Responses to Lower‐Tropospheric Stability Dominate Intermodel Differences in the Historical Pattern Effect

Abstract The sea surface temperature (SST) pattern modulates the Earth's radiative feedbacks at decadal timescales. However, decadal feedback variations over the historical period depend on the choice of climate model, even when forced with the same SST data set. We investigate these differences through analyzing amip‐piForcing output, focusing on low cloud feedback. Time‐variation in low cloud feedback results primarily from the SST pattern, mediated by changes in near‐global lower tropospheric stability (LTS). We investigate the meteorological factors contributing to low cloud feedback variation through the cloud controlling factor analysis method, diagnosing cloud radiative sensitivities from 16 CMIP5 and CMIP6 models, and an observational constraint from MODIS. We find the radiative sensitivity of models to LTS in the stratocumulus regions dominates the magnitude of cloud feedback time variation due to the pattern effect. Additionally, models underestimate low cloud radiative sensitivity to changes in LTS and SST and thus the time‐variation in feedback.

Authors

Institutions

Publication Details

Journal
Geophysical Research Letters
Published
2025-08-28
DOI
https://doi.org/10.1029/2025gl117015
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Responses to Lower‐Tropospheric Stability Dominate Intermodel Differences in the Historical Pattern Effect

Koh Kawaguchi, Paulo Ceppi
1 citations
Geophysical Research Letters
Climate variability and models
1.11
article

Responses to Lower‐Tropospheric Stability Dominate Intermodel Differences in the Historical Pattern Effect

Koh Kawaguchi, Paulo Ceppi
article en
1 citations

Abstract

Abstract The sea surface temperature (SST) pattern modulates the Earth's radiative feedbacks at decadal timescales. However, decadal feedback variations over the historical period depend on the choice of climate model, even when forced with the same SST data set. We investigate these differences through analyzing amip‐piForcing output, focusing on low cloud feedback. Time‐variation in low cloud feedback results primarily from the SST pattern, mediated by changes in near‐global lower tropospheric stability (LTS). We investigate the meteorological factors contributing to low cloud feedback variation through the cloud controlling factor analysis method, diagnosing cloud radiative sensitivities from 16 CMIP5 and CMIP6 models, and an observational constraint from MODIS. We find the radiative sensitivity of models to LTS in the stratocumulus regions dominates the magnitude of cloud feedback time variation due to the pattern effect. Additionally, models underestimate low cloud radiative sensitivity to changes in LTS and SST and thus the time‐variation in feedback.

Geophysical Research LettersVol. 52(17)
Imperial College London (GB)
Government of the United Kingdom, UK Research and Innovation, HORIZON EUROPE Framework Programme, Natural Environment Research Council, HORIZON EUROPE European Research Council
Openalex Percentile: Top 20%
Climate variability and models
1.11
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.

Responses to Lower‐Tropospheric Stability Dominate Intermodel Differences in the Historical Pattern Effect — Koh Kawaguchi, Paulo Ceppi · Geophysical Research Letters (2025) | TGRS Research Map | TGRS