Does Climate Sensitivity Differ Across Regions? A Varying–Coefficient Approach

Global mean surface temperature has been increasing in response to growing greenhouse gas concentrations (IPCC 2021). While Earth is getting warmer overall, regions that have different local geographical features experience unequal increases in temperature. In this article, we develop a varying-coefficient dynamic panel data model and use it to measure local climate sensitivity, defined as the increase in temperature in a given location following a doubling of CO<sub>2</sub> concentration. The inference method proposed in this article can accommodate heterogeneous co-integrating relationships between global and local variables, and it allows the co-moving climate time series to possess both stochastic and deterministic trending components. Using observational data of mean surface temperatures, solar radiation, and carbon dioxide concentrations between 1959 and 2017, our model provides heterogeneous estimates for climate sensitivity that range between increases of 2.5 °C and 5 °C over land, depending on the latitude. Our estimates indicate that high-latitude locations in the Northern Hemisphere are most susceptible to global warming.

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.29038927.v2
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Does Climate Sensitivity Differ Across Regions? A Varying–Coefficient Approach

Figshare
Climate variability and models
article

Does Climate Sensitivity Differ Across Regions? A Varying–Coefficient Approach

article en

Abstract

Global mean surface temperature has been increasing in response to growing greenhouse gas concentrations (IPCC 2021). While Earth is getting warmer overall, regions that have different local geographical features experience unequal increases in temperature. In this article, we develop a varying-coefficient dynamic panel data model and use it to measure local climate sensitivity, defined as the increase in temperature in a given location following a doubling of CO<sub>2</sub> concentration. The inference method proposed in this article can accommodate heterogeneous co-integrating relationships between global and local variables, and it allows the co-moving climate time series to possess both stochastic and deterministic trending components. Using observational data of mean surface temperatures, solar radiation, and carbon dioxide concentrations between 1959 and 2017, our model provides heterogeneous estimates for climate sensitivity that range between increases of 2.5 °C and 5 °C over land, depending on the latitude. Our estimates indicate that high-latitude locations in the Northern Hemisphere are most susceptible to global warming.

Figshare
Climate action
Openalex Percentile: Top 53%
Climate variability and models
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.