Patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.

Ilustraciones, mapas

Autores:
Bonilla Ovallos, Carlos Andrés
Tipo de recurso:
Fecha de publicación:
2020
Institución:
Universidad Nacional de Colombia
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Universidad Nacional de Colombia
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Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/79704
https://repositorio.unal.edu.co/
Palabra clave:
550 - Ciencias de la tierra::551 - Geología, hidrología, meteorología
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
Precipitación atmosférica
Retrotrayectorias
Nubes
Patrones anómalos de circulación
Delimitación de nubes
Back-trajectories
Atmospheric patterns
Extreme rainfall events
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License
Atribución-NoComercial-SinDerivadas 4.0 Internacional
id UNACIONAL2_7d30bdf9cdb2a905b6d92432700f15b2
oai_identifier_str oai:repositorio.unal.edu.co:unal/79704
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.
dc.title.translated.eng.fl_str_mv Atmospheric patterns leading to extreme daily precipitation events in Antioquia.
title Patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.
spellingShingle Patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.
550 - Ciencias de la tierra::551 - Geología, hidrología, meteorología
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
Precipitación atmosférica
Retrotrayectorias
Nubes
Patrones anómalos de circulación
Delimitación de nubes
Back-trajectories
Atmospheric patterns
Extreme rainfall events
title_short Patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.
title_full Patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.
title_fullStr Patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.
title_full_unstemmed Patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.
title_sort Patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.
dc.creator.fl_str_mv Bonilla Ovallos, Carlos Andrés
dc.contributor.advisor.none.fl_str_mv Hoyos Ortiz, Carlos David
dc.contributor.author.none.fl_str_mv Bonilla Ovallos, Carlos Andrés
dc.subject.ddc.spa.fl_str_mv 550 - Ciencias de la tierra::551 - Geología, hidrología, meteorología
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
topic 550 - Ciencias de la tierra::551 - Geología, hidrología, meteorología
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
Precipitación atmosférica
Retrotrayectorias
Nubes
Patrones anómalos de circulación
Delimitación de nubes
Back-trajectories
Atmospheric patterns
Extreme rainfall events
dc.subject.lemb.none.fl_str_mv Precipitación atmosférica
dc.subject.proposal.spa.fl_str_mv Retrotrayectorias
Nubes
Patrones anómalos de circulación
Delimitación de nubes
dc.subject.proposal.eng.fl_str_mv Back-trajectories
Atmospheric patterns
Extreme rainfall events
description Ilustraciones, mapas
publishDate 2020
dc.date.issued.none.fl_str_mv 2020
dc.date.accessioned.none.fl_str_mv 2021-06-24T15:48:56Z
dc.date.available.none.fl_str_mv 2021-06-24T15:48:56Z
dc.type.spa.fl_str_mv Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/TM
status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/79704
dc.identifier.instname.spa.fl_str_mv Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv https://repositorio.unal.edu.co/
url https://repositorio.unal.edu.co/handle/unal/79704
https://repositorio.unal.edu.co/
identifier_str_mv Universidad Nacional de Colombia
Repositorio Institucional Universidad Nacional de Colombia
dc.relation.references.spa.fl_str_mv Álvarez-Villa, O. D., Vélez, J. I., y Poveda, G. (2010). Improved long-term mean annual rainfall fields for Colombia. International Journal of Climatology, 31(14):2194–2212.
Amador, J. (1998). A climatic feature of the tropical americas: The trade wind easterly jet. Top Meteor Oceanogr.
Arias, P. A., Fu, R., Hoyos, C. D., Li, W., y Zhou, L. (2011). Changes in cloudiness over the Amazon rainforests during the last two decades: Diagnostic and potential causes. Climate Dynamics,37(5):1151–1164.
Aristizabal, E. y Gómez, J. (2007). Inventario de emergencias y desastres en el Valle de Aburrá. Gestión y Ambiente, 10(2):17–30.
Avila, , Guerrero, F. C., Escobar, Y. C., y Justino, F. (2019). Recent precipitation trends and floods in the colombian andes. Water, 11.
Bedoya-Soto, J. M., Aristizábal, E., Carmona, A. M., y Poveda, G. (2019). Seasonal shift of the diurnal cycle of rainfall over medellin’s valley, central andes of colombia (1998–2005). Frontiers in Earth Science, 7:92.
Bocheva, L., Gospodinov, I., Simeonov, P., y Marinova, T. (2010). Climatological Analysis of the Synoptic Situations Causing Torrential Precipitation Events in Bulgaria over the Period 1961–2007, pages 97–108.
Bombardi, R. J. y Carvalho, L. M. V. (2017). Práticas Simples em Análises Climatológicas: Uma Revisão Simple Practices in Climatological Analyses: A Review. Revista Brasileira de Meteorologia, 32(3):311–320.
Cai, W., McPhaden, M. J., Grimm, A. M., Rodrigues, R. R., Taschetto, A. S., Garreaud, R. D., Dewitte, B., Poveda, G., Ham, Y.-G., Santoso, A., Ng, B., Anderson, W., Wang, G., Geng, T., Jo, H.-S., Marengo, J. A., Alves, L. M., Osman, M., Li, S., Wu, L., Karamperidou, C., Takahashi, K., y Vera, C. (2020). Climate impacts of the El Niño–Southern Oscillation on South America. Nature Reviews Earth & Environment, 1(4):215–231.
Cavalcanti, I. (2012). Large scale and synoptic features associated with extreme precipitation over south america: A review and case studies for the first decade of the 21st century. Atmospheric Research, 118:27–40.
Cazes-Boezio, G., Robertson, A. W., y Mechoso, C. R. (2003). Seasonal dependence of enso teleconnections over south america and relationships with precipitation in uruguay. Journal of Climate, 16(8):1159 – 1176.
Ceccherini, G., Ameztoy, I., Hernández, C. P. R., y Moreno, C. C. (2015). High-resolution precipitation datasets in south america and west africa based on satellite-derived rainfall, enhanced vegetation index and digital elevation model. Remote Sensing, 7(5):6454–6488.
Chen, F., Sheng, S., Bao, Z., Wen, H., Hua, L., Paul, N., y Fu, Y. (2018). Precipitation Clouds Delineation Scheme in Tropical Cyclones and Its Validation Using Precipitation and Cloud Parameter Datasets from TRMM. Journal of Applied Meteorology and Climatology, 57:821–836. CIRA (2019). Day cloud phase distinction RGB.
Coelho, C. A., Uvo, C. B., y Ambrizzi, T. (2002). Exploring the impacts of the tropical Pacific SST on the precipitation patterns over South America during ENSO periods. Theoretical and Applied Climatology, 71(3-4):185–197.
Cotton, W., Bryan, G., y Heever, S. (2011). Storm and cloud dynamics. Academic Press, Burlington.
Cárdenas, S. G., Arias, P. A., y Vieira, S. C. (2017). The african easterly waves over northern south america. Proceedings, 1(5).
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C., van de Berg, L., Bid- lot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., Mcnally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., y Vitart, F. (2011). The ERA-Interim reanalysis: Configuration and perfor- mance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656):553–597.
Demšar, U., Harris, P., Brunsdon, C., Fotheringham, A. S., y McLoone, S. (2013). Principal Component Analysis on Spatial Data: An Overview. Annals of the Association of American Geographers, 103(1):106–128.
Diem, J. E. (2006). Synoptic-scale controls of summer precipitation in the southeastern United States. Journal of Climate, 19(4):613–621.
Dommenget, D. y Latif, M. (2002). A cautionary note on the interpretation of EOFs. Journal of Climate, 15(2):216–225.
Elsenheimer, C. B. y Gravelle, C. M. (2019). Introducing Lightning Threat Messaging Using the GOES-16 Day Cloud Phase Distinction RGB Composite. Weather and Forecasting, 34(5):1587-1600.
Gallucci, D., De Natale, M. P., Cimini, D., Di Paola, F., Gentile, S., Geraldi, E., Larosa, S., Nilo, S. T., Ricciardelli, E., Viggiano, M., y Romano, F. (2020). Convective initiation proxies for nowcasting precipitation severity using the MSG-SEVIRI rapid scan. Remote Sensing, 12(16).
Gao, C., Li, Y., y Chen, H. (2019). Diurnal variations of different cloud types and the relationship between the diurnal variations of clouds and precipitation in central and east China. Atmosphere, 10(6).
Gil Zapata, M., Quiceno, N., y Poveda Jaramillo, G. (1998). Efecto del ENSO y la NAO sobre el ciclo anual de la hidrología de Colombia: análisis de correlación, reanálisis de NCEP/NCAR y modelos de pronóstico. (5):41–53. Grimm, A. M. y Tedeschi, R. G. (2009). Enso and extreme rainfall events in South America. Journal of Climate, 22(7):1589 – 1609.
Grumm, R. y Hart, R. (2001). Standardized anomalies applied to significant cold season weather events: Preliminary findings. Weather and Forecasting - WEATHER FORECAST, 16:736–754.
Han, H., Lee, S., Im, J., Kim, M., Lee, M. I., Ahn, M. H., y Chung, S. R. (2015). Detection of convective initiation using Meteorological Imager onboard Communication, Ocean, and Meteorological Satellite based on machine learning approaches. Remote Sensing, 7(7):9184–9204.
Hannachi, A. (2004). A primer for EOF analysis of climate data. Reading: University of Reading, pages 1–33.
Harris, R. J., Mecikalski, J. R., Mackenzie, W. M., Durkee, P. A., y Nielsen, K. E. (2010). The definition of GOES infrared lightning initiation interest fields. Journal of Applied Meteorology and Climatology, 49(12):2527–2543.
Hart, R. E. y Grumm, R. H. (2001). Using normalized climatological anomalies to rank synoptic scale events obejectively. Monthly Weather Review, 129(9):2426–2442.
Hayatbini, N., Kong, B., Hsu, K. L., Nguyen, P., Sorooshian, S., Stephens, G., Fowlkes, C., Nemani, R., y Ganguly, S. (2019a). Conditional generative adversarial networks (cGANs) for near real-time precipitation estimation from multispectral GOES-16 satellite imageries-PERSIANN-cGAN. Remote Sensing, 11(19).
Henken, C. C., Schmeits, M. J., Deneke, H., y Roebeling, R. A. (2011). Using MSG-SEVIRI cloud physical properties and weather radar observations for the detection of Cb/TCu clouds. Journal of Applied Meteorology and Climatology, 50(7):1587–1600.
Hoyos, C. D., Ceballos, L. I., Pérez-Carrasquilla, J. S., Sepulveda, J., López-Zapata, S. M., Zuluaga, M. D., Velasquez, N., Herrera-Mejı́a, L., Hernández, O., Guzmán-Echavarrı́a, G., y Zapata, M. (2019). Meteorological conditions leading to the 2015 Salgar flash flood: Lessons for vulnerable regions in tropical complex terrain. Natural Hazards and Earth System Sciences, 19(11):2635–2665.
Hoyos, I., Dominguez, F., Cañón-Barriga, J., Martinez, A., Nieto, R., Gimeno, L., y Dirmeyer, P. (2017). Moisture origin and transport processes in colombia, northern south america. Climate Dynamics, 50.
Huffman, G., Stocker, E., Bolvin, D., Nelkin, E., y Jackson, T. (2019). GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC).
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman, K. P., Hong, Y., Stocker, E. F., y Wolff, D. B. (2007). The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8(1):38–55.
Jana, S., Rajagopalan, B., Alexander, M. A., y Ray, A. J. (2018). Understanding the dominant sources and tracks of moisture for summer rainfall in the southwest United States. Journal of Geophysical Research: Atmospheres, 123(10):4850–4870.
Jaramillo, L. (2012). Caracterización de la lluvia y eventos de precipitación durante 2003-2010 definidos por la misión para la medición de lluvias tropicales (TRMM) sobre Colombia y la Cuenca amazónica. Tesis de Maestrı́a, Universidad Nacional de Colombia.
Jaramillo, L., Poveda, G., y Mejía, J. F. (2017). Mesoscale convective systems and other precipitation features over the tropical Americas and surrounding seas as seen by TRMM. International Journal of Climatology, 37(February):380–397.
Junker, N., Grumm, R., Hart, R., Bosart, L., Bell, K., y Pereira, F. (2007). Use of normalized anomaly fields to anticipate extreme rainfall in the mountains of northern california. Weather and Forecasting, 23.
Junker, N. W., Grumm, R. H., Hart, R., Bosart, L. F., Bell, K. M., y Pereira, F. J. (2008). Use of normalized anomaly fields to anticipate extreme rainfall in the mountains of northern California. Weather and Forecasting, 23(3):336–356.
Kassambara, A. (2017). Practical guide to cluster analysis in R: unsupervised machine learning. Journal of Computational and Graphical Statistics, page 187.
Khain, A. P., Beheng, K. D., Heymsfield, A., Korolev, A., Krichak, S., Levin, Z., Pinsky, M., Phillips, V., Prabhakaran, T., Teller, A., Van den Heever, S. C., y Yano, J. I. (2015). Representation of microphysical processes in cloud-resolving models: Spectral (bin) microphysics versus bulk parameterization. Reviews of Geophysics, 53(37):247–322.
Laing, A. y Evans, J.-L. (2011). Introduction to Tropical Meteorology. The COMET program, 2nd edition.
Li, Z., Chao, Y., y McWilliams, J. C. (01 Nov. 2006). Computation of the stream function and velocity potential for limited and irregular domains. Monthly Weather Review, 134(11):3384 – 3394.
Lima, K. C., Satyamurty, P., y Fernández, J. P. R. (2010). Large-scale atmospheric conditions associated with heavy rainfall episodes in Southeast Brazil. Theoretical and Applied Climatology, 101(1):121–135.
Lindsey, D., Schmit, T. J., Jr., W. M. M., Jewitt, C. P., Gunshor, M. M., y Grasso, L. (2012). 10.35 μm: atmospheric window on the GOES-R Advanced Baseline Imager with less moisture attenuation. Journal of Applied Remote Sensing, 6(1):1–12.
Liu, Q., Li, Y., Yu, M., Chiu, L., Hao, X., Duffy, D., y Yang, C. (2019). Daytime rainy cloud detection and convective precipitation delineation based on a deep neural network method using goes-16 abi images. Remote Sensing, 11:2555.
Lorenz, E. N. (1956). Empirical Orthogonal Functions and Statistical Weather Prediction. Loriaux, J. M., Lenderink, G., y Siebesma, A. P. (01 Feb. 2017). Large-scale controls on extreme precipitation. Journal of Climate, 30(3):955 – 968.
Mapes, B. E., Warner, T. T., Xu, M., y Negri, A. J. (2003). Diurnal patterns of rainfall in northwestern South America. Part I: Observations and context. Monthly Weather Review, 131(5):799–812.
Marengo, J. A. y Espinoza, J. C. (2016). Extreme seasonal droughts and floods in amazonia: causes, trends and impacts. International Journal of Climatology, 36(3):1033–1050.
Marin, G. (2005). Análisis sinóptico y de mesoescala de los eventos hidrometeorológicos extremos que afectan las cuencas de los ríos Nare y Guatapé los cuales alimentan a los embalses el peñol y playas, respectivamente, en el oriente de Antioquia, Colombia.
Mecikalski, J. R. y Bedka, K. M. (2006). Forecasting Convective Initiation by Monitoring the Evolution of Moving Cumulus in Daytime GOES Imagery. Monthly Weather Review, 134(1):49–78.
Mecikalski, J. R., MacKenzie, Wayne M., J., Koenig, M., y Muller, S. (2010a). Cloud-Top Properties of Growing Cumulus prior to Convective Initiation as Measured by Meteosat Second Generation. Part I: Infrared Fields. Journal of Applied Meteorology and Climatology, 49(3):521–534.
Mecikalski, J. R., MacKenzie, Way ne M., J., König, M., y Muller, S. (2010b). Cloud-Top Properties of Growing Cumulus prior to Convective Initiation as Measured by Meteosat Second Generation. Part II: Use of Visible Reflectance. Journal of Applied Meteorology and Climatology, 49(12):2544–2558.
Mejía, J. F. y Poveda, G. (2005). Ambientes Atmosféricos de Sistemas Convectivos de Mesoescala sobre Colombia durante 1998 según la misión TRMM y el re-análisis NCEP/NCAR. Revista de la academia colombiana de ciencias exactas físicas y naturales, 29:495–514.
Montoya, G. y Lemus, R. (2005). Sistemas pluviogenéticos en Colombia: Influencia de frentes fríos del Hemisferio Norte. Meteorología Colombiana, 9:75–81.
Moreno, H., Vélez, M., Montoya, J., y Rhenals, R. (2006). Tierra En Antioquia : Análisis De Su Ocurrencia En Las Escalas Interanual ,. Revista EIA, 5:59–69.
Murtagh, F. y Legendre, P. (2014). Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion? Journal of Classification, 31(1):274–295. Nauss, T. y Kokhanovsky, A. A. (2006). Discriminating raining from non-raining clouds at midlatitudes using multispectral satellite data. Atmospheric Chemistry and Physics, 6(12):5031–5036.
O’Gorman, P. A. (2015). Precipitation Extremes Under Climate Change. Current Climate Change Reports, 1(2):49–59.
Pavolonis, M. J., Heidinger, A. K., y Uttal, T. (2005). Journal of Applied Meteorology, (6).
Peterson, M., Rudlosky, S., y Zhang, D. (2020). Thunderstorm cloud-type classification from space-based lightning imagers. Monthly Weather Review, 148(5):1891–1898.
Poveda, G. (2004). La hidroclimatología de Colombia: una síntesis desde la escala inter-decadal hasta la escala diurna. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 28:202–222.
Poveda, G., Álvarez, D. M., y Rueda, Ó. A. (2010). Hydro-climatic variability over the Andes of Colombia associated with ENSO: A review of climatic processes and their impact on one of the Earth’s most important biodiversity hotspots. Climate Dynamics, 36(11-12):2233–2249.
Poveda, G., Jaramillo, L., y Vallejo, L. F. (2014). Seasonal precipitation patterns along pathways of South American low-level jets and aerial rivers. Water Resources Research, 50(1):98–118.
Poveda, G. y Mesa, O. (1999). La corriente del chorro superficial del oeste (“del Chocó”) y otras dos corrientes de chorro en Colombia: climatología y variabilidad durante las fases del ENSO.
Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 23:517–528. Poveda, G., Mesa, O., AGUDELO, P., ÁLVAREZ, J., Arias, P., Moreno, H., Salazar Velásquez, L., Toro, V., Vieira, S., Jaramillo, A., y GUZMÁN, O. (2002). Influencia del enso,oscilación madden-julian, ondas del este, huracanes y fases de la luna en el ciclo diurno de precipitación en los andes tropicales de colombia de colombia. volume 5, pages 23–30.
Poveda, G. y Mesa, O. J. (2000). On the existence of lloró (the rainiest lovality on earth): Enhanced ocean-land-atmosphere interaction by a low-level jet. Geophysical Research Letters, 27:1675–1678.
Poveda, G., Mesa, O. J., Salazar, L. F., Arias, P. A., Moreno, H. A., Vieira, S. C., Agudelo, P. A., Toro, V. G., y Alvarez, J. F. (01 Jan. 2005). The diurnal cycle of precipitation in the tropical andes of colombia. Monthly Weather Review, 133(1):228 – 240.
Poveda, G., Waylen, P. R., y Pulwarty, R. S. (2006). Annual and inter-annual variability of the present climate in northern South America and southern Mesoamerica. Palaeogeography, Palaeoclimatology, Palaeoecology, 234(1):3–27.
Robert, M. (1967). A numerical procedure for computing fields of stream function and velocity potential.
Roberts, R. D. y Rutledge, S. (2003). Nowcasting storm initiation and growth using GOES-8 and WSR-88D data. Weather and Forecasting, 18(4):562–584.
Rodrı́guez-Morata, C., Ballesteros-Canovas, J. A., Rohrer, M., Espinoza, J. C., Beniston, M., y Stoffel, M. (2018). Linking atmospheric circulation patterns with hydro-geomorphic disasters in peru. International Journal of Climatology, 38(8):3388–3404.
Rojo, J. y Mesa, O. (2020a). On the general circulation of the atmosphere around colombia. Revista de la Academia Colombiana de Ciencias Exactas Físicas y Naturales, 44:857.
Rojo, J. y Mesa, O. (2020b). A simple conceptual model for the heat induced circulation over northern south america and meso-america. Atmosphere, 11.
Salas, H. D., Poveda, G., Mesa, J., y Marwan, N. (2020). Generalized synchronization between enso and hydrological variables in colombia: A recurrence quantification approach. Frontiers in Applied Mathematics and Statistics, 6:3.
Santos, E. B., Lucio, P. S., y Santos e Silva, C. M. (2017). Synoptic patterns of atmospheric circulation associated with intense precipitation events over the Brazilian Amazon. Theoretical and Applied Climatology, 128(1-2):343–358.
Schmit, T., Lindstrom, S., Gerth, J., y Gunshor, M. (2018). Applications of the 16 spectral bands on the advanced baseline imager (abi). Journal of Operational Meteorology, 06:33–46.
Schmit, T. J., Griffith, P., Gunshor, M. M., Daniels, J. M., Goodman, S. J., y Lebair, W. J. (2017). A closer look at the ABI on the GOES-R series. Bull. Amer. Meteor. Soc., (April):681–698.
Seluchi, M. E. y Chou, S. C. (2009). Synoptic patterns associated with landslide events in the Serra do Mar, Brazil. Theoretical and Applied Climatology, 98(1-2):67–77.
Sepúlveda Berrío, J. (2015). Estimación cuantitativa de precipitación a partir de la información de Radar Meteorológico del área Metropolitana del Valle de Aburrá.
Serna, L. M., Arias, P. A., y Vieira, S. C. (2018). Las corrientes superficiales de chorro del Chocó y el Caribe durante los eventos de El Niño y El Niño Modoki. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 42(165):410.
Shimizu, M. H. y Ambrizzi, T. (2016). MJO influence on ENSO effects in precipitation and temperature over South America. Theoretical and Applied Climatology, 124(1-2):291–301.
Shimizu, M. H., Ambrizzi, T., y Liebmann, B. (2017). Extreme precipitation events and their relationship with enso and mjo phases over northern south america. International Journal of Climatology, 37(6):2977–2989. Siewert, C. W., Koenig, M., y Mecikalski, J. R. (2010). Application of Meteosat second generation data towards improving the nowcasting of convective initiation. Meteorological Applications, 17(4):442–451.
Smith, R. K. (2015). Lectures on Tropical Meteorology. En línea: https://www.meteo.physik. uni-muenchen.de/~roger/Lectures/TropicalMetweb/Tropical_meteorology.pdf.
Smyth, C. G. y Royle, S. A. (2000). Urban landslide hazards: incidence and causative factors in niterói, rio de janeiro state, brazil. Applied Geography, 20(2):95–118.
So, D. y Shin, D.-B. (2018). Classification of precipitating clouds using satellite infrared observations and its implications for rainfall estimation. Quarterly Journal of the Royal Meteorological Society, 144(S1):133–144.
Steiner, M., Houze, R. A., y Yuter, S. E. (1995). Climatological Characterization of Three Dimensional Storm Structure from Operational Radar and Rain Gauge Data. Journal of Applied Meteorology and Climatology, 34(9):1978–2007.
Steinley, D. (2006). K-means clustering: A half-century synthesis. British Journal of Mathematical and Statistical Psychology, 59(1):1–34.
Ta, S., Kouadio, K. Y., Ali, K. E., Toualy, E., Aman, A., y Yoroba, F. (2016). West Africa Extreme Rainfall Events and Large-Scale Ocean Surface and Atmospheric Conditions in the Tropical Atlantic. Advances in Meteorology, 2016.
Tedeschi, R. G., Cavalcanti, I. F. A., y Grimm, A. M. (2013). Influences of two types of enso on south american precipitation. International Journal of Climatology, 33(6):1382–1400.
Thies, B., Nauss, T., y Bendix, J. (2008). Precipitation process and rainfall intensity differentiation using meteosat second generation spinning enhanced visible and infrared imager data. Journal of Geophysical Research, 113.
Torres-Pineda, C. E. y Pabón-Caicedo, J. D. (2017). Variabilidad intraestacional de la precipitación en Colombia y su relación con la oscilación de Madden-Julian. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 41(158):79.
UCAR (2014). El ABI del GOES-R: la próxima generación de imágenes satelitales.
Ungerovich, M. y Barreiro, M. (2019). Dynamics of extreme rainfall events in summer in southern Uruguay. International Journal of Climatology, 39(8):3655–3667.
Urán, J. D. (2015). Cambios en los valores extremos de variables climáticas en Colombia asociados al cambio climático. Tesis de Doctorado, Universidad Nacional de Colombia.
Velasquez, N. (2017). Evaluation of existing relations between convective systems and extreme events in tropical catchments of the Andean region. Tesis de Doctorado, Universidad Nacional de Colombia sede Medellín. Vergés-Llahí, J. (2005). Color constancy and image segmentation techniques for applications to mobile robotics. Tesis de Doctorado, Universitat Politècnica de Catalunya.
Wang, C. (2007). Variability of the Caribbean Low-Level Jet and its relations to climate. Climate Dynamics, 29(4):411–422.
Ward, J. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58(301):236–244.
Zuluaga, M. y Poveda, G. (2004). Diagnóstico de sistemas convectivos de mesoescala sobre Colombia y el océano Pacífico Oriental durante 1998-2002. Avances en Recursos Hidráulicos, (11):145–160.
Zuluaga, M. D. y Houze, R. A. (01 Jan. 2015). Extreme convection of the near-equatorial americas, africa, and adjoining oceans as seen by trmm. Monthly Weather Review, 143(1):298 – 316.
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dc.coverage.region.none.fl_str_mv Antioquia (Colombia)
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv Medellín - Minas - Maestría en Ingeniería - Recursos Hidráulicos
dc.publisher.department.spa.fl_str_mv Departamento de Geociencias y Medo Ambiente
dc.publisher.faculty.spa.fl_str_mv Facultad de Minas
dc.publisher.place.spa.fl_str_mv Medellín, Colombia
dc.publisher.branch.spa.fl_str_mv Universidad Nacional de Colombia - Sede Medellín
institution Universidad Nacional de Colombia
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spelling Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Hoyos Ortiz, Carlos David27686cec87756851bf3b2f6ce68e0839600Bonilla Ovallos, Carlos Andrés8f4db9fbf95d99a18fada756d7c8b9b92021-06-24T15:48:56Z2021-06-24T15:48:56Z2020https://repositorio.unal.edu.co/handle/unal/79704Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/Ilustraciones, mapasCon el propósito de fortalecer las capacidades de monitoreo y de pronóstico meteorológico en Antioquia, y con ello las capacidades de gestión de riesgo en este departamento colombiano, se definió como objetivo principal del presente trabajo, la identificación y el análisis de los patrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria. En primer lugar y con base en un ejercicio de regionalización, se identificaron 2 regiones que comprenden la mayor parte del territorio antioqueño, y en las cuales, el comportamiento de la precipitación es diferente. Para estas subregiones del departamento se identificaron eventos extremos de precipitación diaria y se caracterizaron los ambientes atmosféricos asociados a su génesis a través de dos aproximaciones metodológicas: un análisis de retrotrayectorias y de humedad, y un análisis de anomalı́as de circulación en el que se evaluaron, para distintos niveles de presión, los campos de altura geopotencial, vientos horizontales, humedad específica y potencial de velocidad. Adicionalmente, y con el fin de complementar lo antes expuesto mediante la mejora de las capacidades de monitoreo y diagnóstico meteorológico en tiempo real, se exploraron las potencialidades de la información del generador avanzado de imágenes (ABI) del satélite GOES-16 en lo que respecta a la delimitación de las nubes que precipitan y la alerta temprana de precipitaciones convectivas. Los resultados del análisis de retrotrayectorias sugieren que los eventos extremos de precipitación diaria de la mayoría de los meses del año están relacionados con un ambiente de alta convergencia de humedad, cuyos mayores aportes provienen del Pacífico y del Caribe. En cuanto al análisis de compuestos de anomalı́as, los resultados evidencian que pese a que existe una alta variabilidad en cuanto a los patrones generales de anomalı́as analizados, existen elementos comunes que pueden usarse como indicadores del favorecimiento de las condiciones para la ocurrencia de tales eventos extremos. Dentro de estos factores comunes, se destacan: el desarrollo de anomalı́as negativas de altura geopotencial sobre el nor-occidente de Sur América, que inducen el giro ciclónico de los vientos alisios del noreste; la existencia de anomalı́as positivas de viento zonal sobre el Pacifico y de anomalı́as negativas de viento zonal y meridional sobre el Caribe, que favorecen el flujo húmedo hacia la región; la presencia de anomalı́as positivas de humedad específica sobre el Caribe, especialmente durante los meses de DEF; y la configuración de un sistema acoplado de convergencia/divergencia en bajo/alto nivel en el norte de Sur América, el cual favorece la convección profunda sobre la región. Por otro lado, los resultados demuestran que el uso de la información del sensor ABI, a bordo del satélite GOES-16, es una excelente opción para el mejoramiento de las capacidades de gestión de riesgo de desastres en Antioquia, en cuanto permite capturar eficientemente los procesos más importantes dentro del crecimiento de cúmulos, permitiendo ası́ advertir tempranamente la iniciación convectiva; y porque permiten, con base en las propiedades de las nubes, delimitar aceptablemente bien las nubes que precipitan y ası́ constituir una herramienta útil para complementar las estrategias de monitoreo regional. (tomado de la fuente)Aiming to strengthen the monitoring and meteorological forecasting capacities in Antioquia, identifying and characterizing the atmospheric patterns related to the occurrence of daily extreme rainfall events was defined as the main objective of this work. Firstly, using clustering analysis were identified two sub-regions in Antioquia with different precipitation patterns. For these sub-regions of the department, daily extreme rainfall events were identified, and the atmospheric states related with their genesis and development are characterized through two methodological approaches: (1) a back trajectory analysis together with specific humidity, and (2) a composites analysis based on standardized anomalies of geopotential height, horizontal winds, specific humidity and, velocity potential, at several pressure levels. To complement those mentioned above, the potential capabilities of satellite information to monitoring and diagnose weather in real-time were explored. Specifically, data from Advanced Baseline Imager (ABI, onboard of GOES-16) is evaluated regarding the precipitating clouds’ delimitation and the early warning of convective initiation features. Results from the back-trajectory analysis suggest that the extreme daily precipitation events of most months of the year are related to a high environment of humidity convergence, whose significant contributions coming from the Pacific Ocean and the Caribbean Sea. According to the analysis of composite anomalies, there are common elements that can be used as indicators of favoring conditions for the occurrence of such extreme events in the department, though the patterns of anomalies analyzed show high variability.Among these common factors, the following highlighted: the development of negative anomalies of geopotential height over the north-west of South America, which induces the cyclonic turn of the northeast trade winds; the existence of positive zonal wind anomalies over the Pacific; the existence of negative zonal and southerly wind anomalies over the Caribbean; the presence of positive specific humidity anomalies over the Caribbean; and the existence of a coupled system of low-level convergence and height divergence over northern South America, which favors deep convection over the region. On the other hand, the results also show that the ABI data is an excellent tool to capture the more essential processes within cumulus growth (allowing early warning of convective initiation), efficiently delimiting precipitation clouds and, complementing regional monitoring strategies (Tomado de la fuente)MaestríaMagíster en Ingeniería - Recursos HidráulicosMeteorología tropical134 páginasapplication/pdfUniversidad Nacional de ColombiaMedellín - Minas - Maestría en Ingeniería - Recursos HidráulicosDepartamento de Geociencias y Medo AmbienteFacultad de MinasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín550 - Ciencias de la tierra::551 - Geología, hidrología, meteorología620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulicaPrecipitación atmosféricaRetrotrayectoriasNubesPatrones anómalos de circulaciónDelimitación de nubesBack-trajectoriesAtmospheric patternsExtreme rainfall eventsPatrones atmosféricos asociados a la ocurrencia de eventos extremos de precipitación diaria en Antioquia.Atmospheric patterns leading to extreme daily precipitation events in Antioquia.Trabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAntioquia (Colombia)Álvarez-Villa, O. D., Vélez, J. I., y Poveda, G. (2010). Improved long-term mean annual rainfall fields for Colombia. International Journal of Climatology, 31(14):2194–2212.Amador, J. (1998). A climatic feature of the tropical americas: The trade wind easterly jet. Top Meteor Oceanogr.Arias, P. A., Fu, R., Hoyos, C. D., Li, W., y Zhou, L. (2011). Changes in cloudiness over the Amazon rainforests during the last two decades: Diagnostic and potential causes. Climate Dynamics,37(5):1151–1164.Aristizabal, E. y Gómez, J. (2007). Inventario de emergencias y desastres en el Valle de Aburrá. Gestión y Ambiente, 10(2):17–30.Avila, , Guerrero, F. C., Escobar, Y. C., y Justino, F. (2019). Recent precipitation trends and floods in the colombian andes. Water, 11.Bedoya-Soto, J. M., Aristizábal, E., Carmona, A. M., y Poveda, G. (2019). Seasonal shift of the diurnal cycle of rainfall over medellin’s valley, central andes of colombia (1998–2005). Frontiers in Earth Science, 7:92.Bocheva, L., Gospodinov, I., Simeonov, P., y Marinova, T. (2010). Climatological Analysis of the Synoptic Situations Causing Torrential Precipitation Events in Bulgaria over the Period 1961–2007, pages 97–108.Bombardi, R. J. y Carvalho, L. M. V. (2017). Práticas Simples em Análises Climatológicas: Uma Revisão Simple Practices in Climatological Analyses: A Review. Revista Brasileira de Meteorologia, 32(3):311–320.Cai, W., McPhaden, M. J., Grimm, A. M., Rodrigues, R. R., Taschetto, A. S., Garreaud, R. D., Dewitte, B., Poveda, G., Ham, Y.-G., Santoso, A., Ng, B., Anderson, W., Wang, G., Geng, T., Jo, H.-S., Marengo, J. A., Alves, L. M., Osman, M., Li, S., Wu, L., Karamperidou, C., Takahashi, K., y Vera, C. (2020). Climate impacts of the El Niño–Southern Oscillation on South America. Nature Reviews Earth & Environment, 1(4):215–231.Cavalcanti, I. (2012). Large scale and synoptic features associated with extreme precipitation over south america: A review and case studies for the first decade of the 21st century. Atmospheric Research, 118:27–40.Cazes-Boezio, G., Robertson, A. W., y Mechoso, C. R. (2003). Seasonal dependence of enso teleconnections over south america and relationships with precipitation in uruguay. Journal of Climate, 16(8):1159 – 1176.Ceccherini, G., Ameztoy, I., Hernández, C. P. R., y Moreno, C. C. (2015). High-resolution precipitation datasets in south america and west africa based on satellite-derived rainfall, enhanced vegetation index and digital elevation model. Remote Sensing, 7(5):6454–6488.Chen, F., Sheng, S., Bao, Z., Wen, H., Hua, L., Paul, N., y Fu, Y. (2018). Precipitation Clouds Delineation Scheme in Tropical Cyclones and Its Validation Using Precipitation and Cloud Parameter Datasets from TRMM. Journal of Applied Meteorology and Climatology, 57:821–836. CIRA (2019). Day cloud phase distinction RGB.Coelho, C. A., Uvo, C. B., y Ambrizzi, T. (2002). Exploring the impacts of the tropical Pacific SST on the precipitation patterns over South America during ENSO periods. Theoretical and Applied Climatology, 71(3-4):185–197.Cotton, W., Bryan, G., y Heever, S. (2011). Storm and cloud dynamics. Academic Press, Burlington.Cárdenas, S. G., Arias, P. A., y Vieira, S. C. (2017). The african easterly waves over northern south america. Proceedings, 1(5).Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C., van de Berg, L., Bid- lot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., Mcnally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., y Vitart, F. (2011). The ERA-Interim reanalysis: Configuration and perfor- mance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656):553–597.Demšar, U., Harris, P., Brunsdon, C., Fotheringham, A. S., y McLoone, S. (2013). Principal Component Analysis on Spatial Data: An Overview. Annals of the Association of American Geographers, 103(1):106–128.Diem, J. E. (2006). Synoptic-scale controls of summer precipitation in the southeastern United States. Journal of Climate, 19(4):613–621.Dommenget, D. y Latif, M. (2002). A cautionary note on the interpretation of EOFs. Journal of Climate, 15(2):216–225.Elsenheimer, C. B. y Gravelle, C. M. (2019). Introducing Lightning Threat Messaging Using the GOES-16 Day Cloud Phase Distinction RGB Composite. Weather and Forecasting, 34(5):1587-1600.Gallucci, D., De Natale, M. P., Cimini, D., Di Paola, F., Gentile, S., Geraldi, E., Larosa, S., Nilo, S. T., Ricciardelli, E., Viggiano, M., y Romano, F. (2020). Convective initiation proxies for nowcasting precipitation severity using the MSG-SEVIRI rapid scan. Remote Sensing, 12(16).Gao, C., Li, Y., y Chen, H. (2019). Diurnal variations of different cloud types and the relationship between the diurnal variations of clouds and precipitation in central and east China. Atmosphere, 10(6).Gil Zapata, M., Quiceno, N., y Poveda Jaramillo, G. (1998). Efecto del ENSO y la NAO sobre el ciclo anual de la hidrología de Colombia: análisis de correlación, reanálisis de NCEP/NCAR y modelos de pronóstico. (5):41–53. Grimm, A. M. y Tedeschi, R. G. (2009). Enso and extreme rainfall events in South America. Journal of Climate, 22(7):1589 – 1609.Grumm, R. y Hart, R. (2001). Standardized anomalies applied to significant cold season weather events: Preliminary findings. Weather and Forecasting - WEATHER FORECAST, 16:736–754.Han, H., Lee, S., Im, J., Kim, M., Lee, M. I., Ahn, M. H., y Chung, S. R. (2015). Detection of convective initiation using Meteorological Imager onboard Communication, Ocean, and Meteorological Satellite based on machine learning approaches. Remote Sensing, 7(7):9184–9204.Hannachi, A. (2004). A primer for EOF analysis of climate data. Reading: University of Reading, pages 1–33.Harris, R. J., Mecikalski, J. R., Mackenzie, W. M., Durkee, P. A., y Nielsen, K. E. (2010). The definition of GOES infrared lightning initiation interest fields. Journal of Applied Meteorology and Climatology, 49(12):2527–2543.Hart, R. E. y Grumm, R. H. (2001). Using normalized climatological anomalies to rank synoptic scale events obejectively. Monthly Weather Review, 129(9):2426–2442.Hayatbini, N., Kong, B., Hsu, K. L., Nguyen, P., Sorooshian, S., Stephens, G., Fowlkes, C., Nemani, R., y Ganguly, S. (2019a). Conditional generative adversarial networks (cGANs) for near real-time precipitation estimation from multispectral GOES-16 satellite imageries-PERSIANN-cGAN. Remote Sensing, 11(19).Henken, C. C., Schmeits, M. J., Deneke, H., y Roebeling, R. A. (2011). Using MSG-SEVIRI cloud physical properties and weather radar observations for the detection of Cb/TCu clouds. Journal of Applied Meteorology and Climatology, 50(7):1587–1600.Hoyos, C. D., Ceballos, L. I., Pérez-Carrasquilla, J. S., Sepulveda, J., López-Zapata, S. M., Zuluaga, M. D., Velasquez, N., Herrera-Mejı́a, L., Hernández, O., Guzmán-Echavarrı́a, G., y Zapata, M. (2019). Meteorological conditions leading to the 2015 Salgar flash flood: Lessons for vulnerable regions in tropical complex terrain. Natural Hazards and Earth System Sciences, 19(11):2635–2665.Hoyos, I., Dominguez, F., Cañón-Barriga, J., Martinez, A., Nieto, R., Gimeno, L., y Dirmeyer, P. (2017). Moisture origin and transport processes in colombia, northern south america. Climate Dynamics, 50.Huffman, G., Stocker, E., Bolvin, D., Nelkin, E., y Jackson, T. (2019). GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC).Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman, K. P., Hong, Y., Stocker, E. F., y Wolff, D. B. (2007). The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8(1):38–55.Jana, S., Rajagopalan, B., Alexander, M. A., y Ray, A. J. (2018). Understanding the dominant sources and tracks of moisture for summer rainfall in the southwest United States. Journal of Geophysical Research: Atmospheres, 123(10):4850–4870.Jaramillo, L. (2012). Caracterización de la lluvia y eventos de precipitación durante 2003-2010 definidos por la misión para la medición de lluvias tropicales (TRMM) sobre Colombia y la Cuenca amazónica. Tesis de Maestrı́a, Universidad Nacional de Colombia.Jaramillo, L., Poveda, G., y Mejía, J. F. (2017). Mesoscale convective systems and other precipitation features over the tropical Americas and surrounding seas as seen by TRMM. International Journal of Climatology, 37(February):380–397.Junker, N., Grumm, R., Hart, R., Bosart, L., Bell, K., y Pereira, F. (2007). Use of normalized anomaly fields to anticipate extreme rainfall in the mountains of northern california. Weather and Forecasting, 23.Junker, N. W., Grumm, R. H., Hart, R., Bosart, L. F., Bell, K. M., y Pereira, F. J. (2008). Use of normalized anomaly fields to anticipate extreme rainfall in the mountains of northern California. Weather and Forecasting, 23(3):336–356.Kassambara, A. (2017). Practical guide to cluster analysis in R: unsupervised machine learning. Journal of Computational and Graphical Statistics, page 187.Khain, A. P., Beheng, K. D., Heymsfield, A., Korolev, A., Krichak, S., Levin, Z., Pinsky, M., Phillips, V., Prabhakaran, T., Teller, A., Van den Heever, S. C., y Yano, J. I. (2015). Representation of microphysical processes in cloud-resolving models: Spectral (bin) microphysics versus bulk parameterization. Reviews of Geophysics, 53(37):247–322.Laing, A. y Evans, J.-L. (2011). Introduction to Tropical Meteorology. The COMET program, 2nd edition.Li, Z., Chao, Y., y McWilliams, J. C. (01 Nov. 2006). Computation of the stream function and velocity potential for limited and irregular domains. Monthly Weather Review, 134(11):3384 – 3394.Lima, K. C., Satyamurty, P., y Fernández, J. P. R. (2010). Large-scale atmospheric conditions associated with heavy rainfall episodes in Southeast Brazil. Theoretical and Applied Climatology, 101(1):121–135.Lindsey, D., Schmit, T. J., Jr., W. M. M., Jewitt, C. P., Gunshor, M. M., y Grasso, L. (2012). 10.35 μm: atmospheric window on the GOES-R Advanced Baseline Imager with less moisture attenuation. Journal of Applied Remote Sensing, 6(1):1–12.Liu, Q., Li, Y., Yu, M., Chiu, L., Hao, X., Duffy, D., y Yang, C. (2019). Daytime rainy cloud detection and convective precipitation delineation based on a deep neural network method using goes-16 abi images. Remote Sensing, 11:2555.Lorenz, E. N. (1956). Empirical Orthogonal Functions and Statistical Weather Prediction. Loriaux, J. M., Lenderink, G., y Siebesma, A. P. (01 Feb. 2017). Large-scale controls on extreme precipitation. Journal of Climate, 30(3):955 – 968.Mapes, B. E., Warner, T. T., Xu, M., y Negri, A. J. (2003). Diurnal patterns of rainfall in northwestern South America. Part I: Observations and context. Monthly Weather Review, 131(5):799–812.Marengo, J. A. y Espinoza, J. C. (2016). Extreme seasonal droughts and floods in amazonia: causes, trends and impacts. International Journal of Climatology, 36(3):1033–1050.Marin, G. (2005). Análisis sinóptico y de mesoescala de los eventos hidrometeorológicos extremos que afectan las cuencas de los ríos Nare y Guatapé los cuales alimentan a los embalses el peñol y playas, respectivamente, en el oriente de Antioquia, Colombia.Mecikalski, J. R. y Bedka, K. M. (2006). Forecasting Convective Initiation by Monitoring the Evolution of Moving Cumulus in Daytime GOES Imagery. Monthly Weather Review, 134(1):49–78.Mecikalski, J. R., MacKenzie, Wayne M., J., Koenig, M., y Muller, S. (2010a). Cloud-Top Properties of Growing Cumulus prior to Convective Initiation as Measured by Meteosat Second Generation. Part I: Infrared Fields. Journal of Applied Meteorology and Climatology, 49(3):521–534.Mecikalski, J. R., MacKenzie, Way ne M., J., König, M., y Muller, S. (2010b). Cloud-Top Properties of Growing Cumulus prior to Convective Initiation as Measured by Meteosat Second Generation. Part II: Use of Visible Reflectance. Journal of Applied Meteorology and Climatology, 49(12):2544–2558.Mejía, J. F. y Poveda, G. (2005). Ambientes Atmosféricos de Sistemas Convectivos de Mesoescala sobre Colombia durante 1998 según la misión TRMM y el re-análisis NCEP/NCAR. Revista de la academia colombiana de ciencias exactas físicas y naturales, 29:495–514.Montoya, G. y Lemus, R. (2005). Sistemas pluviogenéticos en Colombia: Influencia de frentes fríos del Hemisferio Norte. Meteorología Colombiana, 9:75–81.Moreno, H., Vélez, M., Montoya, J., y Rhenals, R. (2006). Tierra En Antioquia : Análisis De Su Ocurrencia En Las Escalas Interanual ,. Revista EIA, 5:59–69.Murtagh, F. y Legendre, P. (2014). Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion? Journal of Classification, 31(1):274–295. Nauss, T. y Kokhanovsky, A. A. (2006). Discriminating raining from non-raining clouds at midlatitudes using multispectral satellite data. Atmospheric Chemistry and Physics, 6(12):5031–5036.O’Gorman, P. A. (2015). Precipitation Extremes Under Climate Change. Current Climate Change Reports, 1(2):49–59.Pavolonis, M. J., Heidinger, A. K., y Uttal, T. (2005). Journal of Applied Meteorology, (6).Peterson, M., Rudlosky, S., y Zhang, D. (2020). Thunderstorm cloud-type classification from space-based lightning imagers. Monthly Weather Review, 148(5):1891–1898.Poveda, G. (2004). La hidroclimatología de Colombia: una síntesis desde la escala inter-decadal hasta la escala diurna. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 28:202–222.Poveda, G., Álvarez, D. M., y Rueda, Ó. A. (2010). Hydro-climatic variability over the Andes of Colombia associated with ENSO: A review of climatic processes and their impact on one of the Earth’s most important biodiversity hotspots. Climate Dynamics, 36(11-12):2233–2249.Poveda, G., Jaramillo, L., y Vallejo, L. F. (2014). Seasonal precipitation patterns along pathways of South American low-level jets and aerial rivers. Water Resources Research, 50(1):98–118.Poveda, G. y Mesa, O. (1999). La corriente del chorro superficial del oeste (“del Chocó”) y otras dos corrientes de chorro en Colombia: climatología y variabilidad durante las fases del ENSO.Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 23:517–528. Poveda, G., Mesa, O., AGUDELO, P., ÁLVAREZ, J., Arias, P., Moreno, H., Salazar Velásquez, L., Toro, V., Vieira, S., Jaramillo, A., y GUZMÁN, O. (2002). Influencia del enso,oscilación madden-julian, ondas del este, huracanes y fases de la luna en el ciclo diurno de precipitación en los andes tropicales de colombia de colombia. volume 5, pages 23–30.Poveda, G. y Mesa, O. J. (2000). On the existence of lloró (the rainiest lovality on earth): Enhanced ocean-land-atmosphere interaction by a low-level jet. Geophysical Research Letters, 27:1675–1678.Poveda, G., Mesa, O. J., Salazar, L. F., Arias, P. A., Moreno, H. A., Vieira, S. C., Agudelo, P. A., Toro, V. G., y Alvarez, J. F. (01 Jan. 2005). The diurnal cycle of precipitation in the tropical andes of colombia. Monthly Weather Review, 133(1):228 – 240.Poveda, G., Waylen, P. R., y Pulwarty, R. S. (2006). Annual and inter-annual variability of the present climate in northern South America and southern Mesoamerica. Palaeogeography, Palaeoclimatology, Palaeoecology, 234(1):3–27.Robert, M. (1967). A numerical procedure for computing fields of stream function and velocity potential.Roberts, R. D. y Rutledge, S. (2003). Nowcasting storm initiation and growth using GOES-8 and WSR-88D data. Weather and Forecasting, 18(4):562–584.Rodrı́guez-Morata, C., Ballesteros-Canovas, J. A., Rohrer, M., Espinoza, J. C., Beniston, M., y Stoffel, M. (2018). Linking atmospheric circulation patterns with hydro-geomorphic disasters in peru. International Journal of Climatology, 38(8):3388–3404.Rojo, J. y Mesa, O. (2020a). On the general circulation of the atmosphere around colombia. Revista de la Academia Colombiana de Ciencias Exactas Físicas y Naturales, 44:857.Rojo, J. y Mesa, O. (2020b). A simple conceptual model for the heat induced circulation over northern south america and meso-america. Atmosphere, 11.Salas, H. D., Poveda, G., Mesa, J., y Marwan, N. (2020). Generalized synchronization between enso and hydrological variables in colombia: A recurrence quantification approach. Frontiers in Applied Mathematics and Statistics, 6:3.Santos, E. B., Lucio, P. S., y Santos e Silva, C. M. (2017). Synoptic patterns of atmospheric circulation associated with intense precipitation events over the Brazilian Amazon. Theoretical and Applied Climatology, 128(1-2):343–358.Schmit, T., Lindstrom, S., Gerth, J., y Gunshor, M. (2018). Applications of the 16 spectral bands on the advanced baseline imager (abi). Journal of Operational Meteorology, 06:33–46.Schmit, T. J., Griffith, P., Gunshor, M. M., Daniels, J. M., Goodman, S. J., y Lebair, W. J. (2017). A closer look at the ABI on the GOES-R series. Bull. Amer. Meteor. Soc., (April):681–698.Seluchi, M. E. y Chou, S. C. (2009). Synoptic patterns associated with landslide events in the Serra do Mar, Brazil. Theoretical and Applied Climatology, 98(1-2):67–77.Sepúlveda Berrío, J. (2015). Estimación cuantitativa de precipitación a partir de la información de Radar Meteorológico del área Metropolitana del Valle de Aburrá.Serna, L. M., Arias, P. A., y Vieira, S. C. (2018). Las corrientes superficiales de chorro del Chocó y el Caribe durante los eventos de El Niño y El Niño Modoki. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 42(165):410.Shimizu, M. H. y Ambrizzi, T. (2016). MJO influence on ENSO effects in precipitation and temperature over South America. Theoretical and Applied Climatology, 124(1-2):291–301.Shimizu, M. H., Ambrizzi, T., y Liebmann, B. (2017). Extreme precipitation events and their relationship with enso and mjo phases over northern south america. International Journal of Climatology, 37(6):2977–2989. Siewert, C. W., Koenig, M., y Mecikalski, J. R. (2010). Application of Meteosat second generation data towards improving the nowcasting of convective initiation. Meteorological Applications, 17(4):442–451.Smith, R. K. (2015). Lectures on Tropical Meteorology. En línea: https://www.meteo.physik. uni-muenchen.de/~roger/Lectures/TropicalMetweb/Tropical_meteorology.pdf.Smyth, C. G. y Royle, S. A. (2000). Urban landslide hazards: incidence and causative factors in niterói, rio de janeiro state, brazil. Applied Geography, 20(2):95–118.So, D. y Shin, D.-B. (2018). Classification of precipitating clouds using satellite infrared observations and its implications for rainfall estimation. Quarterly Journal of the Royal Meteorological Society, 144(S1):133–144.Steiner, M., Houze, R. A., y Yuter, S. E. (1995). Climatological Characterization of Three Dimensional Storm Structure from Operational Radar and Rain Gauge Data. Journal of Applied Meteorology and Climatology, 34(9):1978–2007.Steinley, D. (2006). K-means clustering: A half-century synthesis. British Journal of Mathematical and Statistical Psychology, 59(1):1–34.Ta, S., Kouadio, K. Y., Ali, K. E., Toualy, E., Aman, A., y Yoroba, F. (2016). West Africa Extreme Rainfall Events and Large-Scale Ocean Surface and Atmospheric Conditions in the Tropical Atlantic. Advances in Meteorology, 2016.Tedeschi, R. G., Cavalcanti, I. F. A., y Grimm, A. M. (2013). Influences of two types of enso on south american precipitation. International Journal of Climatology, 33(6):1382–1400.Thies, B., Nauss, T., y Bendix, J. (2008). Precipitation process and rainfall intensity differentiation using meteosat second generation spinning enhanced visible and infrared imager data. Journal of Geophysical Research, 113.Torres-Pineda, C. E. y Pabón-Caicedo, J. D. (2017). Variabilidad intraestacional de la precipitación en Colombia y su relación con la oscilación de Madden-Julian. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 41(158):79.UCAR (2014). El ABI del GOES-R: la próxima generación de imágenes satelitales.Ungerovich, M. y Barreiro, M. (2019). Dynamics of extreme rainfall events in summer in southern Uruguay. International Journal of Climatology, 39(8):3655–3667.Urán, J. D. (2015). Cambios en los valores extremos de variables climáticas en Colombia asociados al cambio climático. Tesis de Doctorado, Universidad Nacional de Colombia.Velasquez, N. (2017). Evaluation of existing relations between convective systems and extreme events in tropical catchments of the Andean region. Tesis de Doctorado, Universidad Nacional de Colombia sede Medellín. Vergés-Llahí, J. (2005). Color constancy and image segmentation techniques for applications to mobile robotics. Tesis de Doctorado, Universitat Politècnica de Catalunya.Wang, C. (2007). Variability of the Caribbean Low-Level Jet and its relations to climate. Climate Dynamics, 29(4):411–422.Ward, J. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58(301):236–244.Zuluaga, M. y Poveda, G. (2004). Diagnóstico de sistemas convectivos de mesoescala sobre Colombia y el océano Pacífico Oriental durante 1998-2002. Avances en Recursos Hidráulicos, (11):145–160.Zuluaga, M. D. y Houze, R. A. (01 Jan. 2015). Extreme convection of the near-equatorial americas, africa, and adjoining oceans as seen by trmm. 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