Original paper
Machine Learning Approach to Summer Precipitation Nowcasting over the Eastern Alps
Song, Linye; Schicker, Irene; Papazek, Petrina; Kann, Alexander; Bica, Benedikt; Wang, Yong; Chen, Mingxuan
Meteorologische Zeitschrift Vol. 29 No. 4 (2020), p. 289 - 305
46 references
published: Oct 20, 2020
published online: Dec 2, 2019
manuscript accepted: Oct 17, 2019
final revised version received: Oct 16, 2019
manuscript revision requested: Jul 1, 2019
manuscript received: May 23, 2019
Open Access (paper may be downloaded free of charge)
Abstract
This paper presents a new machine learning-based nowcasting model for hourly summer precipitation over the Eastern Alps. An artificial neural network (ANN) using the multi-layer perceptron algorithm was applied and evaluated against the Integrated Nowcasting through Comprehensive Analysis (INCA) nowcasting system and a multiple linear regression (MLR) model. Results show that the ANN model has a better nowcasting skill than the INCA model and the MLR model. The MLR model performs, too, also better than the INCA model. The improvement of precipitation intensity accuracy is substantial for both the morning to late evening period and for large rainfall thresholds. This study suggested that the machine learning approach is a promising methodology for precipitation forecasting.
Keywords
precipitation nowcasting • machine learning • INCA • Alps