| 一种基于频率的GCM日降水偏差校正方法改进及其在长江流域的应用 |
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| 引用本文： | 岳书旭,胡实,莫兴国,占车生,刘苏峡.一种基于频率的GCM日降水偏差校正方法改进及其在长江流域的应用[J].地理研究,2021,40(5):1432-1444. |
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| 作者姓名： | 岳书旭 胡实 莫兴国 占车生 刘苏峡 |
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| 作者单位： | 中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室,北京100101;中国科学院大学中丹学院,北京100049;中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室,北京100101 |
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| 基金项目： | 国家重点研发计划(2017YFA0603702);第二次青藏高原综合科学考察研究(2019QZKK0403);中国科学院战略先导专项(A类)(XDA20040301) |
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| 摘 要： | 对全球气候模式（GCM）数据进行偏差校正是气候影响评估的前提和基础。通过在等比分布映射（ERCDFm）校正法中引入对降水频率的校正,增补了降水日数偏少情况下的小雨日数,保留了降水频率的长期变化信号,提高降水日数及总降水量的模拟效果。以长江流域1961—2005年的格点化日降水资料作为观测数据,对5个GCM模式历史期以及RCP4.5情景下未来日降水进行校正。结果表明：改进后的ERCDFm校正方法明显改善了降水频率及降水量的模拟。降水频率与年降水量的RMSE分别较改进前降低了83%和58%,偏差值小于50 mm/a的格点占比由改进前31%提高至49%,解决了由于降水频率模拟偏低导致的降水量低估。校正后的预估结果表明：RCP4.5情景下,相对于1986—2005年,2030—2050年长江流域降水呈增加趋势（平均增幅为6.1%）,春、夏、秋、冬各季节降水量的平均增幅为8.2%、6.4%、4.7%和0.7%。
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| 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 |
| 收稿时间： | 2020-05-25 |
Improved frequency-dependent bias correction method for GCM daily precipitation and its application in Yangtze River Basin |
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| YUE Shuxu,HU Shi,MO Xingguo,ZHAN Chesheng,LIU Suxia.Improved frequency-dependent bias correction method for GCM daily precipitation and its application in Yangtze River Basin[J].Geographical Research,2021,40(5):1432-1444. |
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| Authors: | YUE Shuxu HU Shi MO Xingguo ZHAN Chesheng LIU Suxia |
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| Institution: | 1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China2. College of Sino-Danish Center, University of Chinese Academy of Sciences, Beijing 100049, China |
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| 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. |
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| Keywords: | bias correction ERCDFm daily precipitation wet-day frequency RCP4 5 emission scenario |
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