GMD Geoscientific Model Development GMD 1991-9603 Copernicus GmbH Göttingen, Germany 10.5194/gmd-3-519-2010 Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model Mann G. W. 1 Carslaw K. S. 2 Spracklen D. V. 2 Ridley D. A. 3 Manktelow P. T. 2 5 Chipperfield M. P. 2 Pickering S. J. 2 Johnson C. E. 4 National Centre for Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK School of Earth and Environment, University of Leeds, Leeds, UK Dept. of Atmospheric Science, Colorado State University, Fort Collins, Colorado, USA Met Office Hadley Centre, Exeter, UK now at: Halcrow Group Ltd, Headingley, Leeds, UK 13 10 2010 3 2 519 551 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.geosci-model-dev.net/3/519/2010/gmd-3-519-2010.html The full text article is available as a PDF file from http://www.geosci-model-dev.net/3/519/2010/gmd-3-519-2010.pdf

A new version of the Global Model of Aerosol Processes (GLOMAP) is described, which uses a two-moment pseudo-modal aerosol dynamics approach rather than the original two-moment bin scheme. GLOMAP-mode simulates the multi-component global aerosol, resolving sulfate, sea-salt, dust, black carbon (BC) and particulate organic matter (POM), the latter including primary and biogenic secondary POM. Aerosol processes are simulated in a size-resolved manner including primary emissions, secondary particle formation by binary homogeneous nucleation of sulfuric acid and water, particle growth by coagulation, condensation and cloud-processing and removal by dry deposition, in-cloud and below-cloud scavenging. A series of benchmark observational datasets are assembled against which the skill of the model is assessed in terms of normalised mean bias (<i>b</i>) and correlation coefficient (<i>R</i>). Overall, the model performs well against the datasets in simulating concentrations of aerosol precursor gases, chemically speciated particle mass, condensation nuclei (CN) and cloud condensation nuclei (CCN). Surface sulfate, sea-salt and dust mass concentrations are all captured well, while BC and POM are biased low (but correlate well). Surface CN concentrations compare reasonably well in free troposphere and marine sites, but are underestimated at continental and coastal sites related to underestimation of either primary particle emissions or new particle formation. The model compares well against a compilation of CCN observations covering a range of environments and against vertical profiles of size-resolved particle concentrations over Europe. The simulated global burden, lifetime and wet removal of each of the simulated aerosol components is also examined and each lies close to multi-model medians from the AEROCOM model intercomparison exercise.

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