基于分段三伽玛分布的降雨偏差纠正方法

为解决全球气候模式模拟降雨与实测降雨存在较大偏差的问题，提出了一种基于分段三伽玛分布的偏差纠正方法。该方法将降雨序列按其分位点分为极小值、常规值和极大值3部分，分别对3部分降雨序列的累积概率分布曲线进行偏差纠正；基于分位数偏差累积思想提出了一种综合性评价指标C，对分段三伽玛方法的偏差纠正效果进行综合评估。应用该方法对CMIP5下18个GCMs在雅鲁藏布江附近17个气象站点的模拟降雨进行偏差纠正，并与单伽玛方法和双伽玛方法进行对比分析。结果表明:分段三伽玛方法可以很好地消除GCMs模拟降雨与实测降雨的偏差，率定期和验证期的偏差纠正效果大多在0.85以上；相比单伽玛和双伽玛方法，分段三伽玛方法在验证期的偏差纠正效果更好，表现更稳健。

A separated three-gamma bias correction method for precipitation

To solve the problem that there exists large bias between simulated precipitation from global climate models (GCMs) and measured precipitation, a bias correction method based on separated three gamma distributions (STG) was proposed. This method divides the precipitation sequence into three parts, i.e., the minimum values, the normal values and the maximum values, and then the cumulative distribution functions (CDFs) of these three parts are respectively bias corrected. In addition, based on the thought of quantile deviation accumulation, a comprehensive evaluation index C is also put forward to evaluate the bias correction effects of STG method. The STG method is applied to correct the bias between the simulated precipitation from 18 GCMs and measured precipitation for 17 meteorological stations in Yarlung Tsangpo River basin, and is further compared with the existing two gamma-related bias correction methods, i.e., Single Gamma (SG) and Double Gamma (DG). The results show that the STG method can effectively remove the bias between GCMs simulated precipitation and observed precipitation, and the evaluation indexes C are mostly above 0.85. Moreover, STG performes better than SG and DG in the validation period which indicates STG is more robust for bias correcting GCMs simulated precipitation.