Code for "Natural variability can mask forced permafrost response to stratospheric aerosol injection in the ARISE-SAI-1.5 simulations"

by A.L. Morrison, E.A. Barnes, and J.W. Hurrell

Contact: Dr. Ariel Morrison

We assess how natural variability may mask the forced response of permafrost to a hypothetical stratospheric aerosol injection (SAI) scenario. We train two logistic regression models to predict whether maps of active layer depth and permafrost soil temperature came from the SAI or SSP2-4.5 (control) simulations, and find that it may take 10-30 years of SAI to accurately detect its influence on permafrost. This code uses output data from the Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI) 1.5 simulations (Richter et al., 2022) to perform the analysis and make figures for "Natural variability can mask forced permafrost response to stratospheric aerosol injection in the ARISE-SAI-1.5 simulations." The unprocessed ARISE-SAI-1.5 data are here and the unprocessed SSP2-4.5 data are here. The necessary monthly mean variables for running this code are:

• ALT
• ALTMAX
• TSOI

gridareaNH.nc and peatareaGlobal.nc are files for calculating the total area covered by permafrost and the peat area covered by permafrost, respectively.