Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts
Climate variables are known to be subject to abrupt changes when some threshold levels are surpassed. We use data for the last 798,000 years on global ice volume (Ice), atmospheric carbon dioxide level (CO2), and Antarctic land surface temperature (Temp) to model and measure those long-run nonlinear...
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ftunivcarlosmadr:oai:e-archivo.uc3m.es:10016/38532 2024-01-21T10:00:53+01:00 Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts Escribano, Álvaro Ministerio de Economía y Competitividad (España) Agencia Estatal de Investigación (España) Comunidad de Madrid 2023-02-01 http://hdl.handle.net/10016/38532 https://doi.org/10.1016/j.eneco.2023.106522 eng eng Elsevier Gobierno de España. RTI2018-101371-B-I00 Gobierno de España. ECO2016-00105-001 Gobierno de España. MDM 2014-0431 Comunidad de Madrid. S2015/HUM-3444 Blazsek, S., & Escribano, A. (2023). Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts. Energy Economics, Vol. 118, p. 106522. 0140-9883 http://hdl.handle.net/10016/38532 https://doi.org/10.1016/j.eneco.2023.106522 Energy Economics 118 AR/0000033069 © The authors Atribución 3.0 España http://creativecommons.org/licenses/by/3.0/es/ open access Antarctic land surface temperature Atmospheric CO2 level Climate change Dynamic conditional score Generalized autoregressive score Global ice volume Score-driven ice-age models C32 C38 C51 C52 C53 Q54 Economía research article VoR 2023 ftunivcarlosmadr https://doi.org/10.1016/j.eneco.2023.106522 2023-12-27T00:21:11Z Climate variables are known to be subject to abrupt changes when some threshold levels are surpassed. We use data for the last 798,000 years on global ice volume (Ice), atmospheric carbon dioxide level (CO2), and Antarctic land surface temperature (Temp) to model and measure those long-run nonlinear climate effects. The climate variables have very long and asymmetric cycles, created by periods of upward trends, followed by periods of downward trends driven by exogenous orbital variables. The exogenous orbital variables considered by the Milankovitch cycles are eccentricity of Earth's orbit, obliquity, and precession of the equinox. We show that our new score-driven threshold ice-age models improve the statistical inference and forecasting performance of competing ice-age models from the literature. The drawback of using our 1000-year frequency observations, is that we cannot measure the nonlinear climate effects of humanity created during the last 250 years, which are known to have generated abrupt structural changes in the Earth's climate, due to unprecedented high levels of CO2 and Temp, and low levels of Ice volume. On the other hand, the advantage of using low-frequency data is that they allow us to obtain long-run forecasts on what would have occurred if humanity had not burned fossil fuels since the start of the Industrial Revolution. These long-run forecasts can serve as benchmarks for the long-run evaluation of the impact of humanity on climate variables. Without the impact of humanity on climate, we predict the existence of turning points in the evolution of the three climate variables for the next 5,000 years: an upward trend in global ice volume, and downward trends in atmospheric CO2 level and Antarctic land surface temperature. Blazsek acknowledges funding from Universidad Francisco Marroquín, Guatemala. Escribano acknowledges funding from Ministerio de Economía, Industria y Competitividad, Spain (ECO2016-00105-001 and MDM 2014-0431), Comunidad de Madrid, Spain (MadEco-CM S2015/HUM-3444), and ... Article in Journal/Newspaper Antarc* Antarctic Universidad Carlos III de Madrid: e-Archivo Antarctic Energy Economics 118 106522 |
institution |
Open Polar |
collection |
Universidad Carlos III de Madrid: e-Archivo |
op_collection_id |
ftunivcarlosmadr |
language |
English |
topic |
Antarctic land surface temperature Atmospheric CO2 level Climate change Dynamic conditional score Generalized autoregressive score Global ice volume Score-driven ice-age models C32 C38 C51 C52 C53 Q54 Economía |
spellingShingle |
Antarctic land surface temperature Atmospheric CO2 level Climate change Dynamic conditional score Generalized autoregressive score Global ice volume Score-driven ice-age models C32 C38 C51 C52 C53 Q54 Economía Escribano, Álvaro Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts |
topic_facet |
Antarctic land surface temperature Atmospheric CO2 level Climate change Dynamic conditional score Generalized autoregressive score Global ice volume Score-driven ice-age models C32 C38 C51 C52 C53 Q54 Economía |
description |
Climate variables are known to be subject to abrupt changes when some threshold levels are surpassed. We use data for the last 798,000 years on global ice volume (Ice), atmospheric carbon dioxide level (CO2), and Antarctic land surface temperature (Temp) to model and measure those long-run nonlinear climate effects. The climate variables have very long and asymmetric cycles, created by periods of upward trends, followed by periods of downward trends driven by exogenous orbital variables. The exogenous orbital variables considered by the Milankovitch cycles are eccentricity of Earth's orbit, obliquity, and precession of the equinox. We show that our new score-driven threshold ice-age models improve the statistical inference and forecasting performance of competing ice-age models from the literature. The drawback of using our 1000-year frequency observations, is that we cannot measure the nonlinear climate effects of humanity created during the last 250 years, which are known to have generated abrupt structural changes in the Earth's climate, due to unprecedented high levels of CO2 and Temp, and low levels of Ice volume. On the other hand, the advantage of using low-frequency data is that they allow us to obtain long-run forecasts on what would have occurred if humanity had not burned fossil fuels since the start of the Industrial Revolution. These long-run forecasts can serve as benchmarks for the long-run evaluation of the impact of humanity on climate variables. Without the impact of humanity on climate, we predict the existence of turning points in the evolution of the three climate variables for the next 5,000 years: an upward trend in global ice volume, and downward trends in atmospheric CO2 level and Antarctic land surface temperature. Blazsek acknowledges funding from Universidad Francisco Marroquín, Guatemala. Escribano acknowledges funding from Ministerio de Economía, Industria y Competitividad, Spain (ECO2016-00105-001 and MDM 2014-0431), Comunidad de Madrid, Spain (MadEco-CM S2015/HUM-3444), and ... |
author2 |
Ministerio de Economía y Competitividad (España) Agencia Estatal de Investigación (España) Comunidad de Madrid |
format |
Article in Journal/Newspaper |
author |
Escribano, Álvaro |
author_facet |
Escribano, Álvaro |
author_sort |
Escribano, Álvaro |
title |
Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts |
title_short |
Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts |
title_full |
Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts |
title_fullStr |
Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts |
title_full_unstemmed |
Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts |
title_sort |
score-driven threshold ice-age models: benchmark models for long-run climate forecasts |
publisher |
Elsevier |
publishDate |
2023 |
url |
http://hdl.handle.net/10016/38532 https://doi.org/10.1016/j.eneco.2023.106522 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
Gobierno de España. RTI2018-101371-B-I00 Gobierno de España. ECO2016-00105-001 Gobierno de España. MDM 2014-0431 Comunidad de Madrid. S2015/HUM-3444 Blazsek, S., & Escribano, A. (2023). Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts. Energy Economics, Vol. 118, p. 106522. 0140-9883 http://hdl.handle.net/10016/38532 https://doi.org/10.1016/j.eneco.2023.106522 Energy Economics 118 AR/0000033069 |
op_rights |
© The authors Atribución 3.0 España http://creativecommons.org/licenses/by/3.0/es/ open access |
op_doi |
https://doi.org/10.1016/j.eneco.2023.106522 |
container_title |
Energy Economics |
container_volume |
118 |
container_start_page |
106522 |
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1788703681615495168 |