote Sensing, 43(8): 1796-1805
  9. 9.
    Bréon F M and Goloub P. 1998. Cloud droplet effective radius from spaceborne polarization measurements. Geophysical Research Letters, 25(11): 1879-1882
  10. 10.
    Buriez J C, Vanbauce C, Parol F, Goloub P, Herman M, Bonnel B, Fouquart Y, Couvert P and Seze G. 1997. Cloud detection and derivation of cloud properties from POLDER. International Journal of Remote Sensing, 18(13): 2785-2813
  11. 11.
    Cairns B, Russell E E, LaVeigne J D and Tennant P M W. 2003. Research scanning polarimeter and airborne usage for remote sensing of aerosols//Proceedings Volume 5158, Polarization Science and Remote Sensing. San Diego, California: SPIE: 33-44
  12. 12.
    Carney T Q and Vincent D G. 1986. Meso-synoptic scale interactions during AVE/SESAME I, 10 11 April 1979. Part I: theoretical development of interaction equations. Monthly Weather Review, 114(2): 344-352
  13. 13.
    Chang Y Y. 2020. Study on the Retrievals of Cloud Properties based on Multi-Directional Polarimetric Data. Hefei: University of Science and Technology of China
  14. 14.
    Chang Y Y, Sun B, Huang C, Hong J and Qiao Y L. 2020. Cloud detection and parameter inversion using multi-directional polarimetric observations. Acta Optica Sinica, 40(11): 1101002
  15. 15.
    Chen F N, Huang C, Hong J, Luo D G, Sun L, Sun X B and Wei W. 2019. In Flight Radiation evaluation and validation of Directional Polarimetric Camera. Aerospace Shanghai, 36(S2): 126-136, 172
  16. 16.
    Chen L F, Shang H Z, Fan M, Tao J H, Husi L T, Zhang Y, Wang H M, Cheng L X, Zhang X X, Wei L S, Li M Y, Zou M M and Liu D D. 2021. Mission overview of the GF-5 satellite for atmospheric parameter monitoring. National Remote Sensing Bulletin, 25(9): 1917-1931
  17. 17.
    Chen X, Yang D X, Cai Z N, Liu Y and Spurr R J D. 2017. Aerosol retrieval sensitivity and error analysis for the cloud and aerosol polarimetric imager on board TanSat: the effect of multi-angle measurement. Remote Sensing, 9(2): 183
  18. 18.
    Chen Z T, Sun X B and Qiao Y L. 2018. Cloud detection over ocean from PARASOL/POLDER3 satellite data. Journal of Remote Sensing, 22(6): 996-1004
  19. 19.
    Chowdhary J, Cairns B, Mishchenko M and Travis L. 2001. Retrieval of aerosol properties over the ocean using multispectral and multiangle photopolarimetric measurements from the Research Scanning Polarimeter. Geophysical Research Letters, 28(2): 243-246
  20. 20.
    Chowdhary J, Cairns B, Mishchenko M I, Hobbs P V, Cota G F, Redemann J, Rutledge K, Holben B N and Russell E. 2005. Retrieval of aerosol scattering and absorption properties from photopolarimetric observations over the ocean during the CLAMS experiment. Journal of the Atmospheric Sciences, 62(4): 1093-1117
  21. 21.
    Christodoulou C I, Michaelides S C and Pattichis C S. 2003. Multifeature texture analysis for the classification of clouds in satellite imagery. IEEE Transactions on Geoscience and Remote Sensing, 41(11): 2662-2668
  22. 22.
    Diner D J, Beckert J C, Reilly T H, Bruegge C J, Conel J E, Kahn R A, Martonchik J V, Ackerman T P, Davies R, Gerstl S A W, Gordon H R, Muller J P, Myneni R B, Sellers P J, Pinty B and Verstraete M M. 1998. Multi-angle Imaging SpectroRadiometer (MISR)-instrument description and experiment overview. IEEE Transactions on Geoscience and Remote Sensing, 36(4): 1072-1087
  23. 23.
    Diner D J, Boland S W, Brauer M, Bruegge C, Burke K A, Chipman R, Di Girolamo L, Garay M J, Hasheminassab S, Hyer E, Jerrett M, Jovanovic V, Kalashnikova O V, Liu Y, Lyapustin A I, Martin R V, Nastan A, Ostro B D, Ritz B, Schwartz J, Wang J and Xu F. 2018a. Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA. Journal of Applied Remote Sensing, 12(4): 042603
  24. 24.
    Diner D J, Boland S W, Brauer M, Bruegge C, Burke K A, Chipman R, Di Girolamo L, Garay M J, Hasheminassab S, Hyer E, Jerrett M, Jovanovic V, Kalashnikova O V, Liu Y, Lyapustin A I, Martin R V, Nastan A, Ostro B D, Ritz B, Schwartz J, Wang J and Xu F. 2018b. Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA. Journal of Applied Remote Sensing, 12(4): 042603
  25. 25.
    Diner D J, Braswell B H, Davies R, Gobron N, Hu J N, Jin Y F, Kahn R A, Knyazikhin Y, Loeb N, Muller J P, Nolin A W, Pinty B, Schaaf C B, Seiz G and Stroeve J. 2005. The value of multiangle measurements for retrieving structurally and radiatively consistent properties of clouds, aerosols, and surfaces. Remote Sensing of Environment, 97(4): 495-518
  26. 26.
    Fougnie B and Bach R. 2009. Monitoring of radiometric sensitivity changes of space sensors using deep convective clouds: operational application to PARASOL. IEEE Transactions on Geoscience and Remote Sensing, 47(3): 851-861
  27. 27.
    Fougnie B, Marbach T, Lacan A, Lang R, Schlüssel P, Poli G, Munro R and Couto A B. 2018b. The multi-viewing multi-channel multi-polarisation imager-overview of the 3MI polarimetric mission for aerosol and cloud characterization. Journal of Quantitative Spectroscopy and Radiative Transfer, 219: 23-32
  28. 28.
    Fougnie B, Marbach T, Lacan A, Schlüssel P, Lang R, Poli G and Munro R. 2018a. The 3MI mission on-board EPS-SG: a multi-spectral multi-polarization multi-directional imager for operational characterization of aerosol and cloud//Proceedings Volume 10764, Earth Observing Systems XXIII. San Diego, California: SPIE
  29. 29.
    Frouin R J, Franz B A, Ibrahim A, Knobelspiesse K, Ahmad Z, Cairns B, Chowdhary J, Dierssen H M, Tan J, Dubovik O, Huang X, Davis A B, Kalashnikova O, Thompson D R, Remer L A, Boss E, Coddington O, Deschamps P Y, Gao B C, Gross L, Hasekamp O, Omar A, Pelletier B, Ramon D, Steinmetz F and Zhai P W. 2019. Atmospheric correction of satellite ocean-color imagery during the PACE era. Frontiers in Earth Science, 7: 145
  30. 30.
    Fu G L, Hasekamp O, Rietjens J, Smit M, Di Noia A, Cairns B, Wasilewski A, Diner D, Seidel F, Xu F, Knobelspiesse K, Gao M, Da Silva A, Burton S, Hostetler C, Hair J and Ferrare R. 2020. Aerosol retrievals from different polarimeters during the ACEPOL campaign using a common retrieval algorithm. Atmospheric Measurement Techniques, 13(2): 553-573
  31. 31.
    Gao M, Zhai P W, Franz B A, Knobelspiesse K, Ibrahim A, Cairns B, Craig S E, Fu G L, Hasekamp O, Hu Y X and Werdell P J. 2020. Inversion of multiangular polarimetric measurements from the ACEPOL campaign: an application of improving aerosol property and hyperspectral ocean color retrievals. Atmospheric Measurement Techniques, 13(7): 3939-3956
  32. 32.
    Gao X, Hu X Q, Fang W and Yin D K. 2019. A cloud detection algorithm over land based on the polarized characteristics difference between cloudless and cloud targets. Earth and Space Science, 6(9): 1769-1780
  33. 33.
    Goloub P, Deuze J L, Herman M and Fouquart Y. 1994. Analysis of the POLDER polarization measurements performed over cloud covers. IEEE Transactions on Geoscience and Remote Sensing, 32(1): 78-88
  34. 34.
    Goloub P, Herman M, Chepfer H, Riedi J, Brogniez G, Couvert P and Séze G. 2000. Cloud thermodynamical phase classification from the POLDER spaceborne instrument. Journal of Geophysical Research: Atmospheres, 105(D11): 14747-14759
  35. 35.
    Goloub P, Tanre D, Deuze J L, Herman M, Marchand A and Breon F M. 1999. Validation of the first algorithm applied for deriving the aerosol properties over the ocean using the POLDER/ADEOS measurements. IEEE Transactions on Geoscience and Remote Sensing, 37(3): 1586-1596
  36. 36.
    Gu X F, Chen X F, Cheng T H, Li Z Q, Yu T, Xie H H and Xu H. 2011. In-flight polarization calibration methods of directional polarized remote sensing camera DPC. Acta Physica Sinica, 60(7): 172-179
  37. 37.
    Guo J J, Yao Z G, Han Z G, Zhao Z L and Yan W. 2019a. TG-2/MAI CCD dark current characteristics and its channel dependence analysis and correction. Chinese Journal of Lasers, 46(1): 0110001
  38. 38.
    Guo J J, Yao Z G, Han Z G, Zhao Z L, Yan W and Jiang J. 2019b. On-Orbit analysis and correction of the inconsistency in the response characteristics of TG-2/MAI CCD pixels. Spectroscopy and Spectral Analysis, 39(12): 3953-3962
  39. 39.
    Guo J J, Yao Z G, Han Z G, Zhao Z L, Yin D K and Yan W. 2018. Airborne experiment of TG-2 multi-angle polarization imager for cloud phase identification. Remote Sensing Technology and Application, 33(3): 439-448
  40. 40.
    Hao Z Z, Pan D L, Sun Z B and Gong F. 2006. Retrieval of the columnar aerosol grain density from SeaWiFS over the China seas. Acta Oceanologica Sinica, 28(6): 32-38
  41. 41.
    Hasekamp O P, Fu G L, Rusli S P, Wu L H, Di Noia A, aan de Brugh J, Landgraf J, Smit J M, Rietjens J and van Amerongen A. 2019. Aerosol measurements by SPEXone on the NASA PACE mission: expected retrieval capabilities. Journal of Quantitative Spectroscopy and Radiative Transfer, 227: 170-184
  42. 42.
    Heidinger A, Foster M, Botambekov D, Hiley M, Walther A and Li Y. 2016. Using the NASA EOS a-train to probe the performance of the NOAA PATMOS-x cloud fraction CDR. Remote Sensing, 8(6): 511
  43. 43.
    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
  44. 44.
    Herman M, Deuzé J L, Marchand A, Roger B and Lallart P. 2005. Aerosol remote sensing from POLDER/ADEOS over the ocean: improved retrieval using a nonspherical particle model. Journal of Geophysical Research: Atmospheres, 110(D10): D10S02
  45. 45.
    Holben B N, Eck T F, Slutsker I, Tanré D, Buis J P, Setzer A, Vermote E, Reagan J A, Kaufman Y J, Nakajima T, Lavenu F, Jankowiak I and Smirnov A. 1998. AERONET-A federated instrument network and data archive for aerosol characterization. Remote Sensing of Environment, 66(1): 1-16
  46. 46.
    Hollars S, Fu Q, Comstock J and Ackerman T. 2004. Comparison of cloud-top height retrievals from ground-based 35 GHz MMCR and GMS-5 satellite observations at ARM TWP Manus site. Atmospheric Research, 72(1/4): 169-186
  47. 47.
    Horváth G. 2014. Polarized Light and Polarization Vision in Animal Sciences. 2nd ed. Berlin, Heidelberg: Springer
  48. 48.
    Ilčev S D. 2019. Satellite remote sensing in meteorology//Global Satellite Meteorological Observation (GSMO) Applications. Switzerland: Springer: 129-182
  49. 49.
    Imaoka K, Kachi M, Fujii H, Murakami H, Hori M, Ono A, Igarashi T, Nakagawa K, Oki T, Honda Y and Shimoda H. 2010. Global Change Observation Mission (GCOM) for monitoring carbon, water cycles, and climate change. Proceedings of the IEEE, 98(5): 717-734
  50. 50.
    IPCC. 2007. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press
  51. 51.
    IPCC. 2021. Climate Change 2021: Summary for Policymakers[M/OL]. ‍
  52. 52.
    Jing Z H, Hu X Q and Yin D K. 2020. TG-2 multi-angle polarization imager remote sensing image geolocation and error correction. Remote Sensing Technology and Application, 35(2): 345-354
  53. 53.
    Kang Q, Yuan Y L, Li J J, Zhai W C, Wu H Y, Hong J and Zheng X B. 2018. Effect of divergence angle of polarization calibration source on DPC polarization calibration: analysis and validation. Journal of Remote Sensing, 22(2): 203-210
  54. 54.
    Knobelspiesse K, Barbosa H M J, Bradley C, Bruegge C, Cairns B, Chen G, Chowdhary J, Cook A, Di Noia A, van Diedenhoven B, Diner D J, Ferrare R, Fu G L, Gao M, Garay M, Hair J, Harper D, van Harten G, Hasekamp O, Helmlinger M, Hostetler C, Kalashnikova O, Kupchock A, De Freitas K L, Maring H, Martins J V, Mcbride B, Mcgill M, Norlin K, Puthukkudy A, Rheingans B, Rietjens J, Seidel F C, Da Silva A, Smit M, Stamnes S, Tan Q, Val S, Wasilewski A, Xu F, Xu X G and Yorks J. 2020. The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) airborne field campaign. Earth System Science Data, 12(3): 2183-2208
  55. 55.
    Lacagnina C, Hasekamp O P and Torres O. 2017. Direct radiative effect of aerosols based on PARASOL and OMI satellite observations. Journal of Geophysical Research: Atmospheres, 122(4): 2366-2388
  56. 56.
    Letu H, Ishimoto H, Riedi J, Nakajima T Y, Labonnote L C, Baran A J, Nagao T M and Sekiguchi M. 2016. Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission. Atmospheric Chemistry and Physics, 16(18): 12287-12303
  57. 57.
    Li C. 2019. Retrieval of Cloud Parameters Based on Imagery from the DPC Onboard GF-5 Satellite. Wuhu: Anhui Normal University: 1-165
  58. 58.
    Li C, Ma J J, Yang P and Li Z Q. 2019. Detection of cloud cover using dynamic thresholds and radiative transfer models from the polarization satellite image. Journal of Quantitative Spectroscopy and Radiative Transfer, 222-223: 196-214
  59. 59.
    Li J, Menzel W P, Zhang W J, Sun F Y, Schmit T J, Gurka J J and Weisz E. 2004. Synergistic use of MODIS and AIRS in a variational retrieval of cloud parameters. Journal of Applied Meteorology and Climatology, 43(11): 1619-1634
  60. 60.
    Li J H, Ma J J, Li C, Wang Y Y, Li Z Q and Hong J. 2021. Multi-information collaborative cloud identification algorithm in Gaofen-5 Directional Polarimetric Camera imagery. Journal of Quantitative Spectroscopy and Radiative Transfer, 261: 107439
  61. 61.
    Li J X, Zhao P, Fang W and Song S X. 2020. Cloud detection of multi-angle remote sensing image based on deep learning. Journal of Atmospheric and Environmental Optics, 15(5): 380-392
  62. 62.
    Li L, Li Z Q, Xu H, Lv Y, Li K. 2019. A method for cloud detection using CE318-DP. China, CN 109959978 A
  63. 63.
    Li S. 2018. Analysis of Cloud Optical Characteristics and Retrieval of Main Cloud Parameters for Satellite Polarized Remote Sensing. Hefei: University of Science and Technology of China: 49-76
  64. 64.
    Li Z Q, Hou W Z, Hong J, Zheng F X, Luo D G, Wang J, Gu X F and Qiao Y L. 2018. Directional Polarimetric Camera (DPC): monitoring aerosol spectral optical properties over land from satellite observation. Journal of Quantitative Spectroscopy and Radiative Transfer, 218: 21-37
  65. 65.
    Li Z Q, Xie Y S, Hong J, Wang Z T, Wang S P, Sun X B, Qiao Y L and Gu X F. 2019. Polarimetric satellite sensors for earth observation and applications in atmospheric remote sensing. Journal of Atmospheric and Environmental Optics, 14(1): 2-17
  66. 66.
    Lin L, Huang S X and Du H D. 2006. Retrieval of cloudtop properties from modis data. Scientia Meteorologica Sinica, 26(6): 655-661
  67. 67.
    Liu Y and Diner D J. 2017. Multi-angle imager for aerosols: a satellite investigation to benefit public health. Public Health Reports, 132(1): 14-17
  68. 68.
    Luo D G, Zhang M M, Meng B H, Xu S L, Liu Z H, Yang W F and Hong J. 2019. Test method for spaceborne directional polarization camera. Journal of Atmospheric and Environmental Optics, 14(2): 144-153
  69. 69.
    Ma J J, Wang C L, Hong J and Li Z Q. 2021. Cloud Remote Sensing from Satellite Multi-Sensor Data. Beijing: Science Press: 328-337
  70. 70.
    Mahajan S and Fataniya B. 2020. Cloud detection methodologies: variants and development-a review. Complex and Intelligent Systems, 6(2): 251-261
  71. 71.
    Marbach T, Riedi J, Lacan A and Schlüssel P. 2015. The 3MI mission: multi-viewing-channel-polarisation imager of the EUMETSAT polar system: second generation (EPS-SG) dedicated to aerosol and cloud monitoring//Proceedings Volume 9613, Polarization Science and Remote Sensing VII. San Diego, California: SPIE
  72. 72.
    Martonchik J V, Kahn R A and Diner D J. 2009. Retrieval of aerosol properties over land using MISR observations//Satellite Aerosol Remote Sensing over Land. Berlin, Heidelberg: Springer: 267-293
  73. 73.
    Matsui T, Masunaga H, Pielke R A and Tao W K. 2004. Impact of aerosols and atmospheric thermodynamics on cloud properties within the climate system. Geophysical Research Letters, 31(6): L06109
  74. 74.
    McBride B A, Martins J V, Barbosa H M J, Birmingham W and Remer L A. 2020. Spatial distribution of cloud droplet size properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) measurements. Atmospheric Measurement Techniques, 13(4): 1777-1796
  75. 75.
    Milinevsky G, Yatskiv Y, Degtyaryov O, Syniavskyi I, Ivanov Y, Bovchaliuk A, Mishchenko M, Danylevsky V, Sosonkin M and Bovchaliuk V. 2015. Remote sensing of aerosol in the terrestrial atmosphere from space: new missions. Advances in Astronomy and Space Physics, 5(1): 11-16
  76. 76.
    Milinevsky G, Yatskiv Y, Degtyaryov O, Syniavskyi I, Mishchenko M, Rosenbush V, Ivanov Y, Makarov A, Bovchaliuk A, Danylevsky V, Sosonkin M, Moskalov S, Bovchaliuk V, Lukenyuk A, Shymkiv A and Udodov E. 2016. New satellite project Aerosol-UA: remote sensing of aerosols in the terrestrial atmosphere. Acta Astronautica, 123: 292-300
  77. 77.
    Mishchenko M I, Cairns B, Kopp G, Schueler C F, Fafaul B A, Hansen J E, Hooker R J, Itchkawich T, Maring H B and Travis L D. 2007. Accurate monitoring of terrestrial aerosols and total solar irradiance: introducing the glory mission. Bulletin of the American Meteorological Society, 88(5): 677-692
  78. 78.
    Nadal F and Breon F M. 1999. Parameterization of surface polarized reflectance derived from POLDER spaceborne measurements. IEEE Transactions on Geoscience and Remote Sensing, 37(3): 1709-1718
  79. 79.
    Nakajima T and King M D. 1990. Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part I: theory. Journal of the Atmospheric Sciences, 47(15): 1878-1893
  80. 80.
    Nakajima T, King M D, Spinhirne J D and Radke L F. 1991. Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part II: marine stratocumulus observations. Journal of the Atmospheric Sciences, 48(5): 728-751
  81. 81.
    Nasiri S L and Kahn B H. 2008. Limitations of bispectral infrared cloud phase determination and potential for improvement. Journal of Applied Meteorology and Climatology, 47(11): 2895-2910
  82. 82.
    Peralta R J, Nardell C, Cairns B, Russell E E, Travis L D, Mishchenko M I, Fafaul B A and Hooker R J. 2007. Aerosol polarimetry sensor for the Glory Mission//Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition. Wuhan: SPIE
  83. 83.
    Piters A J M, Bramstedt K, Lambert J C and Kirchhoff B. 2006. Overview of SCIAMACHY validation: 2002-2004. Atmospheric Chemistry and Physics, 6(1): 127-148
  84. 84.
    Platnick S, King M D, Ackerman S A, Menzel W P, Baum B A, Riedi J C and Frey R A. 2003. The MODIS cloud products: algorithms and examples from Terra. IEEE Transactions on Geoscience and Remote Sensing, 41(2): 459-473
  85. 85.
    Platnick S, Meyer K G, King M D, Wind G, Amarasinghe N, Marchant B, Arnold G T, Zhang Z B, Hubanks P A, Holz R E, Yang P, Ridgway W L and Riedi J. 2017. The MODIS cloud optical and microphysical products: collection 6 updates and examples from terra and aqua. IEEE Transactions on Geoscience and Remote Sensing, 55(1): 502-525
  86. 86.
    Puthukkudy A, Martins J V, Remer L A, Xu X G, Dubovik O, Litvinov P, McBride B, Burton S and Barbosa H M J. 2020. Retrieval of aerosol properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) observations during ACEPOL 2017. Atmospheric Measurement Techniques, 13(10): 5207-5236
  87. 87.
    Qiao R, Qie L L, Xu H, Li Z Q, Zhu S F, Xie Y S, Hong J, Dai H S and Ma J J. 2021. Retrieval of cloud top pressure in oxygen a-band based on data from DPC onboard GF-5 satellite. Journal of Atmospheric and Environmental Optics, 16(3): 256-268
  88. 88.
    Ren J Q, Yan W, Ye J and Han D. 2010. Advances in the study of cloud phase discrimination using satellite remote sensing data. Advances in Earth Science, 25(10): 1051-1060
  89. 89.
    Riedi J, Goloub P and Marchand R T. 2001. Comparison of POLDER cloud phase retrievals to active remote sensors measurements at the ARM SGP site. Geophysical Research Letters, 28(11): 2185-2188
  90. 90.
    Riedi J, Marchant B, Platnick S, Baum B A, Thieuleux F, Oudard C, Parol F, Nicolas J M and Dubuisson P. 2010. Cloud thermodynamic phase inferred from merged POLDER and MODIS data. Atmospheric Chemistry and Physics, 10(23): 11851-11865
  91. 91.
    Riedi J, Merlin G, Labonnote L, Cornet C, Ferlay N, Desmons M, Dubuisson P, Parol F, Davis A B and Marbach T. 2014. Information Content Analysis for the Multi-Viewing, Multi-Channel, Multi-Polarization Imaging (3MI) Instrument: Toward Retrieval of Vertically Resolved Cloud Properties from Passive Only Measurements. Washington, DC: American Geophysical Union
  92. 92.
    Rietjens J, Campo J, Chanumolu A, Smit M, Nalla R, Fernandez C, Dingjan J, van Amerongen A and Hasekamp O. 2019. Expected performance and error analysis for SPEXone, a multi-angle channeled spectropolarimeter for the NASA PACE mission//Proceedings Volume 11132, Polarization Science and Remote Sensing IX. San Diego, CA: SPIE: 11-15
  93. 93.
    Rossow W B and Schiffer R A. 1999. Advances in understanding clouds from ISCCP. Bulletin of the American Meteorological Society, 80(11): 2261-2288
  94. 94.
    Schmunk R B. 2018. Glory APS Science[EB/OL].
  95. 95.
    Segal-Rozenhaimer M, Miller D J, Knobelspiesse K, Redemann J, Cairns B and Alexandrov M D. 2018. Development of neural network retrievals of liquid cloud properties from multi-angle polarimetric observations. Journal of Quantitative Spectroscopy and Radiative Transfer, 220: 39-51
  96. 96.
    Shang H, Chen L, Bréon F M, Letu H, Li S, Wang Z and Su L. 2015. Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument. Atmospheric Measurement Techniques, 8(11): 4931-4945
  97. 97.
    Shang H Z, Letu H, Bréon F M, Riedi J, Ma R, Wang Z M, Nakajima T Y, Wang Z T and Chen L F. 2019. An improved algorithm of cloud droplet size distribution from POLDER polarized measurements. Remote Sensing of Environment, 228: 61-74
  98. 98.
    Shang H Z, Letu H, Chen L F, Riedi J, Ma R, Wei L S, Labonnote L C, Hioki S, Liu C, Wang Z T and Wang J J. 2020. Cloud thermodynamic phase detection using a directional polarimetric camera (DPC). Journal of Quantitative Spectroscopy and Radiative Transfer, 253: 107179
  99. 99.
    Shen F, Zhang Q Y, Ma J J, Li Z Q and Hong J. 2021. Identification of polluted clouds and composition analysis based on GF-5 DPC data. Journal of Quantitative Spectroscopy and Radiative Transfer, 269: 107659
  100. 100.
    Shi G M, Li C C and Ren T. 2014. Sensitivity analysis of single-angle polarization reflectance observed by satellite. Chinese Science Bulletin, 59(14): 1519-1528
  101. 101.
    Sinclair K, van Diedenhoven B, Cairns B, Alexandrov M, Moore R, Crosbie E and Ziemba L. 2019. Polarimetric retrievals of cloud droplet number concentrations. Remote Sensing of Environment, 228: 227-240
  102. 102.
    Stamnes S, Hostetler C, Ferrare R, Burton S, Liu X, Hair J, Hu Y, Wasilewski A, Martin W, van Diedenhoven B, Chowdhary J, Cetinić I, Berg L K, Stamnes K and Cairns B. 2018. Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the "MAPP" algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products. Applied Optics, 57(10): 2394-2413
  103. 103.
    Stephens G L, Tsay S C, Stackhouse P W Jr and Flatau P J. 1990. The relevance of the microphysical and radiative properties of cirrus clouds to climate and climatic feedback. Journal of the Atmospheric Sciences, 47(14): 1742-1754
  104. 104.
    Suhai B and Horváth G. 2004. How well does the Rayleigh model describe the E-vector distribution of skylight in clear and cloudy conditions? A full-sky polarimetric study. Journal of the Optical Society of America A-Optics Image Science and Vision, 21(9): 1669-1676
  105. 105.
    Syniavskyi I I, Milinevsky G P, Ivanov Y S, Sosonkin M G, Danylevsky V O, Rosenbush V K, Bovchaliuk A P, Lukenyuk A A, Shymkiv A P and Mishchenko M I. 2015. Methodology, hardware implementation, and validation of satellite remote sensing of atmospheric aerosols: first results of the aerosol-UA space experiment development. Kosmìčna Nauka Ì Tehnologìâ, 21(3): 9-17
  106. 106.
    Tanré D, Bréon F M, Deuzé J L, Dubovik O, Ducos F, François P, Goloub P, Herman M, Lifermann A and Waquet F. 2011. Remote sensing of aerosols by using polarized, directional and spectral measurements within the A-Train: the PARASOL mission. Atmospheric Measurement Techniques, 4(7): 1383-1395
  107. 107.
    Trenberth K E, Fasullo J T and Kiehl J. 2009. Earth's global energy budget. Bulletin of the American Meteorological Society, 90(3): 311-324
  108. 108.
    Tu B H, Hong J, Yao P P, Meng B H, Yuan Y L, Zhang M M and Weng J W. 2020. Polarization detection performance of directional polarimetric camera. Acta Optica Sinica, 40(7): 0712003
  109. 109.
    Van Amerongen A, Rietjens J, Campo J, Dogan E, Dingjan J, Nalla R, Caron J and Haseka O. 2018. SPEXone: a compact multi-angle polarimeter//Proceedings Volume 11180, International Conference on Space Optics. Chania: SPIE
  110. 110.
    Vanbauce C, Buriez J C, Parol F, Bonnel B, Sèze G and Couvert P. 1998. Apparent pressure derived from ADEOS-POLDER observations in the oxygen A-band over ocean. Geophysical Research Letters, 25(16): 3159-3162
  111. 111.
    Wang J J, Liu S H, Li S, Ye S, Wang X Q and Wang F Y. 2021. Optimization algorithm for polarization remote sensing cloud detection based on machine learning. Acta Photonica Sinica, 50(2): 0228001
  112. 112.
    Wang J J, Sun X B, Ti R F and Yu H X. 2021. Multi-Angle polarization radiation threshold detection method of cloud cover over ocean. Journal of Atmospheric and Environmental Optics, 16(3): 247-255
  113. 113.
    Wang T, Fetzer E J, Wong S, Kahn B H and Yue Q. 2016. Validation of MODIS cloud mask and multilayer flag using CloudSat-CALIPSO cloud profiles and a cross-reference of their cloud classifications. Journal of Geophysical Research: Atmospheres, 121(19): 11620-11635
  114. 114.
    Wang X, Guo Z, Huang Y P, Fan H J and Li W B. 2017. A cloud detection scheme for the Chinese Carbon Dioxide Observation Satellite (TANSAT). Advances in Atmospheric Sciences, 34(1): 16-25
  115. 115.
    Wei L S. 2020. Research on Cloud Detection Algorithm Based on Gaofen-5 -DPC Data. Hohhot: Inner Mongolia Normal University
  116. 116.
    Wei L S, Shang H Z, Husi L T, Ma R, Hu D H, Chao K F, Si F Q and Shi J C. 2021. Cloud detection algorithm based on GF-5 DPC data. National Remote Sensing Bulletin, 25(10): 2053-2066
  117. 117.
    Wu H. 2016. Polarization Imaging and Cloud Polarization Characteristics Research. Wuhu: Anhui Normal University: 1-45
  118. 118.
    Xie Y S, Li Z Q, Hou W Z, Zhang Y, Qie L L, Li L, Li K T and Xu H. 2019. Retrieval of fine-mode aerosol optical depth based on remote sensing measurements of directional polarimetric camera onboard GF-5 satellite. Aerospace Shanghai, 36(S2): 219-226
  119. 119.
    Xu F F. 2018. Research on Pollution Cloud Recognition Algorithm Based on POLDER Data. Wuhu: Anhui Normal University: 15-67
  120. 120.
    Xu F F, Ma J J, Wu S C and Li Z Q. 2019. Identification of smoke and polluted clouds based on polarized satellite images. Journal of Quantitative Spectroscopy and Radiative Transfer, 224: 343-354
  121. 121.
    Yan W, Yang H L and Zhou X W. 2008. A-Train satellite formation and its application to cloud research. Remote Sensing Information, (2): 93-96
  122. 122.
    Yang H C. 2019. On-Orbit Calibration of Particulate Matter Polarimetry Suits. Hefei: University of Science and Technology of China
  123. 123.
    Yang Z W, Gao S G and Wang P G. 2005. Polarization of reflected light by earth objects. Acta Optica Sinica, 25(2): 241-245
  124. 124.
    Yao Z G, Han Z G, Zhao Z L, Lin L F and Fan X H. 2010. Synergetic use of POLDER and MODIS for multilayered cloud identification. Remote Sensing of Environment, 114(9): 1910-1923
  125. 125.
    Yasumoto M, Sano I and Mukai S. 2002. Combined use of OCTS and POLDER for cloud retrieval. Advances in Space Research, 29(1): 39-44
  126. 126.
    Yin D K. 2019. Multi-Angle polarization detection technology. Infrared, 40(1): 1-6, 23
  127. 127.
    Yu H X, Ma J J, Ahmad S, Sun E C, Li C, Li Z Q and Hong J. 2019. Three-dimensional cloud structure reconstruction from the directional polarimetric camera. Remote Sensing, 11(24): 2894
  128. 128.
    Zhang M M, Meng B H, Luo D G, Yang B Y, Ti R F and Hong J. 2018. Measurement precision verification and deviation analysis of spaceborne directional polarimetric camera. Acta Optica Sinica, 38(8): 0812004
  129. 129.
    Zhang W. 2016. Progress of Tiangong-2 space science and application mission. Aerospace China, (12): 18-23
  130. 130.
    Zhang Y, Lv D R and Duan M Z. 2011. Two kinds of cloud top height retrieval methods with oxygen A-Band comparison by simulated data and verification with experimental results in China. Remote Sensing Technology and Application, 26(1): 18-32
  131. 131.
    Zhang Y P, Hu X Q, Yin D K and Gu M J. 2020a. Full image on-orbit polarization calibration method of multi-angle polarization imager. Acta Optica Sinica, 40(19): 1911001
  132. 132.
    Zhang Y P, Hu X Q, Yin D K and Gu M J. 2020b. Onboard polarization calibration technique of multi-angle polarization imager based on sun glint from ocean. Acta Optica Sinica, 40(15): 1528002

قراءة النص الكامل

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website