DOI: 10.1002/2017JD028078
Scopus记录号: 2-s2.0-85046268782
论文题名: Reproducing Long-Range Correlations in Global Mean Temperatures in Simple Energy Balance Models
作者: Meyer P. ; Hoell M. ; Kantz H.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2018
卷: 123, 期: 9 起始页码: 4413
结束页码: 4422
语种: 英语
Scopus关键词: correlation
; data set
; energy balance
; global perspective
; model
; surface temperature
; temperature
英文摘要: We study global mean surface temperature records since 1850 and their potential forcings. We find long range correlations by the method of detrended fluctuation analysis in most data sets, in agreement with previous studies. As a predictive model, we employ a zero-dimensional energy balance model without memory that reproduces temperature data on the timescale of years. Even when driven with white noise, this model generates data that reproduce the observed long-range correlations. We are able to explain this with theoretical results for the AR(1) process, which demonstrates that even processes with exponentially decaying correlations yield nontrivial detrended fluctuation analysis results if the available data set is too short. This article gives new support to the scepticism about long memory in global mean temperatures and discusses further implications of our findings. ©2018. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/113905
Appears in Collections: 气候减缓与适应
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作者单位: Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
Recommended Citation:
Meyer P.,Hoell M.,Kantz H.. Reproducing Long-Range Correlations in Global Mean Temperatures in Simple Energy Balance Models[J]. Journal of Geophysical Research: Atmospheres,2018-01-01,123(9)