RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting

GSTDTAP > 资源环境科学

DOI	10.5194/gmd-13-2631-2020
	RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting
	admin
	2020-06-23
出版年	2020
国家	欧洲
领域	气候变化 ; 资源环境
英文摘要	In this study, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting, which was trained to predict continuous precipitation intensities at a lead time of 5 min. RainNet significantly outperformed the benchmark models at all lead times up to 60 min. Yet, an undesirable property of RainNet predictions is the level of spatial smoothing. Obviously, RainNet learned an optimal level of smoothing to produce a nowcast at 5 min lead time.
URL	查看原文
来源平台	European Geosciences Union
引用统计
文献类型	科技报告
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/277864
专题	资源环境科学气候变化
推荐引用方式 GB/T 7714	admin. RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting,2020.