Extracting and analyzing the warming trend in global and hemispheric temperatures

This article offers an updated and extended attribution analysis based on recently published versions of temperature and forcing datasets. It shows that both temperature and radiative forcing variables can be best represented as trend stationary processes with structural changes occurring in the slo...

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Bibliographic Details
Published in:Journal of Time Series Analysis
Main Authors: Estrada, Francisco, Perron, Pierre
Format: Article in Journal/Newspaper
Language:English
Published: WILEY 2017
Subjects:
Science & technology
Physical sciences
Mathematics
interdisciplinary applications
Statistics & probability
Climate change
Warming hiatus
Structural break
Co-trending
Principal component analysis
Stationary noise component
Surface air-temperature
Anthropogenic climate-change
Time-series analysis
North-Atlantic
Stochastic trends
Simulations
Econometrics
North Atlantic
Online Access:https://hdl.handle.net/2144/26267
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000409322700004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e74115fe3da270499c3d65c9b17d654
https://doi.org/10.1111/jtsa.12246
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Summary:This article offers an updated and extended attribution analysis based on recently published versions of temperature and forcing datasets. It shows that both temperature and radiative forcing variables can be best represented as trend stationary processes with structural changes occurring in the slope of their trend functions and that they share a common secular trend and common breaks, largely determined by the anthropogenic radiative forcing. The common nonlinear trend is isolated, and further evidence on the possible causes of the current slowdown in warming is presented. Our analysis offers interesting results in relation to the recent literature. Changes in the anthropogenic forcings are directly responsible for the hiatus, while natural variability modes such as the Atlantic Multidecadal Oscillation, as well as new temperature adjustments, contribute to weaken the signal. In other words, natural variability and data adjustments do not explain in any way the hiatus; they simply mask its presence.

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