Year: 2025
Type: article
Abstract: The spatial pattern of sea surface temperature (SST) affects the global radiative budget through the “pattern effect.” While previous studies highlighted the role of El Niño–Southern Oscillation (ENSO) in unforced pattern effect, a systematic assessment of the dominant modes of SST variability for the top of atmosphere energy budget has been lacking. Using Partial Least Squares Regression, we identify Eastern Pacific and Modoki ENSO as the two leading modes most relevant to the pattern effect at interannual timescales. These ENSO variants exhibit distinct radiative signatures due to subtle shifts in the location of SST anomalies relative to the climatological warm pool. Furthermore, analysis of individual ENSO events indicates that each event has a unique radiative signature depending on its evolving spatial structure. These findings highlight the importance of accounting for ENSO diversity to accurately understand how modes of SST variability influence the global energy budget.
Source: Geophysical Research Letters
DOI: 10.1029/2025gl116952
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $3,190
Awards: Machine learning approaches to constrain and understand the role of clouds in climate change (ML4CLOUDS), Bergen research and training program for future AI leaders across the disciplines, CIRCULATES: A comprehensive investigation of clouds, circulation and constraints on climate sensitivity, G434337789, G8612102656
OpenAlex ID: W4415302850