1 Technical Department, Meteosim S.L., Barcelona, Spain. 2 Department of Astronomy and Meteorology, University of Barcelona, Barcelona, Spain.
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%.
Pérez, V. , Arasa, R. , Codina, B. and Piñón, J. (2015) Enhancing Air Quality Forecasts over Catalonia (Spain) Using Model Output Statistics. Journal of Geoscience and Environment Protection, 3, 9-22. doi: 10.4236/gep.2015.38002.
[1] Newby, D.E., Manucci, P.M., Grethe, S.T., Baccarelli, A.A., Brook, R.D., Donaldson, K., Forastiere, F., Franchini, M., Franco, O.H., Graham, I., Hoek, G., Hoffmann, B., Hoylaerts, M.F., Künzli, N., Mills, N., Peklanen, J., Peters, A., Piepoli, M.F., Rajagopalan, S. and Storey, R.F. (2014) Expert Position Paper on Air Pollution and Cardiovascular Disease. European Heart Journal, in Press.
http://dx.doi.org/10.1093/eurheartj/ehu458
[2] Crutzen, P.J. (2004) New Directions: The Growing Urban Heat and Pollution Island Effect-Impact on Chemistry and Climate. Atmospheric Environment, 38, 3539-3540.
http://dx.doi.org/10.1016/j.atmosenv.2004.03.032
[3] Ritter, M., Müller, D., Tsai, M.-Y. and Parlow, E. (2013) Air Pollution Modeling over Very Complex Terrain: An Evaluation of WRF-Chem over Switzerland for Two 1-Year Periods. Atmospheric Research, 132-133, 209-222.
http://dx.doi.org/10.1016/j.atmosres.2013.05.021
[4] Querol, X., Viana, M., Moreno, T. and Alastuey, A. (2012) Bases científico-técnicas para un Plan Nacional de Mejora de la Calidad del Aire. Consejo Superior de Investigaciones Científicas (CSIC).
[5] Soler, M.R., Hinojosa, J., Bravo, M., Pino, D. and Vila, J. (2004) Analyzing the Basic Features of Different Complex Terrain Flows by Means of a Doppler Sodar and a Numerical Model: Some Implications to Air Pollution Problems. Meteorological Atmospheric Physics, 85, 141-154. http://dx.doi.org/10.1007/s00703-003-0041-z
[6] Aguirre-Basurko, E., Ibarra-Berastegui, I. and Madariaga, I. (2006) Regression and Multilayer Perceptron-Based Models to Forecast Hourly O3 and NO2 Levels in the Bilbao Area. Environmental Modelling Software, 21, 430-446.
http://dx.doi.org/10.1016/j.envsoft.2004.07.008
[7] McKeen, S., Wilczak, J. and Grell, G. (2005) Assessment of an Ensemble of Seven Real-Time Ozone Forecasts over Eastern North America during the Summer of 2004. Journal of Geophysical Research D, 110, Article ID: D21307.
[8] Wilczak, J.M., McKeen, S. and Djalalova, I. (2006) Bias-Corrected Ensemble and Probabilistic Forecasts of Surface Ozone over Eastern North America during the Summer of 2004. Journal of Geophysical Research D, 111, Article ID: D23S28.
http://dx.doi.org/10.1029/2006jd007598
[9] Delle Monache, L., Nipen, T., Deng, X., Zhou, Z. and Stull R. (2006) Ozone Ensemble Forecasts: 2. A Kalman Filter Predictor Bias Correction. Journal of Geophysical Research D, 111, Article ID: D05308.
[10] Kang, D., Mathur, R., Rao, S.T. and Yu, S. (2008) Bias Adjustment Techniques for Improving Ozone Air Quality Forecasts. Journal of Geophysical Research, 113, Article ID: D23308.
[11] Djalalova, J., Wilczak, J., McKeen, S., Grell, G., Peck-Ham, S., Pagowski, M., DelleMonache, L., McQueen, J., Tang, Y., Lee, P., McHenry, J., Gong, W., Bouchet, V. and Mathur, R. (2010) Ensemble and Bias-Correction Techniques for Air Quality Model Forecasts of Surface O3 and PM2.5 during the TEXAQS-II Experiment of 2006. Atmospheric Environment, 44, 455-467.
http://dx.doi.org/10.1016/j.atmosenv.2009.11.007
[12] Arasa, R., Soler, M.R. and Olid, M. (2012) Numerical Experiments to Determine MM5/WRF-CMAQ Sensitivity to Various PBL and Land-Surface Schemes in North-Eastern Spain: Application to a Case Study in Summer 2009. International Journal of Environment and Pollution, 48, 105-116.
http://dx.doi.org/10.1504/IJEP.2012.049657
[13] Dallavalle, J.P., Ericksonv, M.C. and Maloney, J.C. (2000) Model Output Statistics (Mos) Guidance for Short-Range Projections. National Weather Service/NOAA.
[14] Nicolis, C. and Vannitsem, S. (2007) Dynamical Properties of Model Output Statistics Forecasts. Institute Royal Meteo-rologique de Belgique, Brussels.
[15] Glahn, B., Peroutka, M. and Wiedenfeld, J. (2008) MOS Uncertainty Estimates in an Ensemble Framework. NOAAN, Wakeld, VA.
[16] Monarski, A. (2011) Verification of Model Output Statistics Forecasts Associated with the North American Mesoscale Model Upgrade. Master’s Scholarly Paper, Department of Atmospheric and Oceanic Science, University of Maryland, College Park.
[17] Ranaboldo, M. (2011) Multiple Linear Regression MOS for Short-Term Wind Power Forecast. Universitat de Barcelona, Barcelona.
[18] Karl, T.R. (1978) Potential Application of Model Output Statistics to Forecast of Surface Ozone Concentrations. National Meteorological Center’s Limited Area.
[19] Jianming, X. and Xiangde, X. (2010) Study of Statistically Correcting Model CMAQ-MOS for Forecasting Regional Air Quality. Nanjing University of Information Science Technology, Nanjing.
[20] Pijnappel, A. (2011) Statistical Post Processing of Model Output from the Air Quality Model LOTOS-EUROS. De Bilt, Stageverslag.
[21] Arasa, R., Picanyol, M. and Solé, J.M. (2013) Analysis of the Integrated Environmental and Meteorological Forecasting and Alert System (SIAM) for Air Quality Applications over Different Regions of the Iberian Peninsula.
http://www.harmo.org/Conferences/Proceedings/_Madrid/downloadItem.asp?CID=H15-70
[22] Denby, B. (2010) Guidance on the Use of Models for the European Air Quality Directive. A Working Document of the Forum for Air Quality Modelling in Europe FAIR-MODE, ETC/ACC Report.
[23] Miles, J. and Shelvin, M. (2001) Applying Regression Correlation. Sage Publications, London.
[24] Pérez López, C. (2003) Estadística. Problemas resueltos y problemas. Editorial Pearson.
[25] Wilks, S.D. (2006) Statistical Methods in the Atmospheric Sciences. Second Edition, Academic Press, Waltham.
[26] Montgomery, D.C., Peck, E.A. and Vining, G.G. (2011) Introducció al Análisis de Regressión Lineal. Grupo Editorial Patria. Tercera edición.
[27] Chatterjee, S., Hadi, A.S. and Price, B. (2012) Regression Analysis by Examples. Fifth Edition, Wiley Series in Probability and Statistics.
[28] Willmott, C.J., Ackleson, S.G., Davis, R.E., Feddema, J.J., Klink, K.M., Legates, D.R., O’Donnell, J. and Rowe, C.M. (1985) Statistics for the Evaluation and Comparison of Models. Journal of Geophysical Research, 90, 8995-9005.
[29] EPA (2009) Reassessment of the Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report: Revisions to Phase 2 Recommendations. Draft for Internal Review. US EPA Report No. EPA-454/R-09-XXX, Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina.
[30] Arasa, R. (2010) Avaluació del rendiment del sistema de modelització MM5/MNEQA/CMAQ de la qualitat de l’aire per a pronosticar l’ozó a Catalunya. Tethys núm. 7.
[31] Arasa, R. (2011) Modelització i simulació fotoquíimica mesoescalar del transport del material particular i gasos a l’atmosfera. Tesis doctoral, Universitat de Barcelona, Barcelona.
[32] EPA (1991) Guideline for Regulatory Application of the Urban Airshed Model. US EPA Report No. EPA-450/4-91-013. Office of Air and Radiation, Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina.
[33] EPA (2005) Guidance on the Use of Models and Other Analyses in Attainment Demonstrations for the 8-Hour Ozone NAAQS. US EPA Report No. EPA-454/R-05-002, Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina.