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Status and future of Numerical Atmospheric Aerosol Prediction with a focus on data requirements
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dc.contributor.authorBenedetti, Angelaes_ES
dc.contributor.authorReid, Jeffrey Ses_ES
dc.contributor.authorBaklanov, Alexanderes_ES
dc.contributor.authorBasart, Saraes_ES
dc.contributor.authorBoucher, Olivieres_ES
dc.contributor.authorBrooks, Ian M.es_ES
dc.contributor.authorBrooks, Malcolmes_ES
dc.contributor.authorColarco, Peter R.es_ES
dc.contributor.authorCuevas Agulló, Emilioes_ES
dc.contributor.authorSilva, Arlindo daes_ES
dc.contributor.authorGiuseppe, Francesca Dies_ES
dc.contributor.authorEscribano, Jerónimoes_ES
dc.contributor.authorFlemming, Johanneses_ES
dc.contributor.authorHuneeus, Nicolases_ES
dc.contributor.authorJorba, Orioles_ES
dc.contributor.authorKazadzis, Stelioses_ES
dc.contributor.authorKinne, Stefanes_ES
dc.contributor.authorKnippertz, Peteres_ES
dc.contributor.authorLaj, Paoloes_ES
dc.contributor.authorMarsham, John H.es_ES
dc.contributor.authorMenut, Laurentes_ES
dc.contributor.authorMona, Luciaes_ES
dc.contributor.authorPopp, Thomases_ES
dc.contributor.authorQuinn, Patricia K.es_ES
dc.contributor.authorRemy, Samueles_ES
dc.contributor.authorSekiyama, Thomas S.es_ES
dc.contributor.authorTanaka, Taichues_ES
dc.contributor.authorTerradellas, Enrices_ES
dc.contributor.authorWiedensohler, Alfredes_ES
dc.date.accessioned2018-03-12T09:31:59Z-
dc.date.available2018-03-12T09:31:59Z-
dc.date.issued2018-
dc.identifier.citationAtmospheric Chemistry and Physics Discussions. 2018es_ES
dc.identifier.issn1680-7367-
dc.identifier.issn1680-7375-
dc.identifier.urihttp://hdl.handle.net/20.500.11765/8806-
dc.description.abstractNumerical prediction of aerosol particle properties has become an important activity at many research and operational weather centres due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, providers of climate services, and health professionals. The prediction of aerosol particle properties in Numerical Weather Prediction (NWP) models faces a number of challenges owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions. Errors in aerosol prediction concern all processes involved in the aerosol life cycle. These include errors on the source terms (for both anthropogenic and natural emissions), errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), as well as errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transformation and growth, hygroscopicity). The main goal of current research on aerosol forecast consists in prioritizing these errors and trying to reduce the most important ones through model development and data assimilation. Aerosol particle observations from satellite and ground-based platforms have been crucial to guide model development of the recent years, and have been made more readily available for model evaluation and assimilation (...)es_ES
dc.description.sponsorshipAngela Benedetti has received funding from the H2020 Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS2, Grant Number 654109).es_ES
dc.language.isoenges_ES
dc.publisherEuropean Geosciences Uniones_ES
dc.rightsLicencia CC: Reconocimiento CC BYes_ES
dc.subjectAerosol particlees_ES
dc.subjectNumerical predictiones_ES
dc.subjectAerosol predictiones_ES
dc.subjectAtmospheric composition predictiones_ES
dc.subjectSatellite measurementses_ES
dc.titleStatus and future of Numerical Atmospheric Aerosol Prediction with a focus on data requirementses_ES
dc.typeinfo:eu-repo/semantics/preprintes_ES
dc.relation.publisherversionhttps://dx.doi.org/10.5194/acp-2018-42es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/654109es_ES
Colecciones: Artículos científicos 2015-2018


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