An examination of climate sensitivity for idealised climate change experiments in an intermediate general circulation model

Radiative forcing and climate sensitivity have been widely used as concepts to understand climate change. This work performs climate change experiments with an intermediate general circulation model (IGCM) to examine the robustness of the radiative forcing concept for carbon dioxide and solar constant changes. This IGCM has been specifically developed as a computationally fast model, but one that allows an interaction between physical processes and large-scale dynamics; the model allows many long integrations to be performed relatively quickly. It employs a fast and accurate radiative transfer scheme, as well as simple convection and surface schemes, and a slab ocean, to model the effects of climate change mechanisms on the atmospheric temperatures and dynamics with a reasonable degree of complexity. The climatology of the IGCM run at T-21 resolution with 22 levels is compared to European Centre for Medium Range Weather Forecasting Reanalysis data. The response of the model to changes in carbon dioxide and solar output are examined when these changes are applied globally and when constrained geographically (e.g. over land only). The CO2 experiments have a roughly 17% higher climate sensitivity than the solar experiments. It is also found that a forcing at high latitudes causes a 40% higher climate sensitivity than a forcing only applied at low latitudes. It is found that, despite differences in the model feedbacks, climate sensitivity is roughly constant over a range of distributions of CO2 and solar forcings. Hence, in the IGCM at least, the radiative forcing concept is capable of predicting global surface temperature changes to within 30%, for the perturbations described here. It is concluded that radiative forcing remains a useful tool for assessing the natural and anthropogenic impact of climate change mechanisms on surface temperature.

The lifecycle of the North Atlantic storm track

The North Atlantic eddy-driven jet exhibits latitudinal variability, with evidence of three preferred latitudinal locations: south, middle and north. Here we examine the drivers of this variability and the variability of the associated storm track. We investigate the changes in the storm track characteristics for the three jet locations, and propose a mechanism by which enhanced storm track activity, as measured by upstream heat flux, is responsible for cyclical downstream latitudinal shifts in the jet. This mechanism is based on a nonlinear oscillator relationship between the enhanced meridional temperature gradient (and thus baroclinicity) and the meridional high-frequency (periods of shorter than 10 days) eddy heat flux. Such oscillations in baroclinicity and heat flux induce variability in eddy anisotropy which is associated with the changes in the dominant type of wave breaking and a different latitudinal deflection of the jet. Our results suggest that high heat flux is conducive to a northward deflection of the jet, whereas low heat flux is conducive to a more zonal jet. This jet deflecting effect was found to operate most prominently downstream of the storm track maximum, while the storm track and the jet remain anchored at a fixed latitudinal location at the beginning of the storm track. These cyclical changes in storm track characteristics can be viewed as different stages of the storm track’s spatio-temporal lifecycle.

Optimised frequency grids for infrared radiative transfer simulations in cloudy conditions

This paper shows that radiometer channel radiances for cloudy atmospheric conditions can be simulated with an optimised frequency grid derived under clear-sky conditions. A new clear-sky optimised grid is derived for AVHRR channel 5 ð12 m m, 833 cm �1 Þ. For HIRS channel 11 ð7:33 m m, 1364 cm �1 Þ and AVHRR channel 5, radiative transfer simulations using an optimised frequency grid are compared with simulations using a reference grid, where the optimised grid has roughly 100–1000 times less frequencies than the full grid. The root mean square error between the optimised and the reference simulation is found to be less than 0.3 K for both comparisons, with the magnitude of the bias less than 0.03 K. The simulations have been carried out with the radiative transfer model Atmospheric Radiative Transfer Simulator (ARTS), version 2, using a backward Monte Carlo module for the treatment of clouds. With this module, the optimised simulations are more than 10 times faster than the reference simulations. Although the number of photons is the same, the smaller number of frequencies reduces the overhead for preparing the optical properties for each frequency. With deterministic scattering solvers, the relative decrease in runtime would be even more. The results allow for new radiative transfer applications, such as the development of new retrievals, because it becomes much quicker to carry out a large number of simulations. The conclusions are applicable to any downlooking infrared radiometer.