关键词: 偏差校正, 等比分布映射法, 日降水, 降水频率, RCP4.5情景

Abstract:

Bias correction of global climate model (GCM) outputs is essential for studies on the impact of climate change. Equiratio cumulative distribution functions matching (ERCDFm) method is a widely used bias correction method, and it has advantages in correcting future projections compared with the traditional Quantile Mapping method by preserving a consistent ratio between the observed and simulated values during reference and projection periods. However, the ability of modifying wet-day frequency would affect the performance of bias correction method. In this study, a newly developed frequency-dependent method was introduced into the ERCDFm to improve the simulation of precipitation days and total precipitation, which was achieved by complementing the insufficiency when the simulated number of precipitation days was underestimated, and adjusting the simulation of future wet-day frequency by preserving the trends in the raw GCM. The method was applied to the daily precipitation simulated by five GCMs from ISIMIP (Inter-Sectoral Impact Model Intercomparison Project) in both historical period and future RCP4.5 emission scenario over the Yangtze River Basin (YRB) using the gridded daily precipitation data (1961-2005) as observations. Results showed that the frequency-dependent ERCDFm correction method significantly improved the simulation with respect to wet-day frequency and mean precipitation. Compared to the original ERCDFm, the spatial correlation coefficients (CORs) between the corrected and observed wet-day frequency increased by 140% in spring, 85% in summer, 19% in autum, and 21% in winter by using the improved frequency-dependent ERCDFm method; the RMSE between the corrected and observed wet-day frequency and total precipitation reduced by 83% and 58%, respectively; and the area percentage of the precipitation biases within 50 mm/a increased from 31% to 49% over the YRB. In particular, the improved ERCDFm could alleviate the underestimation of total precipitation caused by the underestimated wet-day frequency. The bias-corrected GCM projections (2030-2050) of the ensemble mean indicated that the annual precipitation is expected to increase by 6.1% over the YRB under the RCP4.5 scenario relative to 1986-2005, with seasonal precipitation increasing by 8.2% in spring, 6.4% in summer, 4.7% in autumn, and 0.7% in winter. It is worth noting that the contribution of the change in wet-day frequency is of great importance to the total precipitation trend; therefore it is critical to retain the long-term change signal of wet-day frequency in the bias correction of daily precipitation.

Key words: bias correction, ERCDFm, daily precipitation, wet-day frequency, RCP4.5 emission scenario