TITLE:
Enhancing Air Quality Forecasts over Catalonia (Spain) Using Model Output Statistics
AUTHORS:
Víctor Andrés Pérez, Raúl Arasa, Bernat Codina, Jesica Piñón
KEYWORDS:
Air Quality Modelling, Forecasting, Model Output Statistics (MOS)
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.3 No.8,
October
9,
2015
ABSTRACT: Model
Output Statistics (MOS) is a well-known technique that allows improving outputs
from numerical atmospheric models. In this contribution, we present the development
of a MOS algorithm to improve air quality forecasts in Catalonia, a region in
the northeast of Spain. These forecasts are obtained from an Eulerian coupled
air quality modelling system developed by Meteosim. Nitrogen Dioxide (NO2),
Particulate Matter (PM10) and Ozone (03) have been the
pollutants considered and the methodology has been applied on statistical
values of these pollutants according to regulatory levels. Four MOS algorithms
have been developed, characterized by different approaches in relation with
seasonal stratification and stratification according to the measurement
stations considered. Algorithms have been compared among them in order to
obtain a MOS that reduces the forecast uncertainties. Results obtained show
that the best MOS designed increases the accuracy of NO2 maximum 1-h
daily value forecast from 71% to 75%, from 68% to 81% in the case of daily
values of PM10, and finally, the accuracy of O3 maximum
1-h daily value from 79% to 87%.