THE FORCING OF A PHOTOCHEMICAL AIR QUALITY MODEL WITH ATMOSPHERIC FIELDS SIMULATED BY A REGIONAL CLIMATE MODEL DATA

Abstract

Within the context of climate change over southern Africa, little is understood about the potential local response of air quality to changes in the larger scale environment. Under future climate forcing, there may be significant changes in the thermodynamic structure of the atmosphere over southern Africa, and in the circulation dynamics of the region. For example, there is evidence that more intense surface inversion layers may occur over the central interior of South Africa in response to the enhanced greenhouse effect (e.g. Engelbrecht et al, 2009). Such changes are likely to influence the future transport and chemistry of air pollutants over the region. The complexity in which climate change may affect regional air quality is evident. Sophisticated numerical models are required to describe such complexity, and need to take into account all meteorological and emission changes, as well as apply relevant dispersion and chemistry to solving variation in pollutant concentration. The capacity to force atmospheric chemistry models with the output of regional climate models exists within CSIR NRE in the form of the photochemical air quality model CAMx forced by the MM5 regional climate model. This is useful for retrospective studies in air quality however the aspect of future climate forcing on air pollution is not addressed. This paper describes the development of new modelling capacity suitable for the simulation of photochemistry over southern Africa under both current and future anthropogenic forcing. The model CAMx was nested within the output of the regional climate model CCAM, which is applied at the NRE to obtain detailed projections of regional climate change. This new configuration may potentially be applied for photochemistry modelling at all time-scales, but the emphasis is on the very long integrations suitable to describe photochemistry characteristics over southern Africa at the climate-change time scale. Here, the new CCAM-CAMx configuration was tested by simulating a selected previously modelled ozone episode, serving to demonstrate the capability of incorporating CCAM data into CAMx as well as investigating how well the new system performs. Results show the importance of preparing appropriate cloud and precipitation data from the CCAM output, as well as a need for finer vertical resolutions in CCAM. In general, CCAM may be appropriately used to force CAMx, illustrating the potential of the new system to simulate photochemistry and air quality over southern Africa under conditions of current and future anthropogenic forcing.