Estudio de la climatología ecuatorial andina con métodos numéricos: pronósticos de tiempo, validaciones y reconstrucción de la atmósfera
Contenido principal del artículo
Resumen
La siguiente investigación, describe dos tipos de estudios acerca del clima y tiempo del Ecuador, implementando los modelos numéricos MM5 (Mesoescale Model versión 5) y WRF (Weather Research Forecasting Model), mostrando sus características principales e instalación para ajustarlo a las condiciones ecuatoriales. Los estudios que se realizan corresponden al pronóstico del tiempo del país, utilizando el modelo MM5 en variables como la temperatura, velocidad de viento y precipitaciones. El estudio de validación se lo hace sobre las precipitaciones de la ciudad de Quito a través de tablas de contingencia, estudiando los meses de agosto a octubre. Se logra así un POD (Probability of Detection) del 93,5% y un FAR (False Alarm Ratio) del 14%, evidenciando la temporada inusualmente seca que se registró en esas fechas. Asimismo se presenta la primera parte del estudio de la reconstrucción de la atmósfera ecuatorial, utilizando el modelo WRF, mostrando el estudio de los perfiles verticales de las velocidades de viento; para concluir este estudio será necesario examinar las series temporales de al menos 30 años. Se obtienen resultados preliminares con una zona de vientos máximos a los 17 km de altura, visualizando sobre este nivel una disminución de su intensidad.
Palabras Clave
modelos numéricos de mesoescala, climatología ecuatorial, predicción, validación, WRF
Citas
Beljaars, A.C.M., 1994. The parameterization of surface fluxes in large-scale models under free convection, Quart. J. Roy. Meteor. Soc., 121, 255–270.
Betts, A. K., 1986: A new convective adjustment scheme. Part I: Observational and theoretical basis. Quart. J. Roy. Meteor. Soc., 112, 677–691.
Betts,A.K.,andM.J.Miller,1986.Anewconvective adjustment scheme. Part II: Single column tests using GATE wave, BOMEX, and arctic air-mass data sets. Quart. J. Roy. Meteor. Soc.112, 693–709.
Chen, S.-H., and W.-Y. Sun, 2002. A one-dimensional time dependent cloud model. J. Meteor.Soc. Japan, 80, 99–118.
Chou M.-D., and M. J. Suarez, 1994. An efficient thermal infrared radiation parameterization for use in general circulation models. NASA Tech. Memo. 104606, 3, 85pp.
Collins, W.D. et al., 2004. Description of the NCAR Community Atmosphere Model (CAM 3.0), NCAR Technical Note, NCAR/TN-464+STR, 226pp.
Dudhia, J., S.-Y. Hong, and K.-S. Lim, 2008: A new method for representing mixed-phase particle fall speeds in bulk microphysics parameterizations. J. Met. Soc. Japan, in press.
Dudhia, J., 1989. Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46, 3077–3107.
Dyer, A. J., and B. B. Hicks, 1970: Flux-gradient relationships in the constant flux layer, Quart.J. Roy. Meteor. Soc., 96, 715–721.
Ecuador inmediato. 2008. SENACYT. Plataforma estratosférica de gran altitud pone a Ecuador en el límite de la ciencia. Disponible en línea:
diato_noticias—83052>
Fels, S. B. and M. D. Schwarzkopf, 1975. The Simplified Exchange Approximation: A New Method for Radiative Transfer Calculations, J. Atmos. Sci., 32, 1475–1488.
García-Moya, J. 2004. Los modelos numéricos de predicción del tiempo. ACAM,Tethys. No. 2. Haltiner, G. J., and R. T. Williams, 1980: Numerical prediction and dynamic meteorology.
John Wiley & Sons, Inc., 477pp.
Hennon, C., C. Marzban, J.S Hobgood. 2004. Improving Tropical Cyclogenesis Statistical Model Forecasts through the Application of a Neural Network Classifier. UCAR.
Hong, S.-Y., and Y. Noh, and J. Dudhia. 2006. A new vertical diffusion package with an explicit treatment of entrainment processes. Mon.Wea. Rev., 134, 2318–2341.
Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A Revised Approach to Ice Microphysical Processes for the Bulk Parameterization of Clouds and Precipitation, Mon. Wea. Rev., 132,
Janjic, Z. I., 1990: The step-mountain coordinate: physical package, Mon. Wea. Rev., 118, 1429–1443.
Janjic, Z. I., 1994: The step-mountain eta coordinate model: further developments of the convection, viscous sublayer and turbulence closure schemes, Mon.Wea. Rev., 122, 927–945.
Janjic, Z. I., 1996: The surface layer in the NCEP Eta Model, Eleventh Conference on Numerical Weather Prediction, Norfolk, VA, 19–23 August; Amer. Meteor. Soc., Boston, MA, 354–355.
Janjic, Z. I., 2000: Comments on ”Development and Evaluation of a Convection Scheme for Use in Climate Models”, J. Atmos. Sci., 57, p. 3686.
Janjic, Z. I., 2002: Nonsingular Implementation of the Mellor–
Kain, J. S., and J. M. Fritsch, 1990: A one-dimensional entraining/ detraining plume model and its application in convective parameterization, J. Atmos. Sci., 47, 2784–2802.
Kain, J. S., and J. M. Fritsch, 1993: Convective parameterization for mesoscale models:The Kain-Fritcsh scheme, The representation of cumulus convection in numerical models, K. A.
Kessler, E., 1969: On the distribution and continuity of water substance in atmospheric circulation, Meteor. Monogr., 32,Amer. Meteor. Soc., 84 pp.
Emanuel and D.J. Raymond, Eds., Amer. Meteor. Soc., 246 pp. Kain, J. S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181.
Lacis, A. A., and J. E. Hansen, 1974. A parameterization for the absorption of solar radiation in the earth’s atmosphere. J.Atmos. Sci., 31, 118–133.
José A. García-Moya Zapata, Los modelos numéricos de predicción del tiempo,Asociación Catalana de Meteorología, Thetys, No. 2, 2006.
Laprise R., 1992: The Euler Equations of motion with hydrostatic pressure as independent variable, Mon.Wea. Rev., 120, 197–207.
Lin,Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 1065–1092.
Malvesada, M.L, B. Gomez, E Penabad, G. Miguez, C. Balseiro,V. Perez-Muñuzuri. 2006. Resultados Preliminares de la Validación de WRF en Galicia. GFNL-USC. Meteogalicia.
Mlawer, E. J., S. J.Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997. Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave.J. Geophys. Res., 102 (D14), 16663–16682.
Ooyama K. V., 1990: A thermodynamic foundation for modeling the moist atmosphere, J.Atmos. Sci., 47, 2580–2593.
Paulson, C.A., 1970: The mathematical representation of wind speed and temperature profiles in the unstable atmospheric surface layer. J. Appl. Meteor., 9, 857–861.
Rutledge, S.A., and P.V. Hobbs, 1984: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. XII: A diagnostic modeling study of precipitation development in narrow cloud-frontal rainbands. J. Atmos. Sci., 20, 2949–2972.
Schwarzkopf, M. D., and S. B. Fels, 1991. The simplified exchange method revisited — An accurate, rapid method for computation of infrared cooling rates and fluxes. J. Geophys. Res., 96 (D5), 9075–9096.
Schaefer, J. 1990. The Critical Success Index as an Indicator of Warning Skill, AMS Journals On line.Vol.5(4). Pp. 570-575.
Serrano, S., E. Palacios, P. Núñez, J. Araujo. 2009. El Modelamiento científico en la UPS: una alternativa en investigación, UNIVERSITAS,AñoVI,No.10
Serrano, S., E. Palacios, P. Núñez, M. Zambrano y C.Terán. 2009. Descripción de las mejores condiciones ambientales para el prototipo PGA: el modelo atmosférico. Boletín PGA.
Skamarock,W., J. Klemp, J. Dudhia, D. Gill, D. Barker, M. Duda. X. Huang, W. Wang y J. Powers. 2008. A description of the advanced Research WRF Version 3. NCAR Technical Note.NCAR/TN-475+SRT. Boulder. USA. 113pp.
Tao, W.-K., J. Simpson, and M. McCumber 1989: An ice-water saturation adjustment, Mon. Wea. Rev., 117, 231–235.
Webb, E. K., 1970: Profile relationships: The log-linear range, and extension to strong stability, Quart. J. Roy. Meteor. Soc., 96, 67–90.
Wicker, L. J., and R. B.Wilhelmson, 1995: Simulation and analysis of tornado development and decay within a three-dimensional supercell thunderstorm. J. Atmos. Sci., 52, 2675–2703.
Zhang, D.-L., and R.A. Anthes, 1982: A high-resolu-tion model of the planetary boundary layer–sensitivity tests and comparisons with SESAME–79 data. J. Appl. Meteor., 21, 1594–1609.
Betts, A. K., 1986: A new convective adjustment scheme. Part I: Observational and theoretical basis. Quart. J. Roy. Meteor. Soc., 112, 677–691.
Betts,A.K.,andM.J.Miller,1986.Anewconvective adjustment scheme. Part II: Single column tests using GATE wave, BOMEX, and arctic air-mass data sets. Quart. J. Roy. Meteor. Soc.112, 693–709.
Chen, S.-H., and W.-Y. Sun, 2002. A one-dimensional time dependent cloud model. J. Meteor.Soc. Japan, 80, 99–118.
Chou M.-D., and M. J. Suarez, 1994. An efficient thermal infrared radiation parameterization for use in general circulation models. NASA Tech. Memo. 104606, 3, 85pp.
Collins, W.D. et al., 2004. Description of the NCAR Community Atmosphere Model (CAM 3.0), NCAR Technical Note, NCAR/TN-464+STR, 226pp.
Dudhia, J., S.-Y. Hong, and K.-S. Lim, 2008: A new method for representing mixed-phase particle fall speeds in bulk microphysics parameterizations. J. Met. Soc. Japan, in press.
Dudhia, J., 1989. Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46, 3077–3107.
Dyer, A. J., and B. B. Hicks, 1970: Flux-gradient relationships in the constant flux layer, Quart.J. Roy. Meteor. Soc., 96, 715–721.
Ecuador inmediato. 2008. SENACYT. Plataforma estratosférica de gran altitud pone a Ecuador en el límite de la ciencia. Disponible en línea:
Fels, S. B. and M. D. Schwarzkopf, 1975. The Simplified Exchange Approximation: A New Method for Radiative Transfer Calculations, J. Atmos. Sci., 32, 1475–1488.
García-Moya, J. 2004. Los modelos numéricos de predicción del tiempo. ACAM,Tethys. No. 2. Haltiner, G. J., and R. T. Williams, 1980: Numerical prediction and dynamic meteorology.
John Wiley & Sons, Inc., 477pp.
Hennon, C., C. Marzban, J.S Hobgood. 2004. Improving Tropical Cyclogenesis Statistical Model Forecasts through the Application of a Neural Network Classifier. UCAR.
Hong, S.-Y., and Y. Noh, and J. Dudhia. 2006. A new vertical diffusion package with an explicit treatment of entrainment processes. Mon.Wea. Rev., 134, 2318–2341.
Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A Revised Approach to Ice Microphysical Processes for the Bulk Parameterization of Clouds and Precipitation, Mon. Wea. Rev., 132,
Janjic, Z. I., 1990: The step-mountain coordinate: physical package, Mon. Wea. Rev., 118, 1429–1443.
Janjic, Z. I., 1994: The step-mountain eta coordinate model: further developments of the convection, viscous sublayer and turbulence closure schemes, Mon.Wea. Rev., 122, 927–945.
Janjic, Z. I., 1996: The surface layer in the NCEP Eta Model, Eleventh Conference on Numerical Weather Prediction, Norfolk, VA, 19–23 August; Amer. Meteor. Soc., Boston, MA, 354–355.
Janjic, Z. I., 2000: Comments on ”Development and Evaluation of a Convection Scheme for Use in Climate Models”, J. Atmos. Sci., 57, p. 3686.
Janjic, Z. I., 2002: Nonsingular Implementation of the Mellor–
Kain, J. S., and J. M. Fritsch, 1990: A one-dimensional entraining/ detraining plume model and its application in convective parameterization, J. Atmos. Sci., 47, 2784–2802.
Kain, J. S., and J. M. Fritsch, 1993: Convective parameterization for mesoscale models:The Kain-Fritcsh scheme, The representation of cumulus convection in numerical models, K. A.
Kessler, E., 1969: On the distribution and continuity of water substance in atmospheric circulation, Meteor. Monogr., 32,Amer. Meteor. Soc., 84 pp.
Emanuel and D.J. Raymond, Eds., Amer. Meteor. Soc., 246 pp. Kain, J. S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181.
Lacis, A. A., and J. E. Hansen, 1974. A parameterization for the absorption of solar radiation in the earth’s atmosphere. J.Atmos. Sci., 31, 118–133.
José A. García-Moya Zapata, Los modelos numéricos de predicción del tiempo,Asociación Catalana de Meteorología, Thetys, No. 2, 2006.
Laprise R., 1992: The Euler Equations of motion with hydrostatic pressure as independent variable, Mon.Wea. Rev., 120, 197–207.
Lin,Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 1065–1092.
Malvesada, M.L, B. Gomez, E Penabad, G. Miguez, C. Balseiro,V. Perez-Muñuzuri. 2006. Resultados Preliminares de la Validación de WRF en Galicia. GFNL-USC. Meteogalicia.
Mlawer, E. J., S. J.Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997. Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave.J. Geophys. Res., 102 (D14), 16663–16682.
Ooyama K. V., 1990: A thermodynamic foundation for modeling the moist atmosphere, J.Atmos. Sci., 47, 2580–2593.
Paulson, C.A., 1970: The mathematical representation of wind speed and temperature profiles in the unstable atmospheric surface layer. J. Appl. Meteor., 9, 857–861.
Rutledge, S.A., and P.V. Hobbs, 1984: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. XII: A diagnostic modeling study of precipitation development in narrow cloud-frontal rainbands. J. Atmos. Sci., 20, 2949–2972.
Schwarzkopf, M. D., and S. B. Fels, 1991. The simplified exchange method revisited — An accurate, rapid method for computation of infrared cooling rates and fluxes. J. Geophys. Res., 96 (D5), 9075–9096.
Schaefer, J. 1990. The Critical Success Index as an Indicator of Warning Skill, AMS Journals On line.Vol.5(4). Pp. 570-575.
Serrano, S., E. Palacios, P. Núñez, J. Araujo. 2009. El Modelamiento científico en la UPS: una alternativa en investigación, UNIVERSITAS,AñoVI,No.10
Serrano, S., E. Palacios, P. Núñez, M. Zambrano y C.Terán. 2009. Descripción de las mejores condiciones ambientales para el prototipo PGA: el modelo atmosférico. Boletín PGA.
Skamarock,W., J. Klemp, J. Dudhia, D. Gill, D. Barker, M. Duda. X. Huang, W. Wang y J. Powers. 2008. A description of the advanced Research WRF Version 3. NCAR Technical Note.NCAR/TN-475+SRT. Boulder. USA. 113pp.
Tao, W.-K., J. Simpson, and M. McCumber 1989: An ice-water saturation adjustment, Mon. Wea. Rev., 117, 231–235.
Webb, E. K., 1970: Profile relationships: The log-linear range, and extension to strong stability, Quart. J. Roy. Meteor. Soc., 96, 67–90.
Wicker, L. J., and R. B.Wilhelmson, 1995: Simulation and analysis of tornado development and decay within a three-dimensional supercell thunderstorm. J. Atmos. Sci., 52, 2675–2703.
Zhang, D.-L., and R.A. Anthes, 1982: A high-resolu-tion model of the planetary boundary layer–sensitivity tests and comparisons with SESAME–79 data. J. Appl. Meteor., 21, 1594–1609.