Publicación: Características de las conexiones entre la precipitación en Colombia y eventos Enos Conónico y Modokí: Un análisis mediante redes complejas
| dc.contributor.advisor | Díaz-Guevara, Diana Cristina | |
| dc.creator | Guevara Muñoz, Duvan Fernando | |
| dc.date.accessioned | 2024-02-19T19:51:25Z | |
| dc.date.available | 2024-02-19T19:51:25Z | |
| dc.date.created | 2021-05-07 | |
| dc.description.abstract | Una de las oscilaciones macroclimáticas de escala interanual que causa las mayores anomalías de precipitación en Colombia es El Niño Oscilación del Sur (ENOS). El ENOS es el resultado de la interacción océano-atmosfera sobre el Océano Pacífico que suscita cambios aperiódicos de la temperatura superficial del mar (TSM) y de la presión atmosférica en superficie (PAS). Un evento con anomalías positivas se denomina El Niño y negativas La Niña, además si las máximas anomalías están concentradas en el Pacífico Oriental (PO) el evento es clasificado como tipo canónico, y si lo están en el Pacífico Central (PC) es denominado como tipo Modoki. Los eventos ENSO en Colombia han sido históricamente asociados a un aumento en la frecuencia o intensidad de situaciones adversas como sequías, incendios forestales, heladas, inundaciones, deslizamientos, entre otros que además de tener efectos negativos en la calidad de vida de la población generan gastos para atender las emergencias provocadas. La presente investigación ofrece a los pronosticadores elementos para evaluar la conexión entre la precipitación en el país y los eventos ENSO en sus diferentes modalidades, y de esta forma mejorar los modelos de pronóstico y aumentar la capacidad del país para prevenir o disminuir los impactos negativos. En esta oportunidad fueron utilizados los principios de la teoría de redes complejas para evaluar la relación entre la precipitación en Colombia y la dinámica oceánica y atmosférica sobre el Pacífico Ecuatorial. La investigación fue realizada para el periodo 1980-2016, en particular para el trimestre diciembre-febrero, época en la cual se ha reportado la mayor influencia del ENSO sobre la variabilidad climática del territorio nacional. La información de la precipitación mensual de las diferentes regiones naturales del país fue obtenida de dos fuentes, una la red de estaciones meteorológicas en superficie del Instituto de Estudios Ambientales (IDEAM) y la otra la base de datos del programa The Climate Hazards Infrared Precipitation with Stations (CHIRPS) basado principalmente en información de sensores satelitales. Por su parte, el ENSO fue representado por medio de ocho índices calculados con base en la TSM de diferentes regiones del pacífico. Las conexiones entre la precipitación y los índices para conformar las redes fueron estimadas utilizando dos medidas o métricas, la primera lineal conocida como el coeficiente de correlación de Pearson y la segunda, de carácter no lineal, denominada información mutua. Las dos medidas fueron aplicadas a los dos conjuntos de datos de precipitación (IDEAM y CHIRPS), conformando en total cuatro tipos de análisis. Adicionalmente en cada análisis fueron evaluados nueve escenarios que contemplaron diferentes combinaciones de eventos canónicos o del Pacífico Oriental (PO) y Modoki o del Pacífico Central (PC). A partir de las conexiones establecidas se obtuvieron cuatro grupos de nueve redes cada uno, las cuales revelan las características de las conexiones entre la precipitación en Colombia y eventos ENOS canónico y Modoki. Durante eventos del tipo Modoki o del PC la precipitación y los diferentes índices presentaron mayor cantidad de conexiones de orden lineal. Por el contrario, para eventos canónicos o del PO hubo mayor proporción de vínculos de tipo no lineal, en especial, si son eventos fríos. Las redes sugirieron también que El Niño 3 y TNI (Índice Trans-Niño) son los índices que más conexiones lineales tienen con la variabilidad de la precipitación, mientras que con Niño 1+2 se obtuvieron la mayor cantidad de vínculos de orden no lineal. | spa |
| dc.description.abstractenglish | One of the macroclimatic interannual oscillations that causes the greatest precipitation anomalies in Colombia is the El Niño-Southern Oscillation (ENSO). ENSO is the result of ocean-atmosphere interaction over the Pacific Ocean that triggers sporadic changes in sea surface temperature (SST) and surface atmospheric pressure (SAP). An event with positive anomalies is called El Niño, and negative anomalies are termed La Niña. Additionally, if the maximum anomalies are concentrated in the Eastern Pacific (EP), the event is classified as canonical, and if they are in the Central Pacific (CP), it is referred to as Modoki type. ENSO events in Colombia have historically been associated with an increase in the frequency or intensity of adverse situations such as droughts, forest fires, frost, floods, landslides, among others, which not only have negative effects on the population's quality of life but also incur expenses to address the resulting emergencies. This research provides forecasters with elements to evaluate the connection between precipitation in the country and ENSO events in their different modalities, thereby improving forecasting models and increasing the country's capacity to prevent or mitigate negative impacts. In this study, the principles of complex network theory were used to evaluate the relationship between precipitation in Colombia and oceanic and atmospheric dynamics over the Equatorial Pacific. The research was conducted for the period 1980-2016, particularly for the December-February quarter, a time when the greatest influence of ENSO on the climatic variability of the national territory has been reported. Monthly precipitation information for the different natural regions of the country was obtained from two sources: the network of surface meteorological stations of the Institute of Environmental Studies (IDEAM) and the database of the Climate Hazards Infrared Precipitation with Stations (CHIRPS) program, based mainly on satellite sensor information. Meanwhile, ENSO was represented by eight indices calculated based on SST from different regions of the Pacific. The connections between precipitation and the indices to form the networks were estimated using two measures or metrics: the first linear one known as the Pearson correlation coefficient, and the second, nonlinear in nature, called mutual information. Both measures were applied to the two precipitation datasets (IDEAM and CHIRPS), resulting in a total of four types of analyses. Additionally, nine scenarios were evaluated in each analysis, considering different combinations of canonical or Eastern Pacific (EP) events and Modoki or Central Pacific (CP) events. Based on the established connections, four groups of nine networks each were obtained, which reveal the characteristics of the connections between precipitation in Colombia and canonical and Modoki ENSO events. During Modoki or CP events, precipitation and the different indices showed a greater number of linear connections. In contrast, for canonical or EP events, there was a higher proportion of nonlinear connections, especially for cold events. The networks also suggested that El Niño 3 and TNI (Trans-Niño Index) are the indices with the most linear connections to precipitation variability, while Niño 1+2 yielded the highest number of nonlinear connections. | spa |
| dc.format.extent | 40 páginas | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.identifier.uri | https://hdl.handle.net/20.500.12010/34036 | |
| dc.language.iso | spa | spa |
| dc.relation.references | Alexander, M. A., Bladé, I., Newman, M., Lanzante, J. R., Lau, N. C., & Scott, J. D. (2002). The atmospheric bridge: The influence of ENSO teleconnections on air–sea interaction over the global oceans. Journal of climate, 15(16), 2205-2231 | spa |
| dc.relation.references | Alfaro, E. J. (2007). Uso del análisis de correlación canónica para la predicción de la precipitación pluvial en Centroamérica. Ingeniería y Competitividad, 9(2), 49-58. | spa |
| dc.relation.references | Ashok K, Behera SK, Rao SA, Weng HY, Yamagata T (2007) El Niño Modoki and its possible teleconnection. J Geophys Res 112:C11007. https ://doi.org/10.1029/2006J C0037 98 | spa |
| dc.relation.references | Beltrán, L., & Díaz, D. C. (2020). Oscilaciones Macroclimáticas que Afectan la Oferta Hídrica en la Cuenca del Río Gachaneca; Boyacá-Colombia. Revista Brasileira de Meteorologia, 35(2), 171-185. | spa |
| dc.relation.references | Carmona, A. M., & Poveda, G. (2014). Detection of long-term trends in monthly hydro-climatic series of Colombia through Empirical Mode Decomposition. Climatic Change, 123(2), 301-313. | spa |
| dc.relation.references | Cannon, A. J. (2015). Revisiting the nonlinear relationship between ENSO and winter extreme station precipitation in North America. International Journal of Climatology, 35(13), 4001-4014. | spa |
| dc.relation.references | Chikamoto, Y., Timmermann, A., Luo, J. J., Mochizuki, T., Kimoto, M., Watanabe, M., & Jin, F. F. (2015). Skilful multi-year predictions of tropical trans-basin climate variability. Nature communications, 6(1), 1-7. | spa |
| dc.relation.references | Díaz, D., & Villegas, N. (2015). Correlación canónica entre índices macroclimáticos y variables meteorológicas de superficie en Colombia. Revista UDCA Actualidad & | spa |
| dc.relation.references | Diaz, D. C., Bojacá, C. R., & Schrevens, E. (2016). Modeling the suitability of the traditional plastic greenhouse for tomato production across Colombian regions. In International Symposia on Tropical and Temperate Horticulture-ISTTH2016 1205 (pp. 857-864). | spa |
| dc.relation.references | Díaz, D.C. (2017). Modelado y simulación de sistemas climáticos: desde la escala global hasta los microclimas. In: C. Bojacá Aldana, D. Díaz Guevara, F. Cala Vitery, F. Gutiérrez Bonilla, G. Villalobos Camargo, J. Riascos Ochoa, J. Burgos Bedout and R. Gil Castañeda, ed., Modelado y Simulación de sistemas naturales, 1st ed. Bogotá: Universidad de Bogotá Jorge Tadeo Lozano, p.44. | spa |
| dc.relation.references | Donges, J. F., Zou, Y., Marwan, N., & Kurths, J. (2009a). Complex networks in climate dynamics. The European Physical Journal Special Topics, 174(1), 157-179. | spa |
| dc.relation.references | Donges, J. F., Zou, Y., Marwan, N., & Kurths, J. (2009b). The backbone of the climate network. EPL (Europhysics Letters), 87(4), 48007. | spa |
| dc.relation.references | Drouard, M., Rivière, G., & Arbogast, P. (2015). The link between the North Pacific climate variability and the North Atlantic Oscillation via downstream propagation of synoptic waves. Journal of Climate, 28(10), 3957-3976. | spa |
| dc.relation.references | Feldhoff, J. H., Lange, S., Volkholz, J., Donges, J. F., Kurths, J., & Gerstengarbe, F. W. (2015). Complex networks for climate model evaluation with application to statistical versus dynamical modeling of South American climate. Climate dynamics, 44(5-6), 1567-1581. | spa |
| dc.relation.references | Fleming, S. W., & Dahlke, H. E. (2014). Parabolic northern-hemisphere river flow teleconnections to El Niño-Southern Oscillation and the Arctic Oscillation. Environmental Research Letters, 9(10), 104007. | spa |
| dc.relation.references | Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S.,& Michaelsen, J. (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific data, 2(1), 1-21. | spa |
| dc.relation.references | Gu, D., & Philander, S. G. (1997). Interdecadal climate fluctuations that depend on exchanges between the tropics and extratropics. Science, 275(5301), 805-807. | spa |
| dc.relation.references | Guzmán, D., Ruíz, J. F., y M., C. (2014). Regionalización de Colombia según la estacionalidad de la precipitación media mensual, a través del análisis de componentes principales. Nota técnica, Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM), Subdirección de Meteorología, Bogotá-Colombia. | spa |
| dc.relation.references | Hallett, T.B.; Coulson, T.; Pilkington, J.G.; Clutton-Brock, T.H.; Pemberton, J.M.; Grenfell, B.T. (2004). Why large-scale climate indices seem to predict ecological processes better than local weather. Nature, 430, 71–75. | spa |
| dc.relation.references | Hao, Z., & Singh, V. P. (2016). Review of dependence modeling in hydrology and wáter resources. Progress in Physical Geography, 40(4), 549-578. | spa |
| dc.relation.references | Harrold, T. I., Sharma, A., & Sheather, S. (2001). Selection of a kernel bandwidth for measuring dependence in hydrologic time series using the mutual information criterion. Stochastic environmental research and risk assessment, 15(4), 310-324. | spa |
| dc.relation.references | Hlinka, J.; Hartman, D.; Vejmelka, M.; Novotná, D.; Paluš, M. Non-linear dependence and teleconnections in climate data: Sources, relevance, nonstationarity. 2014. Clim. Dyn. 42, 1873–1886. | spa |
| dc.relation.references | IDEAM. (2005). Atlas Climatológico de Colombia. Bogotá. ISBN 958-8067146 | spa |
| dc.relation.references | Kao HY, Yu JY (2009) Contrasting eastern-Pacific and central-Pacific types of ENSO. J Clim 22:615–632 | spa |
| dc.relation.references | Marwan, N., Donges, J.F., Zou, Y., Donner, R.V., & Kurths, J. (2009). Complex network approach for recurrence analysis of time series. | spa |
| dc.relation.references | Mesa-Sánchez, Ó. J., & Peñaranda-Vélez, V. M. (2015). Complexity of the space-time structure of rainfall. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 39(152), 304-320. | spa |
| dc.relation.references | Mishra, A.K.; Özger, M.; Singh, V.P. (2009). An entropy-based investigation into the variability of precipitation. J. Hydrol., 370, 139–154. | spa |
| dc.relation.references | Mishra, A.K.; Özger, M.; Singh, V.P. (2011). Association between uncertainty in meteorological variables and water resources planning for Texas. J. Hydrol. Eng., 16, 984–999. | spa |
| dc.relation.references | Mishra, A.K.; Coulibaly, P. (2010). Hydrometric network evaluation for Canadian watersheds. J. Hydrol., 380, 420–437. | spa |
| dc.relation.references | Mishra, A.K.; Singh, V.P. (2009a). Analysis of drought severity-area-frequency curves using a general circulation model and scenario uncertainty. J. Geophys. Res. Atmos. 114 | spa |
| dc.relation.references | Mishra, A.K.; Özger, M.; Singh, V.P. (2009b). Trend and persistence of precipitation under climate change scenarios. Hydrol. Proc. 23, 2345–2357. | spa |
| dc.relation.references | Montealegre, E. (2009). Estudio de la variabilidad climática de la precipitación en Colombia asociada a procesos oceánicos y atmosféricos de meso y gran escala. Nota técnica, Instituto de hidrología, Meteorología y Estudios Ambientales (IDEAM), Subdirección de Meteorología, Bogotá-Colombia. | spa |
| dc.relation.references | Navarro-Monterroza, E., Arias, P. A., & Vieira, S. C. (2019). El Niño-Oscilación del Sur, fase Modoki, y sus efectos en la variabilidad espacio-temporal de la precipitación en Colombia. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 43(166), 120-132. | spa |
| dc.relation.references | Poveda, G., Gil, M. M., Quiceno, N. (1998). El ciclo anual de la hidrología de Colombia en relación con el ENSO y la NAO. Bulletin de l’Institut français d’études andines. 27:721-731. | spa |
| dc.relation.references | Poveda, G. (2004). La Hidroclimatología de Colombia: una síntesis desde la escala inter-decadal hasta la escala diurna. Revista Academia Colombiana de Ciencias, 28 (107):201-222. | spa |
| dc.relation.references | Henríquez, M. (2012). Climatología ambiental de Colombia. Colombia: Universidad Santo Tomás. | spa |
| dc.relation.references | Poveda G, Espinoza JC, Zuluaga MD, Solman SA, Garreaud R and van Oevelen PJ (2020) High Impact Weather Events in the Andes. Front. Earth Sci. 8:162. doi: 10.3389/feart.2020.00162 | spa |
| dc.relation.references | Power, S., Casey, T., Folland, C., Colman, A., Mehta. (1999). Inter decadal modulation of the impact of ENSO on Australia Climate Dyna 15 (5), 319–324. | spa |
| dc.relation.references | Preethi, B., Sabin, T. P., Adedoyin, J. A., & Ashok, K. (2016). Erratum: Impacts of the ENSO Modoki and other Tropical Indo-Pacific Climate-Drivers on African Rainfall. Scientific reports, 6 | spa |
| dc.relation.references | Rasmusson, E. M., Carpenter T. H. (1982). Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/El Niño. Monthly Weather Review. 110: 354-384. | spa |
| dc.relation.references | Rajsekhar, D.; Mishra, A.K.; Singh, V.P. Regionalization of drought characteristics using an entropy approach. J. Hydrol. Eng. (2013) 18, 870–887. | spa |
| dc.relation.references | Rheinwalt, A., Kurths, J., Hoffmann, P., & Werner, P. (2015). Non-linear time series analysis of precipitation events using regional climate networks for Germany. 14 | spa |
| dc.relation.references | Ren HL, Jin FF (2011) Ni.o indices for two types of ENSO. Geophys Res Lett 38: L04704. https://doi.org/10.1029/2010G L0460 31 | spa |
| dc.relation.references | Ren HL, Jin FF, Stuecker M, Xie RH (2013) ENSO regime change since the late 1970s as manifested by two types of ENSO. J Meteor Soc Japan 91:835–842 | spa |
| dc.relation.references | Schmidt, G. Zamora-López, and J. Kurths, Simulation of large-scale cortical networks by use of individual neuron dynamics, Int. J. Bif. Chaos, (2008), in press.15 | spa |
| dc.relation.references | Sharma, A. Seasonal to interannual rainfall probabilistic forecasts for improved water supply management: Part 1—A strategy for system predictor identification. J. Hydrol. (2000). 239, 232–239. | spa |
| dc.relation.references | Singh, A., Acharya, N., Mohanty, U. C., & Mishra, G. (2013). Performance of multi model canonical correlation analysis (MMCCA) for prediction of Indian summer monsoon rainfall using GCMs output. Comptes Rendus Geoscience, 345(2), 62-72. | spa |
| dc.relation.references | Steinhaeuser, K., Chawla, N.V., & Ganguly, A.R. (2009). An exploration of climate data using complex networks. SIGKDD Explorations, 12, 25-32. | spa |
| dc.relation.references | Steinhaeuser, K., Chawla, N.V., & Ganguly, A.R. (2010). Complex Networks In Climate Science: Progress, Opportunities And Challenges. CIDU. | spa |
| dc.relation.references | Steinhaeuser, K., Chawla, N.V., & Ganguly, A.R. (2011). Complex networks as a unified framework for descriptive analysis and predictive modeling in climate science. Statistical Analysis and Data Mining, 4, 497-511. | spa |
| dc.relation.references | Sulca, J., Takahashi, K., Espinoza, J. C., Vuille, M., & Lavado‐Casimiro, W. (2018). Impacts of different ENSO flavors and tropical Pacific convection variability (ITCZ, SPCZ) on austral summer rainfall in South America, with a focus on Peru. International Journal of Climatology, 38(1), 420-435. | spa |
| dc.relation.references | Tartaglione, C.A., Smith, S.R., O’Brien, J.J. (2003). Enso impact on hurricane land fall probabilities for the Caribbean.J. Climate 16 (17), 2925–2931. | spa |
| dc.relation.references | Urrea, V., Ochoa, A., & Mesa, O. (2016). Validación de la base de datos de precipitación CHIRPS para Colombia a escala diaria, mensual y anual en el periodo 1981-2014. In XXVII Congreso Latinoamericano de Hidráulica, IAHS, Lima, Perú, URL http://ladhi2016. org. | spa |
| dc.relation.references | Vu, T. M., Mishra, A. K., & Konapala, G. (2018). Information entropy suggests stronger nonlinear associations between hydro-meteorological variables and ENSO. Entropy, 20(1), 38. | spa |
| dc.relation.references | Wyrtki, K. (1975). El Niño-The Dynamic Response of the Equatorial Pacific Ocean to Atmospheric Forcing. Journal of Physical Oceanography. 5: 572-584 | spa |
| dc.relation.references | Yoon, S., & Lee, T. (2016). Investigation of hydrological variability in the Korean Peninsula with the ENSO teleconnections. Proceedings of the International Association of Hydrological Sciences, 374, 165. | spa |
| dc.relation.references | Zhang, Y.; Cabilio, P.; Nadeem, K. Improved Seasonal Mann–Kendall Tests for Trend Analysis in Water Resources Time Series. (2016). In Advances in Time Series Methods and Applications; Li,W.K., Stanford, D.A., Yu, H., Eds.; Springer: New York, NY, USA; pp. 215–229, ISBN 978-1-4939-6568-7. | spa |
| dc.relation.references | Zhang W. Wang L, Xiang B, Qi L, He J (2015). Impacts of two types of La Nina on the NAO during boreal winter. Clim Dyn 44:1351–1366 | spa |
| dc.relation.references | Zhang W, Li H, Stuecker M, Jin FF, Turner AG (2016). A new understanding of El Nino’s impact over East Asia: dominance of the ENSO combination mode. J Clim 29:4347–4359 | spa |
| dc.relation.references | Zhang T, Hoerling MP, Wolter K et al (2018). Predictability and prediction of southern California rains during strong El Niño events: a focus on the failed 2016 winter rains. J Clim 31:555–574 | spa |
| dc.relation.references | Zhang, W., Wang, Z., Stuecker, M. F., Turner, A. G., Jin, F. F., & Geng, X. (2019). Impact of ENSO longitudinal position on teleconnections to the NAO. Climate Dynamics, 52(1-2), 257-274. | spa |
| dc.relation.references | Earth system research laboratory -ESRL-. (2020a). Climate Indices: Monthly Atmospheric and Ocean Time Series Database [online]. National Oceanic and Atmospheric Administra-tion, Boulder (CO. USA). Disponible desde Internet en: http://www. esrl.noaa.gov/psd/data/climateindices/list/ (con acceso 20/10/2020). | spa |
| dc.relation.references | Earth system research laboratory -ESRL-. (2020b). National Oceanic and Atmospheric Administration, Boulder (CO. USA). Analysis and Plotting Tools. Disponible desde Internet en: https://psl.noaa.gov/cgi-bin/data/composites/plot20thc.v2.pl | spa |
| dc.subject | Precipitacion | spa |
| dc.subject | Enos Canónico | spa |
| dc.subject | Modkí | spa |
| dc.subject.lemb | Precipitaciones -- Investigaciones | |
| dc.subject.lemb | Precipitaciones -- Colombia | |
| dc.subject.lemb | Redes neuronles | |
| dc.title | Características de las conexiones entre la precipitación en Colombia y eventos Enos Conónico y Modokí: Un análisis mediante redes complejas | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | spa |
| dspace.entity.type | Publication | |
| relation.isAdvisorOfPublication | a0b17c33-0de1-481c-beed-d2768c4c73bf | |
| relation.isAdvisorOfPublication.latestForDiscovery | a0b17c33-0de1-481c-beed-d2768c4c73bf |
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