Abstract

Abstract. To simulate the impacts of volcanic eruptions on the stratosphere, chemistry–climate models that do not include an online aerosol module require temporally and spatially resolved aerosol size parameters for heterogeneous chemistry and aerosol radiative properties as a function of wavelength. For phase 1 of the Chemistry-Climate Model Initiative (CCMI-1) and, later, for phase 6 of the Coupled Model Intercomparison Project (CMIP6) two such stratospheric aerosol data sets were compiled, whose functional capability and representativeness are compared here. For CCMI-1, the SAGE-4λ data set was compiled, which hinges on the measurements at four wavelengths of the SAGE (Stratospheric Aerosol and Gas Experiment) II satellite instrument and uses ground-based lidar measurements for gap-filling immediately after the 1991 Mt Pinatubo eruption, when the stratosphere was too optically opaque for SAGE II. For CMIP6, the new SAGE-3λ data set was compiled, which excludes the least reliable SAGE II wavelength and uses measurements from CLAES (Cryogenic Limb Array Etalon Spectrometer) on UARS, the Upper Atmosphere Research Satellite, for gap-filling following the Mt Pinatubo eruption instead of ground-based lidars. Here, we performed SOCOLv3 (Solar Climate Ozone Links version 3) chemistry–climate model simulations of the recent past (1986–2005) to investigate the impact of the Mt Pinatubo eruption in 1991 on stratospheric temperature and ozone and how this response differs depending on which aerosol data set is applied. The use of SAGE-4λ results in heating and ozone loss being overestimated in the tropical lower stratosphere compared to observations in the post-eruption period by approximately 3 K and 0.2 ppmv, respectively. However, less heating occurs in the model simulations based on SAGE-3λ, because the improved gap-filling procedures after the eruption lead to less aerosol loading in the tropical lower stratosphere. As a result, simulated tropical temperature anomalies in the model simulations based on SAGE-3λ for CMIP6 are in excellent agreement with MERRA and ERA-Interim reanalyses in the post-eruption period. Less heating in the simulations with SAGE-3λ means that the rate of tropical upwelling does not strengthen as much as it does in the simulations with SAGE-4λ, which limits dynamical uplift of ozone and therefore provides more time for ozone to accumulate in tropical mid-stratospheric air. Ozone loss following the Mt Pinatubo eruption is overestimated by up to 0.1 ppmv in the model simulations based on SAGE-3λ, which is a better agreement with observations than in the simulations based on SAGE-4λ. Overall, the CMIP6 stratospheric aerosol data set, SAGE-3λ, allows SOCOLv3 to more accurately simulate the post-Pinatubo eruption period.

Highlights

  • The stratospheric aerosol layer is a key component of the climate system as it directly affects how incoming solar radiation is scattered in Earth’s atmosphere and affects the solar energy input to the climate system

  • The results indicate that stratospheric temperatures and ozone changes induced by the Mt Pinatubo eruption in simulations based on SAGE-3λ for CMIP6 are in better agreement with observations than the simulations based on SAGE-4λ for CCMI-1, which in turn is better than previous aerosol data sets based on SAGE retrieval versions 5.9 or earlier (Arfeuille et al, 2013)

  • Lidar data were used for gap-filling in the SAGE-4λ data set, while CLAES data were predominantly used for the SAGE-3λ data set

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Summary

Introduction

The stratospheric aerosol layer is a key component of the climate system as it directly affects how incoming solar radiation is scattered in Earth’s atmosphere and affects the solar energy input to the climate system. CCMs participating in CCMVal-2, the predecessor activity to phase 1 of the Chemistry-Climate Model Initiative (CCMI-1), simulated global-mean temperature anomalies between −1 and +9 K at 50 hPa in the post-Pinatubo eruption period, and globalmean ozone anomalies between −2 and −22 % (Mancini et al, 2010). While this is partly due to how the models handle aerosol radiative and chemical processes, the process of compiling the best historic stratospheric aerosol data set with which to drive the models is incomplete. SAM, SAGE I, SAGE II, SAM, CALIPSO, OSIRIS; sun-photometer data; AER stratospheric aerosol model; mass, volume density, SAD, reff corrected for very small particles below 20 km by OPC measurements

Stratospheric aerosol data sets
SAGE-4λ
SAGE-3λ
SAGE-3λ and SAGE-4λ algorithms
CCM and simulations
Difference in aerosol mass in the CCMI and CMIP6 aerosol data sets
Comparison of simulations using the CCMI and CMIP6 aerosol data sets
Conclusions
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