The study of climate change adaptation plans for drainage infrastructure in a small country as that of Singapore, rainfall projections on the time scale of minutes and on the spatial scales of 1 km are deemed appropriate In this paper, we introduce an application of radar-based stochastic downscaling for rainfall projections at high temporal and spatial resolutions. The input for stochastic model is derived from a Regional Climate Model. The sub-hourly extreme rainfall intensity derived from stochastic model outputs was validated against observed rain-gauge data over the historical period. Considering the advantage in computational efficiency of the stochastic downscaling method, thousand scenarios of rainfall projections at very high temporal and spatial resolution were generated. The implication of this approach is that, from these stochastically downscaled time series of rainfall, it is possible to study future sub-hourly extreme rainfall intensities which would be useful to address issue of flash floods/drainage systems.

在像新加坡这样的小国中，对排水基础设施的气候变化适应计划的研究，以分钟为单位的时间尺度和1 km的空间尺度的降雨预测被认为是适当的。在本文中，我们介绍了基于雷达的应用高时空分辨率下降雨预测的随机降尺度。随机模型的输入来自区域气候模型。根据历史时期的观测雨量数据，验证了随机模型输出得出的亚小时极端降雨强度。考虑到随机缩减方法在计算效率方面的优势，生成了数千种时空分辨率很高的降雨预测方案。这种方法的含义是，