福建电脑2024，Vol.40Issue(1)：1-8,8.DOI:10.16707/j.cnki.fjpc.2024.01.001
中短期降水预报的多分支融合卷积神经网络
Multi-branch Fusion Convolutional Neural Network for Short-and Medium-range Precipitation Forecast Post-processing
摘要
Abstract
Precipitation is easily affected by multi-scale weather systems,resulting in low accuracy of model precipitation forecasts,requiring additional post-processing to correct for bias in the results.In order to improve the accuracy of medium-and short-term precipitation forecasting,this paper proposes a deep learning correction model that uses a multi branch fusion convolution module to extract the spatial features of the forecast factor field and between factors,achieving spatial fusion of multiple forecast factors.Meanwhile,a loss function is proposed to address the issue of imbalanced precipitation samples,in order to enhance the model's ability to correct precipitation.The experimental results show that the method proposed in this paper can improve the correction ability of medium-and short-term precipitation forecasting.关键词
中短期降水预报/后处理/深度学习Key words
Medium-And Short-Term Precipitation Forecasting/Post-Processing/Deep Learning分类
信息技术与安全科学引用本文复制引用
江铭恒,游立军,翁彬,陈家祯..中短期降水预报的多分支融合卷积神经网络[J].福建电脑,2024,40(1):1-8,8.基金项目
本文得到福建省科技厅引导性项目"福建省前汛期持续性强降水过程延伸期预报的人工智能技术研究"(No.2021Y0057)、福建省科技厅引导性项目"基于深度时刻多尺度交叉注意力的华南前汛期极端降水延伸期预报研究"(No.2022Y0008)资助. （No.2021Y0057）
