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The Global Aerosol Synthesis and Science Project (GASSP): measurements and modelling to reduce uncertainty

Abstract:

Novel methodologies to quantify model uncertainty are combined with an extensive new database of in-situ aerosol microphysical and chemical measurements to reduce uncertainty in aerosol effects on climate.

The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in-situ measurements of the particle size distribution, number concentration and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, an extensive global dataset of aerosol in-situ microphysical and chemical measurements, and new ways to assess the uncertainty associated with comparing sparse point measurements with low resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modellers and non-specialist users. Available measurements are extensive, but they biased to polluted regions of the northern hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model-data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1175/BAMS-D-15-00317.1

Authors


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Institution:
University of Oxford
Oxford college:
Oriel College
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Atmos Ocean & Planet Physics
Role:
Author



Publisher:
American Meteorological Society
Journal:
Bulletin of the American Meteorological Society More from this journal
Volume:
September
Issue:
2017
Pages:
1857-1878
Publication date:
2017-02-27
Acceptance date:
2017-02-14
DOI:
EISSN:
1520-0477
ISSN:
0003-0007


Pubs id:
pubs:691207
UUID:
uuid:6959b5eb-df2b-41c8-a235-b64128d2c150
Local pid:
pubs:691207
Source identifiers:
691207
Deposit date:
2017-04-26

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