More Accurate Climate Trend Attribution by Using Cointegrating Vector Time Series Models

Stephenson, D.B., Turasie, A.A. and Cummins, D.P. orcid.org/0000-0003-3600-5367 (2023) More Accurate Climate Trend Attribution by Using Cointegrating Vector Time Series Models. Sustainability, 15 (16). 12142. ISSN 2071-1050

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Item Type: Article
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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Keywords: climate trend; cointegration; detection; attribution; time series; VAR model; TLS; Error-Correction Model
Dates:
  • Published: 8 August 2023
  • Published (online): 8 August 2023
  • Accepted: 27 July 2023
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 12 Jul 2024 10:41
Last Modified: 12 Jul 2024 10:41
Status: Published
Publisher: MDPI
Identification Number: 10.3390/su151612142
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Sustainable Development Goals:
  • Sustainable Development Goals: Goal 13: Climate Action
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