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Status and future of numerical atmospheric aerosol prediction with a focus on data requirements

Benedetti, Angela; Reid, Jeffrey S.; Knippertz, Peter ORCID iD icon 1; Marsham, John H.; Di Giuseppe, Francesca; Rémy, Samuel; Basart, Sara; Boucher, Olivier; Brooks, Ian M.; Menut, Laurent; Mona, Lucia; Laj, Paolo; Pappalardo, Gelsomina; Wiedensohler, Alfred; Baklanov, Alexander; Brooks, Malcolm; Colarco, Peter R.; Cuevas, Emilio; Silva, Arlindo da; ... mehr

Abstract:

Abstract. Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas–aerosol partitioning, chemical transformation and growth, hygroscopicity). ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000085154
Originalveröffentlichung
DOI: 10.5194/acp-18-10615-2018
Scopus
Zitationen: 54
Dimensions
Zitationen: 56
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2018
Sprache Englisch
Identifikator ISSN: 1680-7324
urn:nbn:de:swb:90-851542
KITopen-ID: 1000085154
HGF-Programm 12.01.02 (POF III, LK 01) Proc.res.f.multisc.predictab.of weather
Erschienen in Atmospheric chemistry and physics
Verlag European Geosciences Union (EGU)
Band 18
Heft 14
Seiten 10615–10643
Vorab online veröffentlicht am 25.07.2018
Nachgewiesen in Scopus
Dimensions
Web of Science
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