Community Research and Development Information Service - CORDIS

Improving global climate models

Numerical simulation is a powerful analytical tool that has recently been made more accessible through the advent of microcomputer technology. Scientists at the Italian Joint Research Centre have applied numerical simulation methods to advance the state-of-the-art in global climate modelling.
Improving global climate models
In the 1920s, Lewis Fry Richardson imagined forecasting the weather with a 'forecast-factory', a room full of mathematicians, each performing multiple calculations corresponding to their particular region of the globe. Richardson's vision was never realised since the mathematicians could not perform the calculations fast enough to produce a true forecast. However, since that time computers have replaced the mathematicians, and it is now possible to forecast the weather several days in advance.

But numerical modelling is used for more than just forecasting tomorrow's weather. It is also applied to the global climate, or long-term weather patterns. Recent attention has been focused on man's possible impact on the Earth's climate, chiefly the effect of greenhouse gas emissions on warming the atmosphere. Scientists have recently discovered that global warming may be offset by the cooling effects of airborne aerosols, which reflect incoming solar radiation back into space. Some aerosols are man-made, but others occur naturally, such as dimethylsulphide or DMS.

DMS is produced by algae living in the world's oceans. Once released into the atmosphere, the DMS is transformed into sulphate aerosol through a number of complex chemical reactions. The sulphate aerosol contributes to the global cooling effect. The magnitude of this effect is not yet understood since DMS chemistry has not previously been included in global climate models. However, researchers at the Joint Research Centre (JRC) have recently solved this problem.

The model developed by the JRC addresses gas and aqueous phase DMS chemistry, both of which are necessary to properly simulate DMS in the atmosphere. Another important aspect of the model is the Monte Carlo driver, which allows for global sensitivity analysis. This is a key feature when running the model for different potential future scenarios.

The model was verified against real-world measurements of DMS and performed well in simulating ratios of DMS and its by-products following its release into the atmosphere. The results will be useful to the global climate modelling community as it seeks to resolve the interplay between global warming and cooling to help guide policy making.

The model developers are looking to extend their research to further refine the understanding and modelling of the impact of DMS on the global climate. For more details about the model see e.g. Campolongo, Saltelli, Jensen, Wilson and Hjorth (1999), Journal of Atmospheric Chemistry, vol.32, pp.327-356, and DOMAC final SCA report (2000), EUR 19567.
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