Verification of the quantitative forecast of the precipitation of the WRF model for the provinces Artemisa, Mayabeque and Havana
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Published:
Jul 1, 2017
Keywords:
precipitation, numeric forecast, verification, quantitative estimation
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Abstract
It is made a punctual and spatial verification of the quantitative precipitation forecast (QPF), obtained from the model WRF-ARW in the provinces of Artemisa, Mayabeque and Havana, in Western region of Cuba. This evaluation was made throughout the use of quantitative precipitation estimation (QPE) data from the polarimetric radar of Key West (KBYX),especially 3-hours and 24-hours accumulates. Comparisons were made between these estimations and the pluviometric data obtained from INSMET. Due to correct it, was necessary to take into account two methodologies according to the Cressmaninterpolation method and a modification of the same one, where the orography and its influence in the QPE values are considered; noticeable differences between both procedures were obtained. The analyzed period included months of May 2008, July 2012, January 2013 and September 2013. Investigations were based on model WRF numerical outputs, initialized throughout the 0000 and 1200 UTC runs of the GFS model forecast loops. With the simulation verification process, it was demonstrated that the QPF presents an over-estimation of the total accumulated precipitation values in 3 and 24 hours experiments; however, the model maintained a good spatial representation of rain areas. The comparison with rectified QPE data kept an over-estimation of BIAS, but the mean absolute error decreased.
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PachecoS. M., RamírezC. M. G., & FerrerA. L. (2017). Verification of the quantitative forecast of the precipitation of the WRF model for the provinces Artemisa, Mayabeque and Havana. Revista Cubana De Meteorología, 23(2), 148-163. Retrieved from http://rcm.insmet.cu/index.php/rcm/article/view/236
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Original Articles
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References
Cressman, G. P., 1959: “An operational objective analysis system.” Mon. Wea. Rev.87, 367-374.
Díaz O., Sierra M. et al. (2013): "Asimilación y desarrollo de métodos de evaluación de pronóstico numérico para Cuba y Mares Interamericanos". Proyecto: "Actualización de la distribución espacial de las tormentas eléctricas en Cuba".Código Agencia: 300.20455.
Mesoscale & Microscale Meteorology Division. 2014. ARW Version 3 Modeling System User’s Guide. Complementary to the ARW Tech Note, 411pp. NCAR: Boulder, Colorado, USA. Web: http://www2.mmm.ucar.edu/wrf/users/docs/userguide V3/ARWUsersGuideV3.pdf
Mitrani, I., I. Borrajero, A. Bezanilla (2006): "Pronóstico de lluvia sobre territorio cubano al paso de los huracanes Charley e Iván, usando MM5V3". Climate Variability and Change-Hydrological Impacts (FRIEND 2006, Havana, Cuba). IAHS Publ. No.308, ISSN: 0144-7815.:201-206, November 2006.
Reggiani, P. and A. H. Weerts (2008): Probabilistic Quantitative Precipitation Forecast for Flood Prediction: An Application. AmericanMeteorological Society.Volume 9, February 2008.
Rezacova et al. (2014): Verification of high-resolution precipitation forecast by radar-based data.
Sinclair, G., and G. Pegram, 2004: Combining radar and rain gauge rainfall estimates using conditional merging. Atmos. Sci. Lett.,6,19–22
Sierra, M., A. Ferrer et al. (2014): "Sistema automático de predicción a mesoescala de cuatro ciclos diarios". Proyecto: "Sistema de Predicción a muy corto plazo basado en el Acoplamiento de Modelos de Alta".
Díaz O., Sierra M. et al. (2013): "Asimilación y desarrollo de métodos de evaluación de pronóstico numérico para Cuba y Mares Interamericanos". Proyecto: "Actualización de la distribución espacial de las tormentas eléctricas en Cuba".Código Agencia: 300.20455.
Mesoscale & Microscale Meteorology Division. 2014. ARW Version 3 Modeling System User’s Guide. Complementary to the ARW Tech Note, 411pp. NCAR: Boulder, Colorado, USA. Web: http://www2.mmm.ucar.edu/wrf/users/docs/userguide V3/ARWUsersGuideV3.pdf
Mitrani, I., I. Borrajero, A. Bezanilla (2006): "Pronóstico de lluvia sobre territorio cubano al paso de los huracanes Charley e Iván, usando MM5V3". Climate Variability and Change-Hydrological Impacts (FRIEND 2006, Havana, Cuba). IAHS Publ. No.308, ISSN: 0144-7815.:201-206, November 2006.
Reggiani, P. and A. H. Weerts (2008): Probabilistic Quantitative Precipitation Forecast for Flood Prediction: An Application. AmericanMeteorological Society.Volume 9, February 2008.
Rezacova et al. (2014): Verification of high-resolution precipitation forecast by radar-based data.
Sinclair, G., and G. Pegram, 2004: Combining radar and rain gauge rainfall estimates using conditional merging. Atmos. Sci. Lett.,6,19–22
Sierra, M., A. Ferrer et al. (2014): "Sistema automático de predicción a mesoescala de cuatro ciclos diarios". Proyecto: "Sistema de Predicción a muy corto plazo basado en el Acoplamiento de Modelos de Alta".