文章基本信息

标题：Understanding long-term memory in global mean temperature An attribution study based on model simulations
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作者：Min QIU ; Naiming YUAN ; Shujie YUAN 等
期刊名称：Atmospheric and Oceanic Science Letters
印刷版ISSN：1674-2834
电子版ISSN：2376-6123
出版年度：2020
卷号：13
期号：5
页码：485-492
DOI：10.1080/16742834.2020.1778418
语种：English
出版社：Taylor and Francis Ltd
摘要：Long-term memory (LTM) in the climate system has been well recognized and applied in different research fields, but the origins of this property are still not clear. In this work, the authors contribute to this issue by studying model simulations under different scenarios. The global mean temperatures from pre-industrial control runs (piControl), historical (all forcings) simulations, natural forcing only simulations (HistoricalNat), greenhouse gas forcing only simulations (HistoricalGHG), etc., are analyzed using the detrended fluctuation analysis. The authors find that the LTM already exists in the piControl simulations, indicating the important roles of internal natural variability in producing the LTM. By comparing the results among different scenarios, the LTM from the piControl runs is further found to be strengthened by adding natural forcings such as the volcanic forcing and the solar forcing. Accordingly, the observed LTM in the climate system is suggested to be mainly controlled by both the ‘internal’ natural variability and the ‘external’ natural forcings. The anthropogenic forcings, however, may weaken the LTM. In the projections from RCP2.6 to RCP8.5, a weakening trend of the LTM strength is found. In view of the close relations between the climate memory and the climate predictability, a reduced predictability may be expected in a warming climate.
关键词：Long-term memory;model simulations;attribution;detrended fluctuation analysis;长期记忆性;模式模拟;归因;去趋势的波动分析方法