Can Top-of-Atmosphere Radiation Measurements Constrain Climate Predictions? Part I: Tuning

Abstract

Perturbed physics configurations of the HadAM3 atmospheric model driven with observed sea surface temperatures (SST) and sea ice were tuned to outgoing radiation observations using a Gauss-Newton line-search optimisation algorithm to adjust the model parameters. Four key parameters, that previous research found affected climate sensitivity, were adjusted to several different target values including two sets of observations. The observations used were the global average Reflected Shortwave Radiation (RSR) and Outgoing Longwave Radiation (OLR) from the Clouds and Earth's Radiant Energy System instruments combined with observations of ocean heat content. Using the same method, configurations were also generated that were consistent with the earlier Earth Radiation Budget Experiment results. Many, though not all, tuning experiments were successful with about 2500 configurations being generated and the changes in simulated outgoing radiation largely due to changes in clouds. Clear sky radiation changes were small largely due to a cancellation between changes in upper-tropospheric relative humidity and temperature. Changes in other climate variables are strongly related to changes in OLR and RSR particularly on large scales. There appears to be some equifinality with different parameter configurations producing OLR and RSR values close to observed values. These models have small differences in their climatology with the one group being similar to the standard configuration and the other group drier in the tropics and warmer everywhere.

Automated parameter tuning applied to sea ice in a global climate model

“…We instead employ a classical Gauss-Newton approach. A simple summary of this optimization technique is provided here and readers are referred to Tett et al (2013) and Tett et al (2017) for a fuller description. The aim is to reduce the root mean square error F between a vector of simulated observables and a vector of target observables , with…”

“…Issues of equifinality are explored in Tett et al (2013). We do not examine these here, and instead choose to start from the default model parameter values and investigate the first stationary point that is encountered.…”

“…Recent years have seen the development of methods for automated parameter optimization (Severijns and Hazeleger 2005;Tett et al 2013;Zhang et al 2015). These are motivated by the time-consuming and subjective nature of manual parameter tuning, whereby selected parameters are perturbed in a number of simulations to find a configuration which improves the specified focus of the modeller (Mauritsen et al 2012;Voosen 2016;Hourdin et al 2016).…”

“…Changes to the model must use physically allowed parameter values, account for internal variability and not compromise other climate variables. We implement the Tett et al (2013) method for automated tuning, discussing optimization input in Sect. 2.2 and parameters in Sect.…”

Automated model optimisation using the Cylc workflow engine (Cyclops v1.0)

“…In climate modelling, Severijns and Hazeleger (2005) used the downhill simplex method to optimize the parameter values of the subgrid parameterizations of an atmospheric general circulation model. More recently, Tett et al (2013) applied a Gauss-Newton line search optimization algorithm to climate simulations with the Hadley Centre Atmosphere Model version 3 (HadAM3) forced with observed sea surface temperature and sea ice, optimising an objective function derived from reflected shortwave radiation and outgoing longwave radiation comparisons. The Tett et al (2013) method was subsequently applied to 10 optimize the sea ice component of the global coupled HadCM3 climate model (Roach et al, 2017).…”