European Developments in Mesoscale Modelling for Air Pollution Applications Activities of the COST 728 Action

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European Developments in Mesoscale Modelling for Air Pollution Applications Activities of the COST 728 Action R S Sokhi*, A Baklanov, H Schlünzen, M Sofiev, M Athanassiadou, Peter Builtjes and COST 728 Members *Centre for Atmospheric and Instrumentation Research (CAIR) University of Hertfordshire, UK

COST 728 Action www.cost728.org ENHANCING MESO-SCALE METEOROLOGICAL MODELLING CAPABILITIES FOR AIR POLLUTION AND DISPERSION APPLICATIONS 25 Countries represented with USA, Canada, Russia, Macao, WMO

Meteorological and Air Quality - Complexities Mesoscale effects Local - urban effects

Main Objectives of COST 728 Review and classification models, schemes, databases, evaluation procedures, applications, integration strategies Identification of Improvements schemes, interfaces, data requirements Recommendations - development, operation, validation, applications, European strategy Procedures and protocols for using mesoscale models for air pollution applications

Working Groups WG1 - Meteorological parametrization/applications (Maria Athanassiadou, UK Met Office) WG2 - Integrated systems of MetM-CTM, interfaces, module unification, strategy (Alexander Baklanov, DMI) WG3 - Mesoscale models for air pollution and dispersion applications (Mikhail Sofiev, FMI) WG4 - Development of evaluation tools and methodologies (Heinke Schluenzen, University of Hamburg)

Fragkou 2006 PhD Comparison of PBL Schemes WG1 Surface temperature predicted by different PBL schemes Bedford - suburban LWC - Urban

Integrated FUMAPEX urban module for NWP models different levels of complexity of the NWP urbanization (Baklanov et al)

On-line & Off-line modeling Baklanov et al WG2 On-line coupling Only one grid; No interpolation in space No time interpolation Physical parameterizations are the same; No inconsistencies All 3D Met. Variables are available at the right time (each time step); No restriction in variability of met. fields Possibility to consider feedback mechanisms Does not need meteo- pre/postprocessors Off-line Possibility of independent parameterizations Low computational cost; More suitable for ensembles and operational activities Independence of atmospheric pollution model runs on meteorological model computations More flexible grid construction and generation for ACT models

Air pollution problems affecting European regions WG3 Southern Europe: (Mediterranean basin): Portugal, Spain, Southern France, Italy, Greece Summer Winter Long range transport Urban photochemical smog Local circulations impact (complex terrain + sea breeze) Rare winter episodes Dust pollution from Africa Impact of wild fires on aerosol loading Western Europe: France, Belgium, Netherlands, Germany, United Kingdom Regional scale photochemical episodes Urban photochemical smog Urban winter smog, impact of local sources Transcontinental transport from N America Stratospheric ozone intrusions UK- transport from Western Europe

Air pollution problems affecting European regions Central Europe: Poland, Czech, Hungary, Bulgaria Northern Europe: Finland, Estonia, Sweden, Norway Summer Winter Long range transport Regional scale photochemical episodes Urban photochemical smog Dispersion within complex terrain Biogenic emission during summer periods Forest fires within the region and around Urban winter smog Urban winter smog Spring dust episodes (re-suspenstion) Norway complex terrain flow Long range transport from Western Europe Impact of wild fires in Eastern Europe on aerosol loading Incidental dust transport from over Africa and Arabian Peninsula Pollen transport episodes Long range transport from Western and Central Europe; episodically from Russia

Model Evaluation WG4 The Drivers Schluenzen et al European commission - air quality directives National and local environmental agencies Model users Scientific robustness of methods

Purpose of formal evaluation protocols Comparable method for evaluating models Evaluation of the performance of single models Comparison of performance from different models helps to detect general model shortcomings (and thus deficits in our scientific understanding) in contrast to single model deficits Hints for improvements of models Method should allow a quantitative model evaluation General structure for all scales, benchmark tests need to be case specific (global, regional, urban, local) Cost effective model development Reduction of societal costs for model application

In collaboration with ACCENT and COST 732 Structure of protocol Structure of protocol Objective 1. General evaluation 2. Scientific evaluation 3. Benchmark tests Σ Evaluation Protocol Operational evaluation Part I: Model developer Part II: Model user

Joint Case Studies 2003 warm year influence of extreme met conditions on air quality 2006 forest fires Relative role of local/urban scales and LRT affecting European regions Frequency of episodes Model performance

Feb 2003 PM episode over Germany Builtjes et al

ENVISAT: April-May 2006 multi-pollutant episode Sofiev et al Anthrop.: Birch: Fires: