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dc.contributor.authorBanks, Robert F.
dc.contributor.authorBaldasano, Jose M.
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2016-08-11T09:35:21Z
dc.date.available2016-08-11T09:35:21Z
dc.date.issued2016-12-01
dc.identifier.citationBanks, Robert F.; Baldasano, Jose M. Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain. "Science of The Total Environment", 1 Desembre 2016, vol. 572, p. 98-113.
dc.identifier.issn0048-9697
dc.identifier.urihttp://hdl.handle.net/2117/89377
dc.description.abstractHere we analyze the impact of four planetary boundary-layer (PBL) parametrization schemes from the Weather Research and Forecasting (WRF) numerical weather prediction model on simulations of meteorological variables and predicted pollutant concentrations from an air quality forecast system (AQFS). The current setup of the Spanish operational AQFS, CALIOPE, is composed of the WRF-ARW V3.5.1 meteorological model tied to the Yonsei University (YSU) PBL scheme, HERMES v2 emissions model, CMAQ V5.0.2 chemical transport model, and dust outputs from BSC-DREAM8bv2. We test the performance of the YSU scheme against the Assymetric Convective Model Version 2 (ACM2), Mellor-Yamada-Janjic (MYJ), and Bougeault-Lacarrère (BouLac) schemes. The one-day diagnostic case study is selected to represent the most frequent synoptic condition in the northeast Iberian Peninsula during spring 2015; regional recirculations. It is shown that the ACM2 PBL scheme performs well with daytime PBL height, as validated against estimates retrieved using a micro-pulse lidar system (mean bias = − 0.11 km). In turn, the BouLac scheme showed WRF-simulated air and dew point temperature closer to METAR surface meteorological observations. Results are more ambiguous when simulated pollutant concentrations from CMAQ are validated against network urban, suburban, and rural background stations. The ACM2 scheme showed the lowest mean bias (− 0.96 μg m− 3) with respect to surface ozone at urban stations, while the YSU scheme performed best with simulated nitrogen dioxide (− 6.48 μg m− 3). The poorest results were with simulated particulate matter, with similar results found with all schemes tested.
dc.description.sponsorshipThe research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013): People, ITN Marie Curie Actions Programme (2012–2016) in the frame of ITaRS under grant agreement no. 289923. Simulations were executed on the MareNostrum supercomputer at the Barcelona Supercomputing Centre, under grants SEV-2011-00067 of Severo Ochoa program and CGL2013-46736-R, awardedby theSpanish Government.Specialthanks to Francesc Rocadenbosch and the UPC Remote Sensing Laboratory for use of the extended Kalman filter technique. The authors wish to thank Victor Valverde for his assistance with the air quality simulations.
dc.format.extent16 p.
dc.language.isoeng
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivs 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectÀrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia
dc.subject.lcshWeather Prediction Research Programmes
dc.subject.lcshMeteorological instruments
dc.subject.lcshAir quality
dc.subject.otherAtmospheric modelling
dc.subject.otherWeather research and forecasting (WRF) model
dc.subject.otherRemote sensing
dc.subject.otherAir quality
dc.subject.otherLidar
dc.titleImpact of WRF model PBL schemes on air quality simulations over Catalonia, Spain
dc.typeArticle
dc.subject.lemacClima--Observacions
dc.subject.lemacMeteorologia--Metodologia
dc.subject.lemacAire--Qualitat
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0048969716316217
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/CGL2013-46736-R
upcommons.citation.publishedtrue
upcommons.citation.publicationNameScience of The Total Environment
upcommons.citation.volume572
upcommons.citation.startingPage98
upcommons.citation.endingPage113


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