Mixture of experts for sequential PM10 forecasting in Normandy (France)

Within the framework of air quality monitoring in Normandy, we experiment the methods of sequential aggregation for forecasting concentrations of PM10 of the next day. Besides the field of application and the adaptation to the special context of the work of the forecaster, the main originality of this contribution is that the set of experts contains at the same time statistical models built by means of various methods and different sets of predictors, as well as experts which are deterministic chemical models of prediction modeling pollution, weather and atmosphere. Numerical results on recent data from April 2013 until March 2014, on three monitoring stations, illustrate and compare various methods of aggregation. The obtained results show that such a strategy improves clearly the performances of the best expert both in errors and in alerts and reaches an unbiased observed-forecasted scatterplot, difficult to obtain by usual methods.