Three deterministic prediction evaluation methods,including the standard deviation,root-mean-square error,and time correlation coefficient,and three extreme temperature indices were used to assess the performance of t...Three deterministic prediction evaluation methods,including the standard deviation,root-mean-square error,and time correlation coefficient,and three extreme temperature indices were used to assess the performance of the BCC_CSM2_MR model from CMIP6 in simulating the climate of Northwest China based on monthly grid air temperature data from ground stations.The model performance was evaluated using the daily mean temperature,daily minimum temperature,and daily maximum temperature from 1961 to 2014 and future temperature changes in Northwest China under different radiative forcing scenarios.The BCC_CSM2_MR model reproduces well the seasonal changes,spatial distribution,and other characteristics of the daily mean temperature in Northwest China,especially in the Tarim Basin,the Kunlun and Qilian mountains,and Shaanxi.There is still some deviation in the simulation of the daily mean temperature in the high terrains of the Tianshan,Kunlun,and Altai mountains.The model better simulates the daily minimum temperature than the daily maximum temperature.The simulation error is smallest in summer,followed by autumn and winter,and largest in spring.In terms of extreme temperature indices,the deviations are smaller for cold nights,warm nights,and the annual maximum daily minimum temperatures.Furthermore,the model can capture the increase in warm events and the decrease in cold events.Under different forcing scenarios,there is a general warming trend in Northwest China,with the greatest warming in Xinjiang.展开更多
基金supported by the Numerical model development project of China Meteorological Administration(QHMS2018018,QHMS2019016)Research Fund Project of Chengdu University of Information Technology(KYTZ201721)
文摘Three deterministic prediction evaluation methods,including the standard deviation,root-mean-square error,and time correlation coefficient,and three extreme temperature indices were used to assess the performance of the BCC_CSM2_MR model from CMIP6 in simulating the climate of Northwest China based on monthly grid air temperature data from ground stations.The model performance was evaluated using the daily mean temperature,daily minimum temperature,and daily maximum temperature from 1961 to 2014 and future temperature changes in Northwest China under different radiative forcing scenarios.The BCC_CSM2_MR model reproduces well the seasonal changes,spatial distribution,and other characteristics of the daily mean temperature in Northwest China,especially in the Tarim Basin,the Kunlun and Qilian mountains,and Shaanxi.There is still some deviation in the simulation of the daily mean temperature in the high terrains of the Tianshan,Kunlun,and Altai mountains.The model better simulates the daily minimum temperature than the daily maximum temperature.The simulation error is smallest in summer,followed by autumn and winter,and largest in spring.In terms of extreme temperature indices,the deviations are smaller for cold nights,warm nights,and the annual maximum daily minimum temperatures.Furthermore,the model can capture the increase in warm events and the decrease in cold events.Under different forcing scenarios,there is a general warming trend in Northwest China,with the greatest warming in Xinjiang.
