• INFRARED
  • Vol. 41, Issue 4, 41 (2020)
Gen WANG1、2、3、*, Ya-jun LU4, Yue WANG4, Rui-jiao WU2, and Cong-hui DING2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    DOI: 10.3969/j.issn.1672-8785.2020.04.007 Cite this Article
    WANG Gen, LU Ya-jun, WANG Yue, WU Rui-jiao, DING Cong-hui. Research on Influence of Different Distance Measurements of KNN on Precipitation Retrieval by AGRI Infrared Bright Temperatures of FY-4A[J]. INFRARED, 2020, 41(4): 41 Copy Citation Text show less
    References

    [1] Wang G, Wang K F, Han W, et al. Typhoon maria precipitation retrieval and evolution based on the infrared brightness temperature of the Feng-Yun 4A/Advanced Geosynchronous Radiation Imager[J]. Advances in Meteorology, 2020, 2020:4245037.

    [3] Min M, Bai C, Guo J P, et al. Estimating summertime precipitation from Himawari-8 and global forecast system based on machine learning[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 57(5): 2557-2570.

    [6] Feidas H, Giannakos A. Identifying precipitating clouds in Greece using multispectral infrared Meteosat Second Generation satellite data[J]. Theoretical and Applied Climatology, 2011, 104(1-2): 25-42.

    [7] Thies B, Nauss T, Bendix J. Discriminating raining from non-raining clouds at mid-latitudes using meteosat second generation daytime data[J]. Atmospheric Chemistry and Physics, 2008, 8(9): 2341-2349.

    [8] Tebbi M A, Haddad B. Artificial intelligence systems for rainy areas detection and convective cells′ delineation for the south shore of Mediterranean Sea during day and nighttime using MSG satellite images[J]. Atmospheric Research, 2016, 178: 380-392.

    [9] Meike K, Appelhans T, Thies B, et al. Precipitation Estimates from MSG SEVIRI Daytime, Nighttime, and Twilight Data with Random Forests[J]. Journal of Applied Meteorology and Climatology, 2014, 53(11): 2457-2480.

    [10] Hirose H, Shige S, Yamamoto M K, et al. High temporal rainfall estimations from Himawari-8 multiband observations using the random-forest machine-learning method[J]. Journal of the Meteorological Society of Japan, 2019, 97(3): 689-710.

    [11] Ebtehaj A M, Bras R L, Foufoula-Georgiou E. Shrunken Locally Linear Embedding for Passive Microwave Retrieval of Precipitation[J], IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(7): 3720-3736.

    [13] Yang J, Zhang Z, Wei C, et al. Introducing the new generation of Chinese geostationary weather satellites-FengYun 4 (FY-4)[J]. Bulletin of the American Meteorological Society, 2017, 98(8): 1637-1658.

    [14] Sounak K B, Chandrasekar V. Cross-validation of observations between the GPM dual-frequency precipitation radar and ground based dual-polarization radars[J]. Remote Sensing, 2018, 10(11): 1773.

    WANG Gen, LU Ya-jun, WANG Yue, WU Rui-jiao, DING Cong-hui. Research on Influence of Different Distance Measurements of KNN on Precipitation Retrieval by AGRI Infrared Bright Temperatures of FY-4A[J]. INFRARED, 2020, 41(4): 41
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