摘要
利用全球气候模式、多模式集合和辽宁省气象观测数据,评估了不同典型浓度路径下19个全球气候模式和多模式集合对辽宁省气温变化模拟能力和可信度。结果表明:最优模式模拟结果优于多模式集合,具有较高的可信度。随着全球二氧化碳排放浓度增加,气温变化率和可信度呈增加趋势,首次达到2℃年份呈提前趋势,大部分站点出现在2011年之前,且出现年份越晚,升幅往往越高,反之亦然。大部分站点首次稳定到达2℃阈值开始年份在2022年之前,结束年份出现在2019—2026年,持续时间在13 a以下,开始年份均呈西早—东晚分布形势,结束时间和持续时间分布较均匀,且随着全球二氧化碳排放浓度增加,升温幅度呈上升趋势。不同典型浓度路径下各区域最高温、最低温和平均气温出现年份和变化特征均比较一致。
Using the 19 global climate models,ensemble models in conjunction with the observational data in Liaoning province,we evaluated the accuracy and credibility of air temperature simulated by different models under different typical concentration paths.The results indicate that the optimal model simulation performs better and has higher credibility than ensemble simulation.With the increase in emissions and concentrations of carbon dioxide,the change rate and credibility in simulated air temperature tend to show an increasing trend,and the beginning years when the temperature increment is beyond 2℃for the first time,occur before 2011 at most stations.The later the beginning year is,the higher the temperature increments,and vice versa.The beginning years with temperature increment of stably by 2℃occur before 2022 at most stations,and the ending years occur between 2019 and 2016,with a duration of less than 13 years.The beginning years occur earlier in the western region than in the eastern region in Liaoning province,while the ending years and duration time distribute more even.With the increase in global emissions and concentrations of carbon dioxide,the warming rate increases.Occurrence time and variation trend of the maximum,minimum,and average temperatures in different regions under different typical concentration paths are basically consistent with each other.
作者
王涛
王乙舒
沈玉敏
王艳
赵连伟
王小桃
沈历都
WANG Tao;WANG Yi-shu;SHEN Yu-min;WANG-Yan;ZHAO Lian-wei;WANG Xiao-tao;SHEN Li-du(Shenyang Regional Climate Center,Shenyang 110166,China;Liaoning Meteorological Information Center,Shenyang 110166,China)
出处
《气象与环境学报》
2020年第2期49-61,共13页
Journal of Meteorology and Environment
基金
中国气象局2016年气候变化专项(CCSF201608)
辽宁省科技农业攻关及产业化项目(2015103038)
中国气象局2019年气候变化专项(CCSF201910)
辽宁省气象局科研项目(BA201606)共同资助。
关键词
全球气候模式
多模式集合
升温幅度
2℃阈值
Global climate models
Multi-model ensemble
Magnitude of the warming
2℃threshold
