Detectable global temperature responses to wildfires and volcanic eruptions

Large volcanic eruptions and intense wildfires perturb Earth's atmospheric temperature. Understanding the climate response to such natural forcings is essential for obtaining reliable estimates of its response to anthropogenic greenhouse gas emissions. While the climate impacts of volcanic sulfate aerosols are well documented, other natural forcings-including wildfire smoke reaching the stratosphere and water vapor injections from a submarine eruption-pose new challenges for detecting and attributing their atmospheric temperature impacts. Here, we demonstrate robust detection of statistically significant temperature anomalies in the troposphere and stratosphere using multidecadal satellite observations and internal variability estimates from a climate model ensemble and from observations. We analyze three landmark events: the 1991 Pinatubo eruption, the 2019-2020 Australian wildfires, and the 2022 Hunga Tonga eruption. Each leaves a fingerprint with distinct altitudinal, geographical, and temporal structure. The global-mean stratospheric signal from Australian wildfires is detectable even in time averages extending beyond 10 mo, despite injecting only ~5% of Pinatubo's aerosol mass. For Hunga Tonga, we detect significant and prolonged stratospheric cooling, but no robust tropospheric signal in the first 2 y. These findings show that both sulfate and nonsulfate stratospheric perturbations produce distinct, statistically identifiable global temperature signals. Accounting for such forcings in climate model simulations is therefore essential for improving comparisons of simulated and observed variability.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2026-02-23
DOI
https://doi.org/10.1073/pnas.2525500123
Primary Topic
Climate variability and models
Type
article
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article

Detectable global temperature responses to wildfires and volcanic eruptions

David W. J. Thompson, Yaowei Li, B. D. Santer, Susan Solomon et al.
Proceedings of the National Academy of Sciences
Climate variability and models
article

Detectable global temperature responses to wildfires and volcanic eruptions

David W. J. Thompson, Yaowei Li, B. D. Santer, Susan Solomon, Qiang Fu
article en

Abstract

Large volcanic eruptions and intense wildfires perturb Earth's atmospheric temperature. Understanding the climate response to such natural forcings is essential for obtaining reliable estimates of its response to anthropogenic greenhouse gas emissions. While the climate impacts of volcanic sulfate aerosols are well documented, other natural forcings-including wildfire smoke reaching the stratosphere and water vapor injections from a submarine eruption-pose new challenges for detecting and attributing their atmospheric temperature impacts. Here, we demonstrate robust detection of statistically significant temperature anomalies in the troposphere and stratosphere using multidecadal satellite observations and internal variability estimates from a climate model ensemble and from observations. We analyze three landmark events: the 1991 Pinatubo eruption, the 2019-2020 Australian wildfires, and the 2022 Hunga Tonga eruption. Each leaves a fingerprint with distinct altitudinal, geographical, and temporal structure. The global-mean stratospheric signal from Australian wildfires is detectable even in time averages extending beyond 10 mo, despite injecting only ~5% of Pinatubo's aerosol mass. For Hunga Tonga, we detect significant and prolonged stratospheric cooling, but no robust tropospheric signal in the first 2 y. These findings show that both sulfate and nonsulfate stratospheric perturbations produce distinct, statistically identifiable global temperature signals. Accounting for such forcings in climate model simulations is therefore essential for improving comparisons of simulated and observed variability.

Proceedings of the National Academy of SciencesVol. 123(10)
University of East Anglia (GB), University of Washington (US), Massachusetts Institute of Technology (US), Colorado State University (US)
Climate action
Openalex Percentile: Top 61%
Climate variability and models
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