An EOF-Based Emulator of Means and Covariances of Monthly Climate Fields
Name
esd-17-235-2026.pdf
Description
Published version
Size
12.67 MB
Format
Adobe PDF
Checksum (MD5)
39102c6846e70f2997df2dfcbb085f17
Author(s)
Geogdzhayev, Gosha
Souza, Andre N
Flierl, Glenn R
Ferrari, Raffaele
Date Issued
March 5, 2026
Journal
Earth System Dynamics
Publisher
Copernicus GmbH
Citation
Geogdzhayev, G., Souza, A. N., Flierl, G. R., and Ferrari, R.: An EOF-Based Emulator of Means and Covariances of Monthly Climate Fields, Earth Syst. Dynam., 17, 235–263.
Version
Final published version
Abstract
Fast emulators of comprehensive climate models are often used to explore the impact of anthropogenic emissions on future climate. A new approach to emulators is introduced that generates means and covariances of monthly averaged climate variables as a function of global mean surface temperature. The emulator is trained with output from a state-of-the-art climate model and serves as a good first-order representation for the evolution of spatially resolved climate variables and their variability. To train the emulator, data is first projected into a reduced-dimensional space; the emulator then learns the dependence of climate variables on global mean surface temperature in the projected space. To recover climate variables in physical space, an inverse transformation is applied. The resulting emulator can cheaply generate means and variances of climate fields averaged over arbitrarily defined regions and in previously unseen warming scenarios. For illustrative purposes, the emulator is applied to predict changes in the mean and variability of monthly values of both surface temperature and relative humidity as a function of global mean surface temperature changes. However, the approach can be applied to any other variable of interest on yearly, monthly or daily timescales.
MIT Department
Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.5194/esd-17-235-2026
