Articles | Volume 26, issue 6
https://doi.org/10.5194/hess-26-1631-2022
https://doi.org/10.5194/hess-26-1631-2022
Research article
 | 
25 Mar 2022
Research article |  | 25 Mar 2022

Improving radar-based rainfall nowcasting by a nearest-neighbour approach – Part 1: Storm characteristics

Bora Shehu and Uwe Haberlandt

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Cited articles

Ayzel, G., Scheffer, T., and Heistermann, M.: RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting, Geosci. Model Dev., 13, 2631–2644, https://doi.org/10.5194/gmd-13-2631-2020, 2020. 
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Short summary
In this paper we investigate whether similar storms behave similarly and whether the information obtained from past similar storms can improve storm nowcast based on radar data. Here a nearest-neighbour approach is employed to first identify similar storms and later to issue either a single or an ensemble nowcast based on k most similar past storms. The results indicate that the information obtained from similar storms can reduce the errors considerably, especially for convective storm nowcast.
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