[1] Viúdez-Mora A, Costa-Surós M, Calbó J et al. Modeling atmospheric longwave radiation at the surface during overcast skies: the role of cloud base height[J]. Journal of Geophysical Research: Atmospheres, 120, 199-214(2015).
[2] Herzegh P, Wiener G, Bateman R et al. Data fusion enables better recognition of ceiling and visibility hazards in aviation[J]. Bulletin of the American Meteorological Society, 96, 526-532(2015).
[3] Yan W, Han D, Zhou X K et al. Analysing the structure characteristics of tropical cyclones based on CloudSat satellite data[J]. Chinese Journal of Geophysics, 56, 1809-1824(2013).
[4] Kahn B H, Chahine M T, Stephens G L et al. Cloud type comparisons of AIRS, CloudSat, and CALIPSO cloud height and amount[J]. Atmospheric Chemistry and Physics, 8, 1231-1248(2008).
[5] Shang H Z, Husi L T, Li M et al. Remote sensing of cloud properties based on visible-to-infrared channel observation from passive remote sensing satellites[J]. Acta Optica Sinica, 42, 0600003(2022).
[6] Hutchison K D. The retrieval of cloud base heights from MODIS and three-dimensional cloud fields from NASA’s EOS Aqua mission[J]. International Journal of Remote Sensing, 23, 5249-5265(2002).
[7] Liou K N[M]. Radiation and cloud processes in the atmosphere: theory, observation and modeling(1992).
[8] Seaman C J, Noh Y J, Miller S D et al. Cloud-base height estimation from VIIRS. part I: operational algorithm validation against CloudSat[J]. Journal of Atmospheric and Oceanic Technology, 34, 567-583(2017).
[9] Noh Y J, Forsythe J M, Miller S D et al. Cloud-base height estimation from VIIRS. part Ⅱ: a statistical algorithm based on a-train satellite data[J]. Journal of Atmospheric and Oceanic Technology, 34, 585-598(2017).
[10] Forsythe J M, Haar T H V, Reinke D L. Cloud-base height estimates using a combination of meteorological satellite imagery and surface reports[J]. Journal of Applied Meteorology, 39, 2336-2347(2000).
[11] Wang S H, Yao Z G, Han Z G et al. Feasibility analysis of extending the spatial coverage of cloud-base height from CloudSat[J]. Meteorological Monthly, 38, 210-219(2012).
[12] Li H R, Sun X J, Liu L et al. Cloud base height estimation based on template matching[J]. Journal of the Meteorological Sciences, 35, 610-615(2015).
[13] Gao D. Research on cloud base height retrieval and application based on FY-4A[D](2018).
[14] Tan Z H, Ma S, Han D et al. Estimation of cloud base height for FY-4A satellite based on random forest algorithm[J]. Journal of Infrared and Millimeter Waves, 38, 381-388(2019).
[15] Tan Z H, Huo J, Ma S et al. Estimating cloud base height from Himawari-8 based on a random forest algorithm[J]. International Journal of Remote Sensing, 42, 2485-2501(2021).
[16] Lin H, Li Z L, Li J et al. Estimate of daytime single-layer cloud base height from advanced baseline imager measurements[J]. Remote Sensing of Environment, 274, 112970(2022).
[17] Huang P Y, Guo Q, Han C P et al. Research on retrieval of temperature profile on cloud based on FY-4A/GIIRS data[J]. Laser＆Optoelectronics Progress, 58, 1701002(2021).
[18] Xu W J, Lü D R. Evaluation of cloud mask and cloud top height from Fengyun-4A with MODIS cloud retrievals over the Tibetan Plateau[J]. Remote Sensing, 13, 1418(2021).
[19] Lai R Z, Teng S W, Yi B Q et al. Comparison of cloud properties from Himawari-8 and FengYun-4A geostationary satellite radiometers with MODIS cloud retrievals[J]. Remote Sensing, 11, 1703(2019).
[20] Cui L L, Guo W, Ge W Q et al. Comparisons of cloud top parameter of FY-4A satellite and its typhoon application research[J]. Plateau Meteorology, 39, 196-203(2020).
[21] Yu Z F, Ma S, Hu X et al. Analysis of atmospheric circulation, cloud and precipitation characteristics of typhoon “Lekima”based on multi-source data[J]. Journal of the Meteorological Sciences, 40, 41-52(2020).
[22] Wang Q P, Zhu W N, Wang Y et al. Preliminary application of FY-4A satellite data in dense fog weather events at Urumqi international airport[J]. Meteorological Monthly, 47, 627-637(2021).
[23] Yuan J H, Zhou Y B, Liu Y B et al. Effect of cloud droplet spectrum distribution on retrievals of water cloud optical thickness and effective particle radius by AGRI onboard FY-4A satellite[J]. Acta Optica Sinica, 42, 0628004(2022).
[24] Lao P, Liu Q, Ding Y H et al. Rainrate estimation from FY-4A cloud top temperature for mesoscale convective systems by using machine learning algorithm[J]. Remote Sensing, 13, 3273(2021).
[25] Liu P, Yang Y, Gao J D et al. An approach for assimilating FY4 lightning and cloud top height data using 3DVAR[J]. Frontiers in Earth Science, 8, 288(2020).
[27] 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).
[28] Zhou Z H[M]. Machine learning(2016).
[29] Breiman L. Random forests[J]. Machine Learning, 45, 5-32(2001).
[30] Li Z, Zhang Q Y, Kong L H et al. Hardness characterization of GCrl5 steel based on laser-induced breakdown spectroscopy and random forest[J]. Chinese Journal of Lasers, 0911002(2022).
[31] Friedman J H. Greedy function approximation: a gradient boosting machine[J]. The Annals of Statistics, 29, 1189-1232(2001).
[32] Yu Z F, Ma S, Han D et al. A cloud classification method based on random forest for FY-4A[J]. International Journal of Remote Sensing, 42, 3353-3379(2021).
[33] Li W L, Li X J, Tu H W et al. Relationship between spectral response non-uniformity of pixels and stripe noise[J]. Acta Optica Sinica, 42, 1211001(2022).
