Submitted as: methods for assessment of models
12 Apr 2023
Submitted as: methods for assessment of models |  | 12 Apr 2023
Status: this preprint is currently under review for the journal GMD.

A standardized methodology for the validation of air quality forecast applications (F-MQO): Lessons learnt from its application across Europe

Lina Vitali, Kees Cuvelier, Antonio Piersanti, Alexandra Monteiro, Mario Adani, Roberta Amorati, Agnieszka Bartocha, Alessandro D'Ausilio, Paweł Durka, Carla Gama, Giulia Giovannini, Stijn Janssen, Tomasz Przybyła, Michele Stortini, Stijn Vranckx, and Philippe Thunis

Abstract. A standardized methodology for the validation of short-term air quality forecast applications was developed in the framework of FAIRMODE activities. The proposed approach, focusing on specific features to be checked when evaluating a forecasting application, investigates the model capability to detect sudden changes of pollutants concentrations levels, to predict threshold exceedances and to reproduce air quality indices. The proposed formulation relies on the definition of specific forecast Modelling Quality Objective and Performance Criteria, defining the minimum level of quality to be achieved by a forecasting application when it is used for policy purposes. The persistence model, which uses the most recent observed value as predicted value, is used as benchmark for the forecast evaluation. The validation protocol has been applied to several forecasting applications across Europe, using different modelling paradigms and covering a range of geographical contexts and spatial scales. The method is successful, with room for improvement, in highlighting shortcomings and strengths of forecasting applications. This provides a useful basis for using short-term air quality forecast as a supporting tool for correct information to citizens and regulators.

Lina Vitali et al.

Status: open (until 28 Jun 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2023-65', Juan Antonio Añel, 05 May 2023 reply
    • AC1: 'Reply on CEC1', Philippe Thunis, 12 May 2023 reply
      • CEC2: 'Reply on AC1', Juan Antonio Añel, 12 May 2023 reply
        • AC2: 'Reply on CEC2', Philippe Thunis, 12 May 2023 reply
          • CEC3: 'Reply on AC2', Juan Antonio Añel, 12 May 2023 reply
            • AC3: 'Reply on CEC3', Philippe Thunis, 19 May 2023 reply
              • CEC4: 'Reply on AC3', Juan Antonio Añel, 21 May 2023 reply
  • RC1: 'Comment on gmd-2023-65', Anonymous Referee #1, 16 May 2023 reply
  • RC2: 'Comment on gmd-2023-65', Anonymous Referee #2, 22 May 2023 reply

Lina Vitali et al.

Lina Vitali et al.


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Short summary
Air quality forecasting models play a key role in fostering short-term measures aimed at reducing human exposure to air pollution. Together with this role comes the need for a thorough assessment of the model performances to build confidence in models’ capabilities in particular when model applications support policymaking. In this paper, we propose an evaluation methodology and test it on several domains across Europe, highlighting its strengths and room for improvement.