A machine learning based 24-h-technique for an area-wide rainfall retrieval using MSG SEVIRI data over Central Europe

The aim of the present study was to develop a 24-h-technique for the process-related and quantitative estimation of precipitation in connection with extra-tropical cyclones in the mid-latitudes based on MSG SEVIRI data using the machine learning algorithm random forest. The algorithms and approach...

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Bibliographic Details
Main Author: Kühnlein, Meike
Contributors: Nauss, Thomas (Prof.) (Thesis advisor)
Format: Doctoral Thesis
Language:English
Published: Philipps-Universität Marburg 2014
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Call Number: urn:nbn:de:hebis:04-z2014-04754
Publication Date: 2014-12-16
Date of Acceptance: 2014-11-18
Downloads: 53 (2024), 78 (2023), 101 (2022), 95 (2021), 126 (2020), 113 (2019), 59 (2018)
License: https://rightsstatements.org/vocab/InC-NC/1.0/
Access URL: https://archiv.ub.uni-marburg.de/diss/z2014/0475
https://doi.org/10.17192/z2014.0475