Modeling and forecasting the long memory of Cyclical Trends in paleoclimate data

This paper identifies and estimates the relevant cycles in paleoclimate data of earth temperature, ice volume and CO2. Cyclical cointegration analysis is used to connect these cycles to the earth eccentricity and obliquity and to see that the earth surface temperature and ice volume are closely conn...

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Bibliographic Details
Published in:Energy economics Vol. 147; p. 108520
Main Authors: Castro, Tomas del Barrio, Escribano, Alvaro, Sibbertsen, Philipp
Format: Journal Article
Language:English
Published: Elsevier B.V 01.06.2025
Subjects:
Cyclical fractional cointegration
Forecasting climate data
Paleoclimate cycles
C53
Cyclical fractional cointegration
C22
Forecasting climate data
C32
Paleoclimate cycles
ISSN:0140-9883
Online Access:Get full text
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Summary:This paper identifies and estimates the relevant cycles in paleoclimate data of earth temperature, ice volume and CO2. Cyclical cointegration analysis is used to connect these cycles to the earth eccentricity and obliquity and to see that the earth surface temperature and ice volume are closely connected. These findings are used to build a forecasting model including the cyclical component as well as the relevant earth and climate variables which outperforms models ignoring the cyclical behavior of the data. Especially the turning points can be predicted accurately using the proposed approach. Out of sample forecasts for the turning points of earth temperature, ice volume and CO2 are derived. •Climate variables for the last 800.000 years from antarktic ice cores are considered.•Relevant orbital cycles driving temperature, ice and CO2 are identified.•Cyclical cointegration analysis proves connectedness.•A forecasting model has been developed and turning points for climate variables are predicted.•The influence of humanity has been isolated.
ISSN:0140-9883
DOI:10.1016/j.eneco.2025.108520