基于RegCM4模式的中国区域日尺度降水模拟误差订正

气候模式模拟得到的各气候变量与观测相比，总会存在一定的偏差，所得到的气候变化预估结果难以在影响评估模型中直接应用。本文尝试对一个区域气候模式（RegCM4.4）所模拟的中国区域逐日降水，基于概率分布（分位数映射）方法进行统计误差订正。在订正过程中，以模拟时段1991~2010年中的前半段（1991~2000年）作为参照时段，建立传递函数，对后一时段（2001~2010年）进行订正并检验其效果。首先对使用参数和非参数所建立的6种不同传递函数方法进行对比，发现6种方法均可明显减少降水模拟的误差，其中利用非参数转换建立传递函数的RQUANT方法效果更好。随后进一步分析了采用该方法对模式模拟降水所做订正的效果，结果表明，该方法可以明显改善对平均降水，以及降水年际变率和极端事件的模拟结果。

Bias Correction of Daily Precipitation Simulated by RegCM4 Model over China

There are biases in climate model simulations compared to the observations, which makes it hard to directly use model simulations to drive the impact models. In the present study, the authors try to correct biases in daily precipitation simulated by a regional climate model (RegCM4.4) based on probability distribution (Quantile-Mapping) over China. Transfer functions are established from the reference period 1991-2000, and then applied to the period 2001-2010 to validate the performance of the method. Six different methods using parametric or nonparametric transformations are employed and compared to observations. Results show that all the six methods can effectively reduce the biases of the precipitation simulated, the RQUANT (Non-parametric quantile mapping using robust empirical quantiles) is found to perform better than other methods. Further analysis shows that RQUANT can significantly improve the simulation of the mean precipitation and the interannual variability and extreme events.