The DOI matches its Crossref record; 77 of the 77 references it cites were found in a registry or an index.
Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model
Open accessAbstract
Abstract. 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 (b) and correlation coefficient (R). 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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Atmospheric Chemistry and Physics: From Air Pollution to Climate Change
Seinfeld, J. H., Pandis, S. N., & Noone, K. (1998) · Physics Today · doi:10.1063/1.882420 · Cited by 8,731
Changes in Atmospheric Constituents and in Radiative Forcing
Forster, P. M. D. F., Ramaswamy, V., Artaxo, P. E., Berntsen, T. K., Betts, R., Fahey, D. W., Haywood, J., Lean, J. L., Lowe, D. C., Myhre, G., et al. (2007) · elib (German Aerospace Center) · Cited by 4,635
A global model of natural volatile organic compound emissions
Guenther, A., Hewitt, C. N., Erickson, D., Fall, R., Geron, C., Graedel, T., Harley, P., Klinger, L., Lerdau, M., Mckay, W. A., et al. (1995) · Journal of Geophysical Research: Atmospheres · doi:10.1029/94jd02950 · Cited by 4,169
A Comprehensive Mass Flux Scheme for Cumulus Parameterization in Large-Scale Models
Tiedtke, M. (1989) · Monthly Weather Review · doi:10.1175/1520-0493(1989)117<1779:acmfsf>2.0.co;2 · Cited by 3,648
Organic aerosol and global climate modelling: a review
Kanakidou, M., Seinfeld, J. H., Pandis, S. N., Barnes, I., Dentener, F. J., Facchini, M. C., Van Dingenen, R., Ervens, B., Nenes, A., Nielsen, C. J., et al. (2005) · Atmospheric Chemistry and Physics · doi:10.5194/acp-5-1053-2005 · Cited by 3,244
Advances in Understanding Clouds from ISCCP
Rossow, W. B., & Schiffer, R. A. (1999) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(1999)080<2261:aiucfi>2.0.co;2 · Cited by 2,256
Formation and growth rates of ultrafine atmospheric particles: a review of observations
Kulmala, M., Vehkamäki, H., Petäjä, T., Dal Maso, M., Lauri, A., Kerminen, V.-M., Birmili, W., & McMurry, P. H. (2004) · Journal of Aerosol Science · doi:10.1016/j.jaerosci.2003.10.003 · Cited by 2,191
Sources and distributions of dust aerosols simulated with the GOCART model
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O., & Lin, S. (2001) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2000jd000053 · Cited by 2,167
Nightingale, P. D., Malin, G., Law, C. S., Watson, A. J., Liss, P. S., Liddicoat, M. I., Boutin, J., & Upstill‐Goddard, R. C. (2000) · Global Biogeochemical Cycles · doi:10.1029/1999gb900091 · Cited by 1,477
Atkinson, R., Baulch, D. L., Cox, R. A., Hampson, R. F., Kerr, J. A., & Troe, J. (1992) · Journal of Physical and Chemical Reference Data · doi:10.1063/1.555918 · Cited by 1,289
Cited by
The role of low-volatility organic compounds in initial particle growth in the atmosphere
Tröstl, J., Chuang, W. K., Gordon, H., Heinritzi, M., Yan, C., Molteni, U., Ahlm, L., Frege, C., Bianchi, F., Wagner, R., et al. (2016) · Nature · doi:10.1038/nature18271 · Cited by 850
Self-citationOxidation products of biogenic emissions contribute to nucleation of atmospheric particles
Riccobono, F., Schobesberger, S., Scott, C. E., Dommen, J., Ortega, I. K., Rondo, L., Almeida, J., Amorim, A., Bianchi, F., Breitenlechner, M., et al. (2014) · Science · doi:10.1126/science.1243527 · Cited by 642
Self-citationBlack-carbon absorption enhancement in the atmosphere determined by particle mixing state
Liu, D., Whitehead, J., Alfarra, M. R., Reyes-Villegas, E., Spracklen, D. V., Reddington, C. L., Kong, S., Williams, P. I., Ting, Y.-C., Haslett, S., et al. (2017) · Nature Geoscience · doi:10.1038/ngeo2901 · Cited by 503
Self-citationCauses and importance of new particle formation in the present‐day and preindustrial atmospheres
Gordon, H., Kirkby, J., Baltensperger, U., Bianchi, F., Breitenlechner, M., Curtius, J., Dias, A., Dommen, J., Donahue, N. M., Dunne, E. M., et al. (2017) · Journal of Geophysical Research: Atmospheres · doi:10.1002/2017jd026844 · Cited by 478
Self-citationEvaluating the climate and air quality impacts of short-lived pollutants
Stohl, A., Aamaas, B., Amann, M., Baker, L. H., Bellouin, N., Berntsen, T. K., Boucher, O., Cherian, R., Collins, W., Daskalakis, N., et al. (2015) · Atmospheric Chemistry and Physics · doi:10.5194/acp-15-10529-2015 · Cited by 455
Metadata
- Authors
- Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T., Chipperfield, M. P., Pickering, S. J., & Johnson, C. E.
- Venue
- Geoscientific Model Development
- Publisher
- Copernicus GmbH
- Published
- 2010-10-13
- Volume
- 3
- Issue
- 2
- Pages
- 519-551
- ISSN
- 1991-959X (ISSN-L)
- 1991-9603
- OpenAlex
- W2145318668
- Cited by
- 538
- References
- 77
- FWCI
- 10.18
- Type
- journal article
- Language
- en
- Open access
- gold
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- Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T., Chipperfield, M. P., Pickering, S. J., & Johnson, C. E. (2010). Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model. Geoscientific Model Development. https://doi.org/10.5194/gmd-3-519-2010
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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