Acta Optica Sinica, Volume. 42, Issue 6, 0600003(2022)

Remote Sensing of Cloud Properties Based on Visible-to-Infrared Channel Observation from Passive Remote Sensing Satellites

Huazhe Shang1, Letu Husi1、*, Ming Li1,2, Jinghua Tao1, and Liangfu Chen1,2、**
Author Affiliations
  • 1State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100010, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • show less
    References(136)

    [1] Wylie D, Jackson D L, Menzel W P et al. Trends in global cloud cover in two decades of HIRS observations[J]. Journal of Climate, 18, 3021-3031(2005).

    [2] Zeng S, Parol F, Riedi J et al. Examination of POLDER/PARASOL and MODIS/Aqua cloud fractions and properties representativeness[J]. Journal of Climate, 24, 4435-4450(2011).

    [3] Rosenfeld D. Aerosols, clouds, and climate[J]. Science, 312, 1323-1324(2006).

    [4] Rosenfeld D, Zhu Y N, Wang M H et al. 363(6427): eaav0566[J]. water of oceanic low-level clouds. Science(2019).

    [5] Myers T A, Scott R C, Zelinka M D et al. Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity[J]. Nature Climate Change, 11, 501-507(2021).

    [6] Yin Y, Carslaw K S, Feingold G. Vertical transport and processing of aerosols in a mixed-phase convective cloud and the feedback on cloud development[J]. Quarterly Journal of the Royal Meteorological Society, 131, 221-245(2005).

    [7] Fu Y F, Yu R C, Xu Y P et al. Analysis on precipitation structures of two heavy rain cases by using TRMM PR and IMI[J]. Acta Meteorologica Sinica, 61, 421-431, 513(2003).

    [8] Xu X D, Zhou L, Zhou X J et al. Influence region of surrounding sources in the process of heavy air pollution in urban environment[J]. SCIENCE IN CHINA Ser. D Earth Sciences, 34, 958-966(2004).

    [9] Liu Y M, Yan Y F, Lü J H et al. Review of current investigations of cloud, radiation and rainfall over the Tibetan Plateau with the CloudSat/CALIPSO dataset[J]. Chinese Journal of Atmospheric Sciences, 42, 847-858(2018).

    [10] Twomey S. The influence of pollution on the shortwave albedo of clouds[J]. Journal of the Atmospheric Sciences, 34, 1149-1152(1977).

    [11] Ramanathan V, Ramana M V, Roberts G et al. Warming trends in Asia amplified by brown cloud solar absorption[J]. Nature, 448, 575-578(2007).

    [12] Sun Y, Ding Y H. Responses of South and East Asian summer monsoons to different land-sea temperature increases under a warming scenario[J]. Chinese Science Bulletin, 56, 2718-2726(2011).

    [13] Merlin G, Riedi J, Labonnote L C et al. Cloud information content analysis of multi-angular measurements in the oxygen A-band: application to 3MI and MSPI[J]. Atmospheric Measurement Techniques, 9, 4977-4995(2016).

    [14] Baum B A, Frey R A, Mace G G et al. Nighttime multilayered cloud detection using MODIS and ARM data[J]. Journal of Applied Meteorology, 42, 905-919(2003).

    [15] Chen Q, Zhang H. Effects of ice crystal habit weight on ice cloud optical properties and radiation[J]. Acta Meteorologica Sinica, 76, 279-288(2018).

    [16] van Diedenhoven B. Remote sensing of crystal shapes in ice clouds[M]. ∥Kokhanovsky A. Springer series in light scattering. Cham: Springer, 197-250(2018).

    [17] Chen H B, Bian J C, Lü D R. Advances and prospects in the study of stratosphere-troposphere exchange[J]. Chinese Journal of Atmospheric Sciences, 30, 813-820(2006).

    [18] Zhao C F, Liu L P, Wang Q Q et al. Toward understanding the properties of high ice clouds at the Naqu site on the Tibetan Plateau using ground-based active remote sensing measurements obtained during a short period in July 2014[J]. Journal of Applied Meteorology and Climatology, 55, 2493-2507(2016).

    [19] Baker M B, Peter T. Small-scale cloud processes and climate[J]. Nature, 451, 299-300(2008).

    [20] Fu Y F, Pan X, Xian T et al. Precipitation characteristics over the steep slope of the Himalayas in rainy season observed by TRMM PR and VIRS[J]. Climate Dynamics, 51, 1971-1989(2018).

    [21] Qu Y W, Han Y, Wu Y H et al. Study of PBLH and its correlation with particulate matter from one-year observation over Nanjing, southeast China[J]. Remote Sensing, 9, 668(2017).

    [22] Gong W, Li W L. Simulation of severe storm rainfall event in 1991 over Changjiang Huaihe River valley with a Chinese regional climate model[J]. Quarterly Journal of Applied Meteorlolgy, 8, 70-79(1997).

    [23] Huang J P, Chen W, Wen Z P et al. Review of Chinese atmospheric science research over the past 70 years: climate and climate change[J]. Scientia Sinica Terrae, 49, 1607-1640(2019).

    [24] Zhang H, Wang F, Zhao S Y et al. Earth’s energy budget, climate feedbacks, and climate sensitivity[J]. Climate Change Research, 17, 691-698(2021).

    [25] Masson-Delmotte V, Zhai P, Pirani A et al. Towards the sixth assessment report of the Intergovernmental Panel on Climate Change (IPCC). [C]∥Proceedings of the 2016 AGU Fall Meeting, December 12-16, 2016, Moscone. New York: AGU(2016).

    [26] Liu Y Z, Wu C Q, Jia R et al. An overview of the influence of atmospheric circulation on the climate in arid and semi-arid region of Central and East Asia[J]. Science China Earth Sciences, 61, 1183-1194(2018).

    [27] Yu H P, Huang J P, Li W J et al. Development of the analogue-dynamical method for error correction of numerical forecasts[J]. Journal of Meteorological Research, 28, 934-947(2014).

    [28] Wang M H, Ghan S, Liu X H et al. Constraining cloud lifetime effects of aerosols using A-Train satellite observations[J]. Geophysical Research Letters, 39, L15709(2012).

    [29] Zhu L, Lu C S, Gao S N et al. Spectral width of cloud droplet spectra and its impact factors in marine stratocumulus[J]. Chinese Journal of Atmospheric Sciences, 44, 575-590(2020).

    [30] Dongfang X[J]. A brief analysis of high resolution satellite and its application in China Satellite Application, 2015, 44-48.

    [31] Jiang X W, Lin M S, Zhang Y G. Progress and prospect of Chinese ocean satellites[J]. Journal of Remote Sensing, 20, 1185-1198(2016).

    [32] Yang J, Dong C H, Lu N M et al. FY-3A: the new generation polar-orbiting meteorological satellite of China[J]. Acta Meteorologica Sinica, 67, 501-509(2009).

    [33] Zhang P, Guo Q, Chen B Y et al. The Chinese next-generation geostationary meteorological satellite FY-4 compared with the Japanese Himawari-8/9 satellites[J]. Advances in Meteorological Science and Technology, 6, 72-75(2016).

    [34] Yang P, Hioki S, Saito M et al. A review of ice cloud optical property models for passive satellite remote sensing[J]. Atmosphere, 9, 499(2018).

    [35] Congalton R G. Remote sensing: an overview[J]. GIScience & Remote Sensing, 47, 443-459(2010).

    [36] Stephens G L, Kummerow C D. The remote sensing of clouds and precipitation from space: a review[J]. Journal of the Atmospheric Sciences, 64, 3742-3765(2007).

    [37] Zhao C F, Yang Y K. Progress and challenges of ground-based cloud remote sensing[J]. Torrential Rain and Disasters, 40, 243-258(2021).

    [38] Riedi J, Marchant B, Platnick S et al. Cloud thermodynamic phase inferred from merged POLDER and MODIS data[J]. Atmospheric Chemistry and Physics, 10, 11851-11865(2010).

    [39] Breon F M, Doutriaux-Boucher M. A comparison of cloud droplet radii measured from space[J]. IEEE Transactions on Geoscience and Remote Sensing, 43, 1796-1805(2005).

    [40] Platnick S, Meyer K G, King M D et al. The MODIS cloud optical and microphysical products: Collection 6 updates and examples from Terra and Aqua[J]. IEEE Transactions on Geoscience and Remote Sensing, 55, 502-525(2017).

    [41] Labonnote L C, Brogniez G, Buriez J C et al. Polarized light scattering by inhomogeneous hexagonal monocrystals: validation with ADEOS-POLDER measurements[J]. Journal of Geophysical Research, 106, 12139-12153(2001).

    [42] Letu H S, Ishimoto H, Riedi J et al. Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission[J]. Atmospheric Chemistry and Physics, 16, 12287-12303(2016).

    [43] Plass G N, Kattawar G W, Catchings F E. Matrix operator theory of radiative transfer. 1: Rayleigh scattering[J]. Applied Optics, 12, 314-329(1973).

    [44] Thalman R, Zarzana K J, Tolbert M A et al. Rayleigh scattering cross-section measurements of nitrogen, argon, oxygen and air[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 147, 171-177(2014).

    [45] Rothman L S, Gordon I E, Barbe A et al. The HITRAN 2008 molecular spectroscopic database[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 110, 533-572(2009).

    [46] Nakajima T, King M D. Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part I: theory[J]. Journal of the Atmospheric Sciences, 47, 1878-1893(1990).

    [47] Nakajima T Y, Nakajma T. Wide-area determination of cloud microphysical properties from NOAA AVHRR measurements for FIRE and ASTEX regions[J]. Journal of the Atmospheric Sciences, 52, 4043-4059(1995).

    [48] Remer L A, Kaufman Y J, Tanré D et al. The MODIS aerosol algorithm, products, and validation[J]. Journal of the Atmospheric Sciences, 62, 947-973(2005).

    [49] Hua D X, Song X Q. Advances in lidar remote sensing techniques[J]. Infrared and Laser Engineering, 37, 21-27(2008).

    [50] Mao F Y, Gong W, Li J et al. Cloud detection and parameter retrieval based on improved differential zero-crossing method for Mie lidar[J]. Acta Optica Sinica, 30, 3097-3102(2010).

    [51] Li J, Huang J, Stamnes K et al. A global survey of cloud overlap based on CALIPSO and CloudSat measurements[J]. Atmospheric Chemistry and Physics, 15, 519-536(2015).

    [52] Yang B Y, Zhang H, Peng J et al. Analysis on global distribution characteristics of cloud microphysical and optical properties based on the CloudSat data[J]. Plateau Meteorology, 33, 1105-1118(2014).

    [53] Stein T H M, Delanoë J, Hogan R J. A comparison among four different retrieval methods for ice-cloud properties using data from CloudSat, CALIPSO, and MODIS[J]. Journal of Applied Meteorology and Climatology, 50, 1952-1969(2011).

    [54] Saunders R W, Kriebel K T. An improved method for detecting clear sky and cloudy radiances from AVHRR data[J]. International Journal of Remote Sensing, 9, 123-150(1988).

    [55] Duan M Z, Lü D R. Simultaneously retrieving aerosol optical depth and surface albedo over land from POLDER’s multi-angle polarized measurements Ⅱ: a case study[J]. Chinese Journal of Atmospheric Sciences, 32, 27-35(2008).

    [56] Alexandrov M D, Miller D J, Rajapakshe C et al. Vertical profiles of droplet size distributions derived from cloud-side observations by the research scanning polarimeter: tests on simulated data[J]. Atmospheric Research, 239, 104924(2020).

    [57] Buriez J C. An improved derivation of the top-of-atmosphere albedo from POLDER/ADEOS-2: narrowband albedos[J]. Journal of Geophysical Research Atmospheres, 110, D05202(2005).

    [58] Deschamps P Y, Breon F M, Leroy M et al. The POLDER mission: instrument characteristics and scientific objectives[J]. IEEE Transactions on Geoscience and Remote Sensing, 32, 598-615(1994).

    [59] Fougnie B, Bracco G, Lafrance B et al. PARASOL in-flight calibration and performance[J]. Applied Optics, 46, 5435-5451(2007).

    [60] Chen L F, Shang H Z, Fan M et al. Mission overview of the GF-5 satellite for atmospheric parameter monitoring[J]. National Remote Sensing Bulletin, 25, 1917-1931(2021).

    [61] Li Z Q, Hou W Z, Hong J et al. Directional Polarimetric Camera (DPC): monitoring aerosol spectral optical properties over land from satellite observation[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 218, 21-37(2018).

    [62] Yang J, Zhang Z Q, Wei C Y et al. Introducing the new generation of Chinese geostationary weather satellites, Fengyun-4[J]. Bulletin of the American Meteorological Society, 98, 1637-1658(2017).

    [63] Zhang P, Zhu L, Tang S H et al. General comparison of FY-4A/AGRI with other GEO/LEO instruments and its potential and challenges in non-meteorological applications[J]. Frontiers in Earth Science, 6, 224(2019).

    [64] Bessho K, Date K J, Hayashi M et al. An introduction to Himawari-8/9: Japan’s new-generation geostationary meteorological satellites[J]. Journal of the Meteorological Society of Japan Ser II, 94, 151-183(2016).

    [65] Lee K S, Chung S R, Lee C et al. Development of land surface albedo algorithm for the GK-2A/AMI instrument[J]. Remote Sensing, 12, 2500(2020).

    [66] Schmit T J, Griffith P, Gunshor M M et al. A closer look at the ABI on the GOES-R series[J]. Bulletin of the American Meteorological Society, 98, 681-698(2017).

    [67] Schmit T J, Gunshor M M, Menzel W P et al. Introducing the next-generation advanced baseline imager on Goes-R[J]. Bulletin of the American Meteorological Society, 86, 1079-1096(2005).

    [68] He X W, Feng X H, Han Q et al. Advances of the geostationary meteorological satellite in the world: a review[J]. Advances in Meteorological Science and Technology, 10, 22-29, 41(2020).

    [69] Goodman A H, Henderson-Sellers A. Cloud detection and analysis: a review of recent progress[J]. Atmospheric Research, 21, 203-228(1988).

    [70] Bréon F M, Colzy S. Cloud detection from the spaceborne POLDER instrument and validation against surface synoptic observations[J]. Journal of Applied Meteorology, 38, 777-785(1999).

    [71] Frey R A, Ackerman S A, Liu Y H et al. Cloud detection with MODIS. Part I: improvements in the MODIS cloud mask for Collection 5[J]. Journal of Atmospheric and Oceanic Technology, 25, 1057-1072(2008).

    [72] Ackerman S A, Strabala K I, Menzel W P et al. Discriminating clear sky from clouds with MODIS[J]. Journal of Geophysical Research, 103, 32141-32157(1998).

    [73] Nakajima T Y, Ishida H, Nagao T M et al. Theoretical basis of the algorithms and early phase results of the GCOM-C (Shikisai) SGLI cloud products[J]. Progress in Earth and Planetary Science, 6, 52(2019).

    [74] Li X, Pinker R T, Wonsick M M et al. Toward improved satellite estimates of short-wave radiative fluxes: focus on cloud detection over snow: 1. methodology[J]. Journal of Geophysical Research, 112, D07208(2007).

    [75] Pinker R T, Li X, Meng W et al. Toward improved satellite estimates of short-wave radiative fluxes: focus on cloud detection over snow: 2. results[J]. Journal of Geophysical Research, 112, D09204(2007).

    [76] Jeppesen J H, Jacobsen R H, Inceoglu F et al. A cloud detection algorithm for satellite imagery based on deep learning[J]. Remote Sensing of Environment, 229, 247-259(2019).

    [77] Min M, Wu C Q, Li C et al. Developing the science product algorithm testbed for Chinese next-generation geostationary meteorological satellites: Fengyun-4 series[J]. Journal of Meteorological Research, 31, 708-719(2017).

    [78] Derrien M, Farki B, Harang L et al. Automatic cloud detection applied to NOAA-11/AVHRR imagery[J]. Remote Sensing of Environment, 46, 246-267(1993).

    [79] Platnick S, Wind G, King M D et al. Comparison of the MODIS Collection 5 multilayer cloud detection product with CALIPSO[C]. AIP Conference Proceedings, 1100, 416-419(2009).

    [80] Hu X Q, Lu N M, Zhang P. Remote sensing and detection of dust storm in China using the thermal bands of geostationary meteorological satellite[J]. Journal of Applied Meteorological Science, 18, 266-275(2007).

    [81] Shang H Z, Chen L F, Letu H S et al. Development of a daytime cloud and haze detection algorithm for Himawari-8 satellite measurements over central and eastern China[J]. Journal of Geophysical Research, 122, 3528-3543(2017).

    [82] Wei L S, Shang H Z, Husi L T et al. Cloud detection algorithm based on GF-5 DPC data[J]. National Remote Sensing Bulletin, 25, 2053-2066(2021).

    [83] Shang H Z, Letu H S, Chen L F et al. Cloud thermodynamic phase detection using a directional polarimetric camera (DPC)[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 253, 107179(2020).

    [84] Pilewskie P, Twomey S. Cloud phase discrimination by reflectance measurements near 1.6 and 2.2 μm[J]. Journal of the Atmospheric Sciences, 44, 3419-3420(1987).

    [85] Platnick S, King M D, Ackerman S A et al. The MODIS cloud products: algorithms and examples from Terra[J]. IEEE Transactions on Geoscience and Remote Sensing, 41, 459-473(2003).

    [86] Mouri K, Izumi T, Suzue H et al. Algorithm theoretical basis document of cloud type/phase product[J]. Meteorological Satellite Center Technical Note, 61, 19-31(2016).

    [87] Goloub P, Herman M, Chepfer H et al. Cloud thermodynamical phase classification from the POLDER spaceborne instrument[J]. Journal of Geophysical Research, 105, 14747-14759(2000).

    [88] Doutriaux-Boucher M, Buriez J C, Brogniez G et al. Sensitivity of retrieved POLDER directional cloud optical thickness to various ice particle models[J]. Geophysical Research Letters, 27, 109-112(2000).

    [89] Riedi J, Doutriaux-Boucher M, Goloub P et al. Global distribution of cloud top phase from POLDER/ADEOS I[J]. Geophysical Research Letters, 27, 1707-1710(2000).

    [90] Wylie D P, Menzel W P. Eight years of high cloud statistics using HIRS[J]. Journal of Climate, 12, 170-184(1999).

    [91] Nakajima T Y, Ishida H, Nagao T M et al. Theoretical basis of the algorithms and early phase results of the GCOM-C (Shikisai) SGLI cloud products[J]. Progress in Earth and Planetary Science, 6, 52(2019).

    [92] Håkansson N, Adok C, Thoss A et al. Neural network cloud top pressure and height for MODIS[J]. Atmospheric Measurement Techniques, 11, 3177-3196(2018).

    [93] Parol F, Buriez J C, Vanbauce C et al. First results of the POLDER “Earth radiation budget and clouds” operational algorithm[J]. IEEE Transactions on Geoscience and Remote Sensing, 37, 1597-1612(1999).

    [94] Ferlay N, Thieuleux F, Cornet C et al. Toward new inferences about cloud structures from multidirectional measurements in the oxygen a band: middle-of-cloud pressure and cloud geometrical thickness from POLDER-3/PARASOL[J]. Journal of Applied Meteorology and Climatology, 49, 2492-2507(2010).

    [95] Vanbauce C, Buriez J C, Parol F et al. Apparent pressure derived from ADEOS-POLDER observations in the oxygen A-band over ocean[J]. Geophysical Research Letters, 25, 3159-3162(1998).

    [96] Pilewskie P, Twomey S. Cloud phase discrimination by reflectance measurements near 1.6 and 2.2 μm[J]. Journal of the Atmospheric Sciences, 44, 3419-3420(1987).

    [97] Zhang Z B, Platnick S, Yang P et al. Effects of ice particle size vertical inhomogeneity on the passive remote sensing of ice clouds[J]. Journal of Geophysical Research, 115, D17203(2010).

    [98] Letu H S, Nakajima T Y, Matsui T N. Development of an ice crystal scattering database for the global change observation mission/second generation global imager satellite mission: investigating the refractive index grid system and potential retrieval error[J]. Applied Optics, 51, 6172-6178(2012).

    [99] Husi L, Nakajima T Y, Nagao T M et al. Comparation of the ice cloud properties from Himawari-8/AHI and MODIS C6 product. [C]∥AGU Fall Meeting, December 10-14, 2018, Washington, D.C. New York: AGU(2018).

    [100] Labonnote L C, Brogniez G, Doutriaux-Boucher M et al. Modeling of light scattering in cirrus clouds with inhomogeneous hexagonal monocrystals. Comparison with in situ and ADEOS-POLDER measurements[J]. Geophysical Research Letters, 27, 113-116(2000).

    [101] Bi L, Yang P, Liu C et al. Optical properties of ice clouds: new modeling capabilities and relevant applications[J]. Proceedings of SPIE, 9259, 92591A(2014).

    [102] Liang S L, Zhao X, Liu S H et al. A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies[J]. International Journal of Digital Earth, 6, 5-33(2013).

    [103] Chen H B. An overview of the space-based observations for upper atmospheric research[J]. Advances in Earth Science, 24, 229-241(2009).

    [104] Letu H S, Yang K, Nakajima T Y et al. High-resolution retrieval of cloud microphysical properties and surface solar radiation using Himawari-8/AHI next-generation geostationary satellite[J]. Remote Sensing of Environment, 239, 111583(2020).

    [105] Letu H S, Nakajima T Y, Wang T X et al. A new benchmark for surface radiation products over the East Asia-Pacific region retrieved from the Himawari-8/AHI next-generation geostationary satellite[J]. Bulletin of the American Meteorological Society, 1-40(2021).

    [106] Rausch J, Meyer K, Bennartz R et al. Differences in liquid cloud droplet effective radius and number concentration estimates between MODIS Collections 5.1 and 6 over global oceans[J]. Atmospheric Measurement Techniques, 10, 2105-2116(2017).

    [107] Shang H, Chen L, Bréon F M et al. Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument[J]. Atmospheric Measurement Techniques, 8, 4931-4945(2015).

    [108] Bréon F M, Tanré D, Generoso S. Aerosol effect on cloud droplet size monitored from satellite[J]. Science, 295, 834-838(2002).

    [109] Bréon F M, Goloub P. Cloud droplet effective radius from spaceborne polarization measurements[J]. Geophysical Research Letters, 25, 1879-1882(1998).

    [110] Shang H Z, Letu H S, Bréon F M et al. An improved algorithm of cloud droplet size distribution from POLDER polarized measurements[J]. Remote Sensing of Environment, 228, 61-74(2019).

    [111] Alexandrov M D, Cairns B, Emde C et al. Accuracy assessments of cloud droplet size retrievals from polarized reflectance measurements by the research scanning polarimeter[J]. Remote Sensing of Environment, 125, 92-111(2012).

    [112] Alexandrov M D, Cairns B, Wasilewski A P et al. Liquid water cloud properties during the Polarimeter Definition Experiment (PODEX)[J]. Remote Sensing of Environment, 169, 20-36(2015).

    [113] Seethala C, Horvath Á. Global assessment of AMSR-E and MODIS cloud liquid water path retrievals in warm oceanic clouds[J]. Journal of Geophysical Research, 115, D13202(2010).

    [114] Miller D J, Zhang Z B, Ackerman A S et al. The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: a theoretical study based on large-eddy simulations of shallow marine boundary layer clouds[J]. Journal of Geophysical Research, 121, 4122-4141(2016).

    [115] Hu Y X, Rodier S, Xu K M, liquid water content et al. 115: D00H34[J]. fraction of supercooled water clouds from combined CALIOP/IIR/MODIS measurements. Journal of Geophysical Research(2010).

    [116] Lee J, Yang P, Dessler A E et al. The influence of thermodynamic phase on the retrieval of mixed-phase cloud microphysical and optical properties in the visible and near-infrared region[J]. IEEE Geoscience and Remote Sensing Letters, 3, 287-291(2006).

    [117] Delanoë J. 115(D4): D00H29[J]. Hogan R J. Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds. Journal of Geophysical Research(2010).

    [118] Baum B A, Tovinkere V, Titlow J et al. Automated cloud classification of global AVHRR data using a fuzzy logic approach[J]. Journal of Applied Meteorology, 36, 1519-1540(1997).

    [119] Liu Y, Xia J, Shi C X et al. An improved cloud classification algorithm for China’s FY-2C multi-channel images using artificial neural network[J]. Sensors, 9, 5558-5579(2009).

    [120] Zhang C W, Zhuge X Y, Yu F. Development of a high spatiotemporal resolution cloud-type classification approach using Himawari-8 and CloudSat[J]. International Journal of Remote Sensing, 40, 6464-6481(2019).

    [121] Liu C, Yang S, Di D et al. A machine learning-based cloud detection algorithm for the Himawari-8 spectral image[J]. Advances in Atmospheric Sciences, 1-14(2021).

    [122] Tan Z H, Liu C, Ma S et al. Detecting multilayer clouds from the geostationary advanced Himawari imager using machine learning techniques[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-12(2022).

    [123] Min M, Li J, Wang F et al. Retrieval of cloud top properties from advanced geostationary satellite imager measurements based on machine learning algorithms[J]. Remote Sensing of Environment, 239, 111616(2020).

    [124] Zhang J L, Liu P, Zhang F et al. CloudNet: ground-based cloud classification with deep convolutional neural network[J]. Geophysical Research Letters, 45, 8665-8672(2018).

    [125] Li J M, Lü Q Y, Zhang M et al. Effects of atmospheric dynamics and aerosols on the fraction of supercooled water clouds[J]. Atmospheric Chemistry and Physics, 17, 1847-1863(2017).

    [126] Fu H L, Shen Y, Liu J et al. Cloud detection for FY meteorology satellite based on ensemble thresholds and random forests approach[J]. Remote Sensing, 11, 44(2018).

    [127] Wang Z M, Letu H S, Shang H Z et al. A supercooled water cloud detection algorithm using Himawari-8 satellite measurements[J]. Journal of Geophysical Research, 124, 2724-2738(2019).

    [128] Teng S W, Liu C, Zhang Z B et al. 47(16): e2020GL088941[J]. optical properties using passive radiometers. Geophysical Research Letters(2020).

    [130] Matsui T N, Suzuki K, Nakajima T Y et al. Interpretation of multi-wavelength-retrieved cloud droplet effective radii in terms of cloud vertical inhomogeneity using a spectral-bin microphysics cloud model and the radiative transfer computation[C]∥2011 IEEE International Geoscience and Remote Sensing Symposium, July 24-29, 2011, Vancouver, BC, Canada., 3229-3232(2011).

    [131] Huang J, Yu H, Guan X et al. Accelerated dryland expansion under climate change[J]. Nature Climate Change, 6, 166-171(2016).

    [132] Wu G, Liu Y, He B et al. Thermal controls on the Asian summer monsoon[J]. Scientific Reports, 2, 404(2012).

    [133] Lu C S, Liu Y G, Yum S S et al. A new approach for estimating entrainment rate in cumulus clouds[J]. Geophysical Research Letters, 39, L04802(2012).

    [134] Chen Y L, Chen G C, Cui C G et al. Retrieval of the vertical evolution of the cloud effective radius from the Chinese FY-4 (Feng Yun 4) next-generation geostationary satellites[J]. Atmospheric Chemistry and Physics, 20, 1131-1145(2020).

    [135] Kokhanovsky A A, Painemal D, Rozanov V V. The intercomparison of satellite-derived and in situ profiles of droplet effective radii in marine stratocumulus clouds[J]. IEEE Geoscience and Remote Sensing Letters, 10, 1147-1151(2013).

    [136] Chen H L, Chen L, Hu X Q et al. Effect of external stray light on low-light imager loaded in Fengyun-3 day/night orbit meteorological satellite[J]. Laser & Optoelectronics Progress, 54, 050101(2017).

    [137] Fougnie B, Marbach T, Lacan A et al. The multi-viewing multi-channel multi-polarisation imager-overview of the 3MI polarimetric mission for aerosol and cloud characterization[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 219, 23-32(2018).

    Tools

    Get Citation

    Copy Citation Text

    Huazhe Shang, Letu Husi, Ming Li, Jinghua Tao, Liangfu Chen. Remote Sensing of Cloud Properties Based on Visible-to-Infrared Channel Observation from Passive Remote Sensing Satellites[J]. Acta Optica Sinica, 2022, 42(6): 0600003

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Reviews

    Received: Dec. 28, 2021

    Accepted: Feb. 8, 2022

    Published Online: Mar. 15, 2022

    The Author Email: Husi Letu (husiletu@radi.ac.cn), Chen Liangfu (chenlf@radi.ac.cn)

    DOI:10.3788/AOS202242.0600003

    Topics