基于贝叶斯模型平均的赣江与汉江流域多气候模式集合研究  

Multi-climate Model Ensemble in Ganjiang and Hanjiang Basins Based on Bayesian Model Average

作　　者：周梦瑶 袁飞[1] 江善虎[1] 张利敏 石佳勇 ZHOU Meng-yao;YUAN Fei;JIANG Shan-hu;ZHANG Li-min;SHI Jia-yong(College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China)

机构地区：[1]河海大学水文水资源学院,江苏南京210098

出　　处：《水电能源科学》2021年第9期1-5,共5页Water Resources and Power

基　　金：国家重点研发计划(2019YFC0409000);国家自然科学基金项目(51779070);中央高校基本科研业务费专项(2019B10314)。

摘　　要：采用贝叶斯模型平均法(BMA)集合第五次耦合模式比较计划8个气候模式模拟的赣江流域和汉江流域1961~2000年的月气温、月降水数据,评估了单气候模式和BMA集合气温和降水的精度及其误差时空间分布。结果表明,BMA集合的两个流域月降水和月气温相关系数明显高于单个气候模式,其相对误差和绝对误差低于多数单模式,流域平均的均方根误差最小,BMA集合的月降水和月气温总体优于单个集合成员,表明了BMA法在一定程度上提高了气候模式在研究区气温和降水模拟精度。The Bayesian model average(BMA)method was used to ensemble the monthly air temperature and precipitation data in the Ganjiang and the Hanjiang River basins from 1961-2000 simulated by eight climate models in the coupled model comparison program-phase 5.The accuracy and spatiotemporal variation of errors of the simulated air temperature and precipitation from climate models and BMA ensemble were evaluated.The results show that the correlation coefficients of the BMA-ensembled monthly precipitation and air temperature in the two basins were obviously higher than those of individual climate models.The BMA-ensembled monthly precipitation and air temperature had lower relative error and absolute error than most individual models,with the lowest average root mean square error.The BMA-ensembled monthly precipitation and air temperature was generally superior to individual climate models.This finding indicates that the BMA improved the performance of climate models in air temperature and precipitation simulations in the study area.

关 键 词：贝叶斯模型平均 第五次耦合模式比较计划 汉江流域 赣江流域 

分 类 号：P46[天文地球—大气科学及气象学]