统计降尺度法在数值预报产品释用中的应用

Application of Statistical Downscaling Method to Numerical Weather Forecast

目前数值模式输出的空间分辨率较低,缺少区域信息,很难对区域气候做精确的预测。降尺度方法通过把大尺度、低分辨率的数值模式输出信息转化为区域尺度的地面气候变化信息(如气温、降水),从而达到弥补数值模式预测区域未来气候变化不足的目的。这种做法的基础在于区域气候变化是以大尺度(如大陆尺度甚至行星尺度)气候为条件的。统计降尺度法以大尺度数值预报产品为预报因子,利用历史资料建立区域预报量与大尺度预报因子之间的统计模型,实现对数值预报产品的释用。在系统论述统计降尺度法的基本原理、一般步骤的基础上,初步探讨统计降尺度法在中期天气预报方面的应用。

Numerical forecast models are widely used as an important tool of projecting global climate change. However, their resolution is too coarse to provide the regional scale information. Therefore, downscaling methods for extracting regional scale information from output of numerical forecast models are developed. Statistical downscaling techniques can be used to predict regional scale climate by using statistical relationship between the large-scale climate and the regional scale climate. On the basis of introducing the theory and approach of statistical downscaling, application of statistical downscaling to the medium term weather forecast was simply discussed.