发表机构
Southern University of Science and Technology; Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation（南方科技大学; 广东省类脑智能计算重点实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
FreCast是一种两阶段雷达回波预测框架，以初始预报的空间结构为约束校正回波强度偏差，在三个数据集上提升了预报技能，更好保留雨带与强降水结构。
AI 中文摘要
临近降水预报通过历史雷达回波序列预测未来雷达回波的时空演化，从而估算短期内降水的发生、发展与移动情况。近年来，深度学习已成为临近降水预报的重要方法。尽管当前最先进的模型通常能够捕捉未来降水的整体空间分布，但其预测结果在各位置的雷达回波强度仍存在显著偏差。这一发现促使人们采用更具针对性的策略来减少预报误差。与无空间约束地重新生成整个雷达回波序列不同，可利用预测的降水结构来指导各位置回波强度的优化。这种结构引导的优化直接针对回波强度偏差。据此，我们提出FreCast，这是一个用于雷达回波预测的两阶段框架：第一阶段生成未来雷达回波的初始预报；第二阶段将初始预报的空间结构作为约束，进一步校正第一阶段预测中各位置的强度偏差。在三个数据集上的实验表明，FreCast在各项预报技能指标上均取得了一致提升，定性结果进一步显示，FreCast在更长预见期内能够更好地保持雨带连续性和强降水结构。
英文摘要
Precipitation nowcasting predicts the spatiotemporal evolution of future radar echoes from historical radar echo sequences, thereby estimating the occurrence, development, and movement of precipitation over the near term. In recent years, deep learning has become an important approach to precipitation nowcasting. Although state-of-the-art models can generally capture the overall spatial distribution of future precipitation, their predictions still exhibit substantial biases in radar echo intensity at individual locations. This observation motivates a more targeted strategy for reducing forecast errors. Instead of regenerating an entire radar echo sequence without spatial constraints, the predicted precipitation structure can be used to guide the refinement of echo intensities at individual locations. This structure-guided refinement directly targets echo intensity biases. Accordingly, we propose FreCast, a two-stage framework for radar echo prediction. The first stage generates an initial forecast of future radar echoes. The second stage uses the spatial structure of the initial forecast as a constraint to further correct intensity biases at individual locations in the first-stage prediction. Experiments on three datasets demonstrate that FreCast achieves consistent improvements across forecast skill metrics. Qualitative results further show that FreCast better preserves rainband continuity and intense precipitation structures at longer lead times.
