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TZID:Europe/Berlin
TZUNTIL:20211031T010000Z
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DTSTART:20191027T030000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
RDATE:20201025T030000
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UID:www.bayceer.uni-bayreuth.de-bayceer-t150119id
DTSTAMP:20260817T072245Z
DESCRIPTION:The MiSKOR project is to provide the appropriate strategy to mi
 tigate the impacts of climate change jeopardizing urban life through extre
 me high temperatures and resulting high surface ozone (O3) concentrations.
  This talk is about the application of statistical tools in the trend anal
 ysis and modeling of O3 formation in northern Bavaria (NB). The trend anal
 ysis of O3 and O3 health metrics is implemented on both regional (NB) and 
 country scales (Germany). We also used linear- and tree-based gradient boo
 sting machines (MLR-GBM and Tree-GBM) and logistic regression (LR) for the
  estimation\, forecast and classification of hourly O3 concentration data 
 at unmonitored stations within NB. The performance of these statistical mo
 dels is compared with the ensembles of seven state-of-the-art numerical ai
 r quality models run in the framework of the Copernicus Atmosphere Monitor
 ing Service (CAMS) regional air quality model for Europe (CAMS-EU). This i
 s the first attempt to check the feasibility of using a hybrid model from 
 the combination of GBM and CAMS-EU simulations for the site-scale predicti
 on of O3.
DTSTART;TZID=Europe/Berlin:20191114T120000
DTEND;TZID=Europe/Berlin:20191114T133000
SUMMARY:Dr. Seyed Omid Nabavi\, Climatology\, BayCEER\, University of Bayre
 uth (Homepage): Analysis of ozone formation and trend over northern Bavari
 a by using stochastic and deterministic models
TRANSP:TRANSPARENT
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