Skip to main content
U.S. flag

An official website of the United States government

Implications of Inter-Dataset Differences in Sea Surface Warming for Top-of-Atmosphere Radiation and Feedbacks

Presentation Date
Tuesday, December 12, 2023 at 8:30am - Tuesday, December 12, 2023 at 8:33am
MC - eLightning Theater I, Hall D - South



Changes in both the global mean and spatial pattern of sea surface temperature (SST) have a strong influence on Earth’s energy budget through several radiative feedback mechanisms. It is often assumed that SST observations covering the “well-observed” era (since the early 1980s) should show good agreement with each other. Here we demonstrate that there are marked differences among datasets in both the global mean and spatial pattern of SST change per unit of global warming, even during the CERESMIP target period of 2001-2021. Using Green’s functions that quantify the global radiative impact of SST anomalies, we further show that these inter-dataset differences imply substantial differences in radiative feedbacks that are comparable to the strength of the nominal pattern effect between past and predicted future warming. Surprisingly, much of the inter-dataset differences in implied feedbacks are tied to differences in their mean warming rate, with variations in their patterns of warming playing a secondary role. Hence, observational uncertainty – even during the recent “well-observed” period – must be carefully explored in studies of the pattern effect or in establishing how well models match observations during the CERES record.

This work was performed under the auspices of the United States Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.IM Release #LLNL-ABS-852570

Funding Program Area(s)