GASSP uses the Met Office global climate model HadGEM-UKCA. The model includes an advanced treatment of aerosol microphysical processes.
The need to improve estimates of aerosol forcing has led to the development of sophisticated “second generation” aerosol microphysics models in many of the world’s climate models. Models like the one to be used in GASSP are now capable of simulating the principal aerosol quantity that drives the aerosol indirect effect – cloud condensation nuclei (CCN) concentrations. Cloud drop concentrations and subsequent cloud radiative and dynamical changes are determined fundamentally by CCN. However, IPCC models have so far not included this level of sophistication in their treatment of aerosols, and are therefore not directly constrained by observations of this key aerosol quantity.
The aerosol model is described in a paper:
- Mann GW; Carslaw KS; Spracklen DV; Ridley DA; Manktelow PT; Chipperfield MP; Pickering SJ; Johnson CE (2010) Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model, GEOSCI MODEL DEV, 3, pp.519-551. doi: 10.5194/gmd-3-519-2010.
- Further information about the model, and the science it has been used for, is available from the Leeds Aerosol Model Research Group, the Oxford Climate Processes group, or the UKCA website.
Developments in model sophistication have been matched or even exceeded by a dramatic increase in the extent and sophistication of aerosol microphysics measurements. These data include particle size distributions, number concentrations and size-resolved composition, all of which influence CCN. But these datasets have only been used in an ad hoc way to evaluate some aspects of the models, and many datasets have barely been used at all. Global CCN and related microphysics measurements provide a rich but under-exploited dataset for reducing uncertainty in the indirect effect.
GASSP brings together an advanced global aerosol model with these rich datasets to test our understanding of aerosol, and thereby reduce the uncertainty in forcing.