Abstract

Abstract. We present top-of-atmosphere and surface radiative kernels based on the atmospheric component (GA7.1) of the HadGEM3 general circulation model developed by the UK Met Office. We show that the utility of radiative kernels for forcing adjustments in idealised CO2 perturbation experiments is greatest where there is sufficiently high resolution in the stratosphere in both the target climate model and the radiative kernel. This is because stratospheric cooling to a CO2 perturbation continues to increase with height, and low-resolution or low-top kernels or climate model output are unable to fully resolve the full stratospheric temperature adjustment. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), standard atmospheric model data are available up to 1 hPa on 19 pressure levels, which is a substantial advantage compared to CMIP5. We show in the IPSL-CM6A-LR model where a full set of climate diagnostics are available that the HadGEM3-GA7.1 kernel exhibits linear behaviour and the residual error term is small, as well as from a survey of kernels available in the literature that in general low-top radiative kernels underestimate the stratospheric temperature response. The HadGEM3-GA7.1 radiative kernels are available at https://doi.org/10.5281/zenodo.3594673 (Smith, 2019).

Highlights

  • Radiative kernels describe how a small change in an atmospheric state variable affects the Earth’s energy balance (Soden et al, 2008; Shell et al, 2008)

  • The first assumes that we have knowledge of the cloud adjustment term Ac, and knowledge of the instantaneous radiative forcing (IRF) (Fi) from a double call in the online model. This is rare in practice, as double calls and International Satellite Cloud Climatology Project (ISCCP) cloud diagnostics are not routinely archived on the Earth System Grid Federation (ESGF), the main distributed data source for CMIP6 output

  • This paper serves two purposes – it introduces the radiative kernel based on the high-top HadGEM3-GA7.1 general circulation model, and it compares estimates of the stratospheric temperature adjustment obtained with a variety of different radiative kernels for quadrupled CO2 experiments

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Summary

Introduction

Radiative kernels describe how a small change in an atmospheric state variable affects the Earth’s energy balance (Soden et al, 2008; Shell et al, 2008). For determining adjustments to a radiative forcing AX, the kernel KX is multiplied by the change in atmospheric state variable X between two integrations of a climate model such that. Cloud adjustments and feedbacks cannot be determined directly using atmospheric state kernels They may be diagnosed using the cloud kernel based on International Satellite Cloud Climatology Project (ISCCP) simulator diagnostics (Zelinka et al, 2012) or from the residual of all-sky and clear-sky radiative kernels (Soden et al, 2008; Shell et al, 2008). With longitude compared to longer time steps, while keeping computational demands to a minimum These model outputs were transplanted into an offline version of the SOCRATES radiative transfer code (version 17.03; Manners et al, 2015; Edwards and Slingo, 1996) and top-of-atmosphere and surface radiative fluxes calculated for each 2 h time step in both the shortwave and longwave spectra, for all sky and clear sky. In the 19-level format they can be used with standard “Amon” model output from any CMIP6 model, which is one of the key advantages of radiative kernels

Top-of-atmosphere kernels
Surface kernels
Comparison to other kernels for stratospheric temperature
Findings
Conclusions
Full Text
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