DOI: 10.5061/dryad.66t1g1k7v
title: Data from: Quantifying the impact of internal variability on the CESM2 control algorithm for stratospheric aerosol injection dataset

description: Earth system models are a powerful tool to simulate the response to
 hypothetical climate intervention strategies, such as stratospheric
 aerosol injection (SAI). Recent simulations of SAI implement tools from
 control theory, called “controllers”, to determine the quantity of aerosol
 to inject into the stratosphere to reach or maintain specified global
 temperature targets, such as limiting global warming to 1.5C above
 pre-industrial temperatures. This work explores how internal (unforced)
 climate variability can impact controller-determined injection amounts
 using the Assessing Responses and Impacts of Solar climate intervention on
 the Earth system with Stratospheric Aerosol Injection (ARISE-SAI)
 simulations. Since the ARISE-SAI controller determines injection amounts
 by comparing global annual-mean surface temperature to predetermined
 temperature targets, internal variability that impacts temperature can
 impact the total injection amount as well. Using an offline version of the
 ARISE-SAI controller and data from CESM2 earth system model simulations,
 we quantify how internal climate variability and volcanic eruptions impact
 injection amounts. While idealized, this approach allows for the
 investigation of a large variety of climate states without additional
 simulations and can be used to attribute controller sensitivities to
 specific modes of internal variability.
description: # Data from: Quantifying the impact of internal variability on the CESM2
 control algorithm for stratospheric aerosol injection dataset (Connolly et
 al. 2024) TREFHT_Basestates_SSP45: ensemble mean calculated from the
 ARISE-SAI 10 member ensemble and smoothed by fitting a 3rd order
 polynomial to the time series at each grid point.
 TREFHT_anomalies_SSP45.nc: anomalies from the ARISE-SAI control simulation
 which is used when making composites based off the modes of internal
 variability. TREFHT_anomalies_LE.nc: anomalies from the CESM Large
 Ensemble which is used when making composites based off the modes of
 internal variability. ENSO_anomalies_LE.nc: contains the ENSO index
 calculated from the CESM Large Ensemble. ENSO_anomalies_SSP45:contains the
 ENSO index calculated from the ARISE-SAI control simulations.
 NAO_anomalies_LE.nc: contains the NAO index calculated from the CESM Large
 Ensemble. NAO_anomalies_SSP45:contains the NAO index calculated from the
 ARISE-SAI control simulations. SAM_anomalies_LE.nc: contains the SAM index
 calculated from the CESM Large Ensemble. SAM_anomalies_SSP45.nc: contains
 the SAM index calculated from the ARISE-SAI control simulations.
 VOLC_anomalies.nc: contains the average temperature anomalies two years
 after the 1991 Pinatubo eruption. ## Code/Software The CESM2-LE is
 available at the Climate Data Gateway
 [https://climatedata.ibs.re.kr/data/cesm2-lens](https://climatedata.ibs.re.kr/data/cesm2-lens). The ARISE-SAI data is available at [https://www.cesm.ucar.edu/community-projects/arise-sai](https://www.cesm.ucar.edu/community-projects/arise-sai). Code used in this work can be found at [https://github.com/connollyc152/ExploreARISEcontroller](https://github.com/connollyc152/ExploreARISEcontroller)