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 longrun nonlinear...

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Main Authors: Blazsek, Szabolcs, Escribano, Álvaro
Other Authors: Universidad Carlos III de Madrid. Departamento de Economía
Format: Report
Language:English
Published: 2022
Subjects:
C32
C38
C51
C52
C53
Q54
Online Access:http://hdl.handle.net/10016/34757
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spelling ftunivcarlosmadr:oai:e-archivo.uc3m.es:10016/34757 2024-01-21T10:00:57+01:00 Score-driven threshold ice-age models: benchmark models for long-run climate forecasts Blazsek, Szabolcs Escribano, Álvaro Universidad Carlos III de Madrid. Departamento de Economía 2022-05-10 http://hdl.handle.net/10016/34757 eng eng Working paper. Economics 22-05 2340-5031 http://hdl.handle.net/10016/34757 DT/0000001996 Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Climate Change Ice-Ages Global Ice Volume Atmospheric Co2 Level Antarctic Land Surface Temperature Dynamic Conditional Score Models Generalized Autoregressive Score Models C32 C38 C51 C52 C53 Q54 Economía working paper 2022 ftunivcarlosmadr 2023-12-27T00:20:11Z 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 longrun 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 1,000-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. Report Antarc* Antarctic Universidad Carlos III de Madrid: e-Archivo Antarctic
institution Open Polar
collection Universidad Carlos III de Madrid: e-Archivo
op_collection_id ftunivcarlosmadr
language English
topic Climate Change
Ice-Ages
Global Ice Volume
Atmospheric Co2 Level
Antarctic Land Surface Temperature
Dynamic Conditional Score Models
Generalized Autoregressive Score Models
C32
C38
C51
C52
C53
Q54
Economía
spellingShingle Climate Change
Ice-Ages
Global Ice Volume
Atmospheric Co2 Level
Antarctic Land Surface Temperature
Dynamic Conditional Score Models
Generalized Autoregressive Score Models
C32
C38
C51
C52
C53
Q54
Economía
Blazsek, Szabolcs
Escribano, Álvaro
Score-driven threshold ice-age models: benchmark models for long-run climate forecasts
topic_facet Climate Change
Ice-Ages
Global Ice Volume
Atmospheric Co2 Level
Antarctic Land Surface Temperature
Dynamic Conditional Score Models
Generalized Autoregressive Score 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 longrun 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 1,000-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.
author2 Universidad Carlos III de Madrid. Departamento de Economía
format Report
author Blazsek, Szabolcs
Escribano, Álvaro
author_facet Blazsek, Szabolcs
Escribano, Álvaro
author_sort Blazsek, Szabolcs
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
publishDate 2022
url http://hdl.handle.net/10016/34757
geographic Antarctic
geographic_facet Antarctic
genre Antarc*
Antarctic
genre_facet Antarc*
Antarctic
op_relation Working paper. Economics
22-05
2340-5031
http://hdl.handle.net/10016/34757
DT/0000001996
op_rights Atribución-NoComercial-SinDerivadas 3.0 España
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
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