In the Hong Kong Observatory, the Analogue Forecast System (AFS) for precipitation has been providing useful reference in predicting possible daily rainfall scenarios for the next 9 days, by identifying historical cases with similar weather patterns to the latest output from the deterministic model of the European Centre for Medium-Range Weather Forecasts (ECMWF). Recent advances in machine learning allow more sophisticated models to be trained using historical data and the patterns of high-impact weather events to be represented more effectively. As such, an enhanced AFS has been developed using the deep learning technique autoencoder. The datasets of the fifth generation of the ECMWF Reanalysis (ERA5) are utilised where more meteorological elements in higher horizontal, vertical and temporal resolutions are available as compared to the previous ECMWF reanalysis products used in the existing AFS. The enhanced AFS features four major steps in generating the daily rain class forecasts: (1) preprocessing of gridded ERA5 and ECMWF model forecast, (2) feature extraction by the pretrained autoencoder, (3) application of optimised feature weightings based on historical cases, and (4) calculation of the final rain class from a weighted ensemble of top analogues. The enhanced AFS demonstrates a consistent and superior performance over the existing AFS, especially in capturing heavy rain cases, during the verification period from 2019 to 2022. This paper presents the detailed formulation of the enhanced AFS and discusses its advantages and limitations in supporting precipitation forecasting in Hong Kong.

翻译：香港天文台的降水类比预报系统（AFS）通过识别与欧洲中期天气预报中心（ECMWF）确定性模式最新输出结果具有相似天气形势的历史个例，为未来9天的可能日降水情景预测提供了有价值的参考。机器学习的最新进展使得能够利用历史数据训练更复杂的模型，并更有效地表征高影响天气事件的形态特征。为此，本研究采用深度学习技术中的自编码器开发了增强型AFS。系统采用ECMWF第五代再分析数据集（ERA5），相较于现有AFS使用的早期ECMWF再分析产品，ERA5提供了更高水平、垂直及时间分辨率的多元气象要素。增强型AFS生成日降水等级预报包含四个主要步骤：（1）ERA5网格数据与ECMWF模式预报的预处理；（2）通过预训练自编码器进行特征提取；（3）基于历史个例应用优化特征权重；（4）通过加权集成最优类比个例计算最终降水等级。在2019年至2022年的验证期内，增强型AFS展现出较现有系统更稳定且优越的性能，尤其在强降水个例的捕捉方面。本文详述了增强型AFS的构建框架，并探讨了其在支持香港地区降水预报方面的优势与局限性。