Precipitation Estimates from MSG SEVIRI Daytime, Nighttime, and Twilight Data with Random Forests

@article{Khnlein2014PrecipitationEF,
  title={Precipitation Estimates from MSG SEVIRI Daytime, Nighttime, and Twilight Data with Random Forests},
  author={Meike K{\"u}hnlein and Tim Appelhans and Boris Thies and Thomas Nauss},
  journal={Journal of Applied Meteorology and Climatology},
  year={2014},
  volume={53},
  pages={2457-2480}
}
AbstractA new rainfall retrieval technique for determining rainfall rates in a continuous manner (day, twilight, and night) resulting in a 24-h estimation applicable to midlatitudes is presented. The approach is based on satellite-derived information on cloud-top height, cloud-top temperature, cloud phase, and cloud water path retrieved from Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) data and uses the random forests (RF) machine-learning algorithm… 

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