Persistence as a reference in the estimate of the ability of Short Range Weather Forecast
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Abstract
A persistence forecasting method is presented for the determination of the ability of predictions issued by the Weather Forecast Center of the Institute of Meteorology of Cuba. All this in order to introduce a new approach in the verification of the forecasts before the current simplicity of the prediction’s evaluation. For the construction of the persistent, we proceeded from the procedure of Moya et al. (2013) and was made up of three algorithms for the prediction of: extreme temperatures and wind force in which maximum overlapping intervals were considered, wind direction in hierarchically organized selection criteria were used, as well as cloudiness and precipitation. Also, an adequacy of the method is exposed to the possibility of verifying the forecasts of cloud cover and of the area covered by rain through the satellite images. The validation of the proposal was made with technical predictions valid for twenty four hours in the rainy season of 2016 and observations of surface stations of the Institute of Meteorology of Cuba, yielding four new distributions of maximum overlapping intervals. In this period, the average effectiveness of short range predictions overcame that of persistent prediction. Both types of forecasts show a lower effectiveness in the months of May and October, related to the beginning and end of the rainy season in Cuba, and reaffirm the cloudiness and precipitation as the variables with the lowest historical compliance rates. A measure of the quality of forecast center predictions are given by the positive values of the ability index obtained for all meteorological variables involved in the assessment of predictions, except wind strength reaching negative values in favor of persistent prognosis. The results presented here allow to take into account in the final result of the evaluation the skill of the forecasts, mainly in those days where the variations of the meteorological conditions are remarkable.
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Valderá-FigueredoN., Ballester-PérezM., & Sánchez-Pérez Ángel L. (2018). Persistence as a reference in the estimate of the ability of Short Range Weather Forecast. Revista Cubana De Meteorología, 24(1), 29-43. Retrieved from http://rcm.insmet.cu/index.php/rcm/article/view/258
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References
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WILKS, D. S. (2006). Statistic Methods in Atmospheric Sciences. Academic Press, New York, 627 p.
CAZORLA, A., OLMO, F. J. & ALADOS-ARBOLEDAS, L. (2005): Estimación de la cubierta nubosa en imágenes de cielo mediante el algoritmo de clasificación KNN. XI Congreso Nacional de Teledetección. Puerto de la Cruz. Tenerife, pp. 335-338.
FERNÁNDEZ, A. J. & DÍAZ, Y. A. (2005): Catálogo de Procesos Sinóptico del Archipiélago Cubano en el periodo 1979-1993. Centro Meteorológico Provincial de Cienfuegos, Cuba, 167 p.
FINLEY, J. P. (1884). Tornado prediction. American Meteorological Journal 1(3), 85–88.
JOLLIFFE, I. T. & STEPHENSON, D. B. (2003). Forecast Verification: A Practicioner’s Guide in Atmospheric Science. John Wiley & Sons Ltd. Chichester, West Sussex, England, 240 p.
LECHA, L. B., PAZ, L. R. & LAPINEL, B. (1994): El clima de Cuba. Editorial Academia, La Habana, Cuba, 196 p.
MOYA, A. S., ESTRADA, A., BALLESTER, M. & GONZÁLEZ, C. (2013). Evaluación de los pronósticos del tiempo a corto plazo. Informe de Resultado Científico, Resultado 3, Proyecto Evaluación de los Pronósticos del Tiempo. Instituto de Meteorología INSMET. La Habana, Cuba, 55 p.
MURPHY, A. H. & DAAN, H. (1985): Forecast evaluation. En: Probability, Statistics and Desicion Making in the Atmospheric Sciences, Murphy, A. H. & Katz, R. W. (eds.). Westview Press, Boulder, CO, pp. 379-437.
ODAK, I. & PASARIÉ, Z. (2013): Persistency as a reference in verification forecast with categorical predictands, 21 p. Consultado el 15 de octubre de 2015 en http://www.meteohmd.hr/files/file/Aktivnosti/MeteoIzazovi/MI3/PDF/TALK_PR15.pdf
PORTELA, M. A. (2006): Meteorología General. Instituto de Meteorología INSMET. La Habana, Cuba, 240 p.
QUEVEDO, J. L. (2012): Estimación de las áreas de lluvia sobre Cuba a partir de las imágenes VIS e IR obtenidas del satélite GOES–E. Tesis presentada en opción al Título de Licenciado en Meteorología. Instituto Superior de Tecnologías y Ciencias Aplicadas InSTEC. La Habana, Cuba, 53 p.
RIEHL, H. (1965): Introduction to the atmosphere. McGraw-Hill Book Company. New York, 365 p.
SOROCHINSKI, M., GONZÁLEZ, C., RUBIO, G., CARCAÑO, G. & MARTÍNEZ, R. (1975). Métodos para la Evaluación de Pronósticos. Academia de Ciencias de Cuba. Instituto de Meteorología INSMET, 12 p.
THORNES, J. E. (1996): The quality and accuracy of a sample of public and commercial weather forecast in the UK. Meteorological Applications 3, 63–74.
THORNES, J. E. & PROCTOR, E. A. J. (1999): Persisting with persistence: The verification of radio 4 weather forecasts. Weather 54(10), 311–321. URL http://onlinelibrary.wiley.com/doi/10.1002/j.1477-8696.1999.tb03991.x/pdf.
TRUJILLO, G. (2011): Estimación de la cobertura nubosa sobre Cuba a partir de las imágenes del satélite GOES–E. Tesis presentada en opción al Título de Licenciado en Meteorología. Instituto Superior de Tecnologías y Ciencias Aplicadas InSTEC. La Habana, Cuba, 57 p.
WILKS, D. S. (2006). Statistic Methods in Atmospheric Sciences. Academic Press, New York, 627 p.