Natural methane emissions feedbacks in MAGICC v. 7.6

Literature estimates of natural methane emissions, particularly from wetlands, have a wide range of uncertainty. Meanwhile, few Earth System Models (ESMs) explicitly model wetlands as a potential source of methane. As a result, Simple Climate Models that aim to emulate the behaviour of ESMs have little to constrain their present and future contributions. MAGICC, as of version 7.5.3, fixed natural methane concentrations as constant after the historical period. Two studies that model wetland methane emissions over the 21st century both find a relationship between those emissions and global temperature, though disagree on the extent of this temperature sensitivity. An updated version of MAGICC has been created that uses this evidence to include a linearised representation of the relationship between wetland methane emissions and global temperature. The temperature-sensitivity parameter in this relationship has been parametrised in a way such that its distribution encompasses the uncertainty in both modelling literature and carbon budget studies, reflecting the currently high degree of uncertainty in wetland emissions. Our results show how incorporating a temperature feedback in methane emissions leads to both higher temperature projections for all scenarios used here, and a widening of the uncertainty in global temperature response.

Authors

Institutions

Publication Details

Journal
Geoscientific model development
Published
2026-09-24
DOI
https://doi.org/10.5194/gmd-19-9063-2026
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Natural methane emissions feedbacks in MAGICC v. 7.6

Joeri Rogelj, Zebedee Nicholls, Gang Tang, Thomas Kleinen et al.
Geoscientific model development
Atmospheric and Environmental Gas Dynamics
article

Natural methane emissions feedbacks in MAGICC v. 7.6

Joeri Rogelj, Zebedee Nicholls, Gang Tang, Thomas Kleinen, Trevor Sloughter, Zhen Zhang
article en

Abstract

Literature estimates of natural methane emissions, particularly from wetlands, have a wide range of uncertainty. Meanwhile, few Earth System Models (ESMs) explicitly model wetlands as a potential source of methane. As a result, Simple Climate Models that aim to emulate the behaviour of ESMs have little to constrain their present and future contributions. MAGICC, as of version 7.5.3, fixed natural methane concentrations as constant after the historical period. Two studies that model wetland methane emissions over the 21st century both find a relationship between those emissions and global temperature, though disagree on the extent of this temperature sensitivity. An updated version of MAGICC has been created that uses this evidence to include a linearised representation of the relationship between wetland methane emissions and global temperature. The temperature-sensitivity parameter in this relationship has been parametrised in a way such that its distribution encompasses the uncertainty in both modelling literature and carbon budget studies, reflecting the currently high degree of uncertainty in wetland emissions. Our results show how incorporating a temperature feedback in methane emissions leads to both higher temperature projections for all scenarios used here, and a widening of the uncertainty in global temperature response.

Geoscientific model developmentVol. 19(18)
International Institute for Applied Systems Analysis (AT), The University of Melbourne (AU), Chinese Academy of Sciences (CN), University of Exeter (GB), NIHR Imperial Biomedical Research Centre (GB), Institute of Tibetan Plateau Research (CN), Max Planck Institute for Biogeochemistry (DE), Max Planck Institute for Meteorology (DE), Imperial College London (GB)
Climate action
Openalex Percentile: Top 14%
Atmospheric and Environmental Gas Dynamics
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.