FAIRMODE QUALITY ASSURANCE OF MODELS. S. Galmarini Joint Research Center Ispra

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1 1 FAIRMODE QUALITY ASSURANCE OF MODELS S. Galmarini Joint Research Center Ispra

2 2 FAIRMODE is steered by the air quality legislation To provide a permanent European Forum for Air Quality Modellers and Model Users To produce guidance on the use of air quality models (including fitness for purpose) for assessing current and future air quality for the purpose of implementation of the Air Quality Directive and in preparation to the revision of this Directive To study and set-up a system on the quality assurance and the continuous improvements of air quality models To make recommendations for further research and other relevant improvements, such as improvements on emission inventories, meteorology, boundary conditions, temporal and geographic scale

3 FAIRMODE Communication 3 FAIRMODE AirBase EEA s data centre GMES observations COST actions EU projects FP6, FP7 AQMEII Other Interested Modelling experts FAIRMODE Invited experts EEA EC-JRC DG-ENV ETC/ACC EIONET Model Users CLRTAP UNECE/EMEP WG1 Guidance on modelling Best modelling practices Protocols for QA of models Input to legislation WG2 Quality assurance

4 FAIRMODE ORGANISATION 4 WG1 Guidance Documents and Dissemination N + 1 Iteration N WG2 Competence Building and Benchmarking

5 5 FAIRMODE WG2 Its main goal is develop a user friendly system to assess the quality of air quality models used under the implementation of the Directives Protocols for model quality assessment Benchmarking tools Dialogue and exchange WG2 provides input and recommendations to WG1 in order to produce better guidance

6 6 Protocol for quality assessment of models WG2 contribution Model/Method documentation Good pratice guidance, for the combination of models and observations (SG1) Protocol for assessment of methods for source allocation (SG2) Input data documentation: Focus on emission/projection compilation at urban scale (SG3) Model validation: Evaluation of appropriate MQI model performance indicators and identification of response indicators Interactions with AQMEII, TFMM, EURODELTA Model benchmarking: Elaboration of a prototype for benchmarking models in urban agglomeration (SG4)

7 WG2 ORGANISATION 7 WG 2 is organised in 4 different groups SG (1) Models and Measurements- Bruce Denby SG( 2) - Source Allocation-John Douros SG (3) Emissions and Projections-Julio Lumbreras SG (4) Benchmarking and Tools - Philippe Thunis

8 How do the SGs work together? 8 SG4 Benchmarking SG1 Models and Measurements SG2 Source allocation SG3 Emissions WG2 Coordination WG1 Guidance

9 Overview of AQD applications & scale in on-going projects 9 Applications for the AQD Local-Hot spot (dx ~ m) Urban/Agglom (dx ~ 1-5 km) Regional (dx ~ km) Compliance / Assessment Mitigation & Planning Data Assimilation Fusion Emission scenarios Source Apportionment TRANSPHORM COST 732 TRANSPHORM TRANSPHORM PASODOBLE PASODOBLE EURODELTA AQMEII CITYZEN MEGAPOLI MACC EURODELTA CITYZEN MEGAPOLI MACC MEGAPOLI EC4MACS Public information AQ near real time forecast 9 FAIRMODE PASODOBLE MACC COST 602 Chemical Weather Nov. 19, 2009

10 10 WG2 DELIVERABLES FOR Protocols for best practice on data assimilation and on source allocation 2. Prototype tool for benchmarking urban scale models 3. Background document on need for emission data and guidance in local/urban scale Workshop on emissions with local authorities/impel Framework proposal

11 WG Main activities SG1 SG1 Combining monitoring and modelling (I) 11 Collecting information about groups and their methods and applications (data assimilation) Provide an assessment concerning the fitness for purpose. Identify objectives and indicators. Provide basic recommendations for applications relevant to the directive (forecasting and compliance assessment) Ø Links to Air4EU, MACC, PASODOBLE, COST 602

12 WG Main activities SG1 SG1 - Combining monitoring and modelling (II) 12 Evaluation of nesting procedures and capabilities will be carried out by the work in PASODOBLE, links are to be ensured Evaluation of the Representativeness of observations Need to evaluate station evaluation criteria Recommendations on position of monitoring stations Needs for new monitoring data

13 WG Main activities SG2 SG2 Contribution of natural sources and source allocation 13 Extended review of the guidance from the WG on Implementation Review of experiences from the members states reporting under Art.20 and 21 Protocol for best practice for model uses beyond receptor modelling for Winter sanding Wind-blown dust Sea salt Wild open fires Links to MACC, PASODOBLE,MEGACITIES And TFMM

14 WG Main activities SG3 SG3 on urban emissions and projections (I) 14 Background document on the emission needs at local scale Needs for guidance on emission compilation at urban level Consistency with national inventories Top down vs bottom up approches Use of GIS tools

15 WG Main activities SG3 SG3 on urban emissions and projections (II) 15 Urban emission compilation is a key issue at European level Both guidance and relevant exchange fora are needed Workshop with city authorities in 2010 Proposal for a framework for the development of emission inventories at local scale Links to TFEIP/EIONET, GEIA, JRC-EDGAR Funding will be needed!

16 FAIRMODE FAIRMODE 16 SG4 (JRC) Benchmarking Within SG4 a procedure for model bench marking has been devised and accepted by the FAIRMODE community Within the procedure ENSEMBLE will be used for deep model evaluation, multi model analysis and research

17 17 USER Data Extraction Facility JRC Model results DELTA BENCHMARKING service Unofficial Working Report Official Reports Unofficial Working Report

18 The benchmarking service (II) 18 Core set of statistical indicators R Correlation B Bias SD Standard deviation RMSE Root Mean Square Error RMSEs Systematic RMSE RMSEu Unsystematic RMSE CRMSE Centered RMSE IOA Index of Agreement MFB Mean Fractional Bias MFE Mean Fractional Error RDE Relative Directive Error RPE Relative Percentile Error

19 The benchmarking service (III) 19 Criteria: Model acceptable performance for a given type of application (e.g. PM: MFE=75%, MFB=+/-60%) Goal: Best performance a model should aim to reach given its current capabilities (e.g. PM: MFE=50%, MFB=+/-30%) Observation Uncertainty: Accuracy level of the measurements

20 The benchmarking service (II) 20 CMRSE Cos-1R Summary Diagrams

21 The benchmarking service (IV) 21 Performance summary report

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