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Aerosol formation in clouds: the effects of aerosol on cloud microphysics implications for global warming

Objective

To investigate aerosol formation in clouds, the effects of
aerosols on cloud microphysics, and the implications for the
representation of cloud processes in climate models.


The Great Dun Fell cap cloud will be used as a Natural Flow
through reactor in a novel experiment to increase our
understanding of the interaction between aerosol, clouds and
cloud chemistry. The flow through reactor results in a much
better characterised system than has been possible in the past.

The specific research items are:

Investigation of the relationship between the gas phase
precursors and the development of hygroscopic aerosol particles
due to chemical processes in and near cloud.

Study the effects of passing through a cloud system on the
atmospheric aerosol size distribution and optical properties.

Determination and quantification of the factors controlling the
scavenging of particles in the cloud and investigation the
droplet growth process and how it depends on the original
particle size and composition.

Exploration of the results from the above items
for atmospheric modelling of climate change with particular
emphasis on regional scale aerosol climate forcing caused by
European emissions of sulphur and nitrogen species.

Investigation of factors influencing the lifetime of ammonia in
the atmosphere as the air is involved in cloud formation.

The experiment will bring together detailed measurements of cloud
physics and atmospheric chemistry using state of the art
equipment with aerosol measurements using novel techniques and
very new instrumentation. The results of the field experiment
will be directly incorporated into a recently developed regional
model to assess the impact of the processes discovered.

Call for proposal

Data not available

Coordinator

University of Manchester Institute of Science and Technology
EU contribution
No data
Address
Sackville Street
M60 1QD Manchester
United Kingdom

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Total cost
No data

Participants (5)