Video-Based Convolutional Neural Networks Forecasting for Rainfall Forecasting

This study presents a new methodology for improving forecasts of current monthly, regional precipitation using video-based convolutional neural networks (CNNs). Using 13 administrative regions of Great Britain as a case study, three CNN architectures are trained for each region to forecast monthly r...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5
Hauptverfasser:	Barnes, Andrew P., Kjeldsen, Thomas R., McCullen, Nick
Format:	Artikel
Sprache:	eng
Schlagworte:	Air temperature Artificial neural networks Atmospheric precipitations Benchmark testing Benchmarks Convolutional neural networks Ensemble forecasting Errors Forecasting Hydrologic data Mathematical models Meteorology Modelling Monthly rainfall Neural networks Precipitation Precipitation forecasting Predictive models Rain Rainfall Rainfall data Rainfall forecasting Sea level Sea level forecasting Sea level pressure Spatial variations Training Weather forecasting
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