Intensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externo

Ilustraciones, mapas

Autores:
Pérez Carrasquilla, Jhayron Steven
Tipo de recurso:
Fecha de publicación:
2021
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
eng
OAI Identifier:
oai:repositorio.unal.edu.co:unal/79714
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/79714
https://repositorio.unal.edu.co/
Palabra clave:
550 - Ciencias de la tierra::551 - Geología, hidrología, meteorología
530 - Física::532 - Mecánica de fluidos
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
Ciclones
Ciclones tropicales
Convección húmeda
Intensificación rápida
Tropical cyclones
Moist convection
Rapid intensification
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openAccess
License
Atribución-NoComercial-SinDerivadas 4.0 Internacional
id UNACIONAL2_7c4443c631ca9aff5f09895a5cd6d020
oai_identifier_str oai:repositorio.unal.edu.co:unal/79714
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Intensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externo
dc.title.translated.eng.fl_str_mv Tropical cyclone rapid intensification: spatio-temporal variability, inner-core dynamics and environmental control.
title Intensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externo
spellingShingle Intensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externo
550 - Ciencias de la tierra::551 - Geología, hidrología, meteorología
530 - Física::532 - Mecánica de fluidos
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
Ciclones
Ciclones tropicales
Convección húmeda
Intensificación rápida
Tropical cyclones
Moist convection
Rapid intensification
title_short Intensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externo
title_full Intensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externo
title_fullStr Intensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externo
title_full_unstemmed Intensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externo
title_sort Intensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externo
dc.creator.fl_str_mv Pérez Carrasquilla, Jhayron Steven
dc.contributor.advisor.none.fl_str_mv Hoyos Ortiz, Carlos David
dc.contributor.author.none.fl_str_mv Pérez Carrasquilla, Jhayron Steven
dc.subject.ddc.spa.fl_str_mv 550 - Ciencias de la tierra::551 - Geología, hidrología, meteorología
530 - Física::532 - Mecánica de fluidos
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
topic 550 - Ciencias de la tierra::551 - Geología, hidrología, meteorología
530 - Física::532 - Mecánica de fluidos
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
Ciclones
Ciclones tropicales
Convección húmeda
Intensificación rápida
Tropical cyclones
Moist convection
Rapid intensification
dc.subject.lemb.none.fl_str_mv Ciclones
dc.subject.proposal.spa.fl_str_mv Ciclones tropicales
Convección húmeda
Intensificación rápida
dc.subject.proposal.eng.fl_str_mv Tropical cyclones
Moist convection
Rapid intensification
description Ilustraciones, mapas
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-06-24T18:56:36Z
dc.date.available.none.fl_str_mv 2021-06-24T18:56:36Z
dc.date.issued.none.fl_str_mv 2021
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/79714
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/79714
https://repositorio.unal.edu.co/
identifier_str_mv Universidad Nacional de Colombia
Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv Anthes, R. A., Kuo, Y.-H., Baumhefner, D. P., Errico, R. M., and Bettge, T. W. (1985). Predictability of mesoscale atmospheric motions. In Advances in geophysics, volume 28, pages 159–202. Elsevier.
Bell, M. M., Montgomery, M. T., and Emanuel, K. A. (2012). Air–sea enthalpy and momentum exchange at major hurricane wind speeds observed during cblast. Journal of the Atmospheric Sciences, 69(11):3197–3222.
Bister, M. and Emanuel, K. A. (1998). Dissipative heating and hurricane intensity. Meteorology and Atmospheric Physics, 65(3-4):233–240.
Bosart, L. F., Bracken, W. E., Molinari, J., Velden, C. S., and Black, P. G. (2000). Environmental influences on the rapid intensification of hurricane opal (1995) over the gulf of mexico. Monthly Weather Review, 128(2):322–352.
Bryan, G. H. (2012). Effects of surface exchange coefficients and turbulence length scales on the intensity and structure of numerically simulated hurricanes. Monthly weather review, 140(4):1125–1143.
Bryan, G. H. and Fritsch, J. M. (2002). A benchmark simulation for moist nonhydrostatic numerical models. Monthly Weather Review, 130(12):2917–2928.
Camargo, S. J., Robertson, A. W., Barnston, A. G., and Ghil, M. (2008). Clustering of eastern north pacific tropical cyclone tracks: Enso and mjo effects. Geochemistry, Geophysics, Geosystems, 9(6).
Camargo, S. J., Robertson, A. W., Gaffney, S. J., Smyth, P., and Ghil, M. (2007). Cluster analysis of typhoon tracks. part ii: Large-scale circulation and enso. Journal of climate, 20(14):3654–3676.
Camargo, S. J. and Sobel, A. H. (2005). Western north pacific tropical cyclone intensity and enso. Journal of Climate, 18(15):2996–3006.
Carr III, L. and Williams, R. (1989). Barotropic vortex stability to perturbations from axisymmetry. Journal of the atmospheric sciences, 46(20):3177–3191.
Chan, J. C. (2000). Tropical cyclone activity over the western north pacific associated with el niño and la niña events. Journal of Climate, 13(16):2960–2972.
Charney, J. G. and Eliassen, A. (1964). On the growth of the hurricane depression. Journal of the Atmospheric Sciences, 21(1):68–75.
Chen, B., Li, J., and Ding, R. (2006). Nonlinear local lyapunov exponent and atmospheric predictability research. Science in China Series D: Earth Sciences, 49(10):1111–1120.
Chiang, J. C. and Sobel, A. H. (2002). Tropical tropospheric temperature variations caused by enso and their influence on the remote tropical climate. Journal of climate, 15(18):2616– 2631.
Chu, P. (2004). Enso and tropical cyclone activity. hurricanes and typhoons: Past, present, and potential, rj murnane and k.-b. liu, eds. Columbia University Press, 297:332.
Cione, J. J. and Uhlhorn, E. W. (2003). Sea surface temperature variability in hurricanes: Implications with respect to intensity change. Monthly Weather Review, 131(8).
Dare, R. A. and McBride, J. L. (2011). Sea surface temperature response to tropical cyclones. Monthly Weather Review, 139(12):3798–3808.
Davis, C., Wang, W., Chen, S. S., Chen, Y., Corbosiero, K., DeMaria, M., Dudhia, J., Holland, G., Klemp, J., Michalakes, J., et al. (2008). Prediction of landfalling hurricanes with the advanced hurricane wrf model. Monthly weather review, 136(6):1990–2005.
Davis, C. A. and Emanuel, K. A. (1991). Potential vorticity diagnostics of cyclogenesis. Monthly weather review, 119(8):1929–1953.
DeMaria, M. and Kaplan, J. (1994). A statistical hurricane intensity prediction scheme (ships) for the atlantic basin. Weather and Forecasting, 9(2):209–220.
DeMaria, M., Kaplan, J., and Baik, J.-J. (1993). Upper-level eddy angular momentum fluxes and tropical cyclone intensity change. Journal of the atmospheric sciences, 50(8):1133–1147.
DeMaria, M., Sampson, C. R., Knaff, J. A., and Musgrave, K. D. (2014). Is tropical cyclone intensity guidance improving? Bulletin of the American Meteorological Society, 95(3):387–398.
Emanuel, K., DesAutels, C., Holloway, C., and Korty, R. (2004). Environmental control of tropical cyclone intensity. Journal of the atmospheric sciences, 61(7):843–858.
Emanuel, K. and Zhang, F. (2016). On the predictability and error sources of tropical cyclone intensity forecasts. Journal of the Atmospheric Sciences, 73(9):3739–3747.
Emanuel, K. A. (1986). An air-sea interaction theory for tropical cyclones. part i: Steady- state maintenance. Journal of the Atmospheric Sciences, 43(6):585–605.
Emanuel, K. A. (1989). Dynamical theories of tropical. Australian Meteorological Magazine, 37(1).
Fan, Y., Ginis, I., and Hara, T. (2009). The effect of wind–wave–current interaction on air–sea momentum fluxes and ocean response in tropical cyclones. Journal of Physical Oceanography, 39(4):1019–1034.
Finocchio, P. M. and Majumdar, S. J. (2017). The predictability of idealized tropical cyclones in environments with time-varying vertical wind shear. Journal of Advances in Modeling Earth Systems, 9(8):2836–2862.
Frank, W. M. and Ritchie, E. A. (2001). Effects of vertical wind shear on the intensity and structure of numerically simulated hurricanes. Monthly weather review, 129(9):2249–2269.
Frank, W. M. and Roundy, P. E. (2006). The role of tropical waves in tropical cyclogenesis. Monthly W eather Review, 134(9):2397–2417.
Fudeyasu, H., Ito, K., and Miyamoto, Y. (2018). Characteristics of tropical cyclone rapid intensification over the western north pacific. Journal of Climate, 31(21):8917–8930.
Giannini, A., Chiang, J. C., Cane, M. A., Kushnir, Y., and Seager, R. (2001). The enso teleconnection to the tropical atlantic ocean: Contributions of the remote and local ssts to rainfall variability in the tropical americas. Journal of Climate, 14(24):4530–4544.
Girishkumar, M. and Ravichandran, M. (2012). The influences of enso on tropical cyclone activity in the bay of bengal during october–december. Journal of Geophysical Research: Oceans, 117(C2).
Girishkumar, M., Suprit, K., Vishnu, S., Prakash, V. T., and Ravichandran, M. (2015). The role of enso and mjo on rapid intensification of tropical cyclones in the bay of bengal during october–december. Theoretical and Applied Climatology, 120(3-4):797–810.
Gloeckler III, L. C. and Roundy, P. E. (2019). A statistical analysis of relationships between western north pacific tropical cyclones and extratropical circulation patterns accompanying the madden–julian oscillation. Journal of the Atmospheric Sciences, 76(2):583–604.
Goldenberg, S. B. and Shapiro, L. J. (1996). Physical mechanisms for the association of el niño and west african rainfall with atlantic major hurricane activity. Journal of Climate, 9(6):1169–1187.
Goodman, S. J., Blakeslee, R. J., Koshak, W. J., Mach, D., Bailey, J., Buechler, D., Carey, L., Schultz, C., Bateman, M., McCaul Jr, E., et al. (2013). The goes-r geostationary lightning mapper (glm). Atmospheric research, 125:34–49.
Gray, W. M. (1984). Atlantic seasonal hurricane frequency. part i: El niño and 30 mb quasi-biennial oscillation influences. Monthly Weather Review, 112(9):1649–1668.
Green, B. W. and Zhang, F. (2014). Sensitivity of tropical cyclone simulations to parametric uncertainties in air–sea fluxes and implications for parameter estimation. Monthly Weather Review, 142(6):2290–2308.
Green, B. W. and Zhang, F. (2015). Numerical simulations of h urricane k atrina (2005) in the turbulent gray zone. Journal of Advances in Modeling Earth Systems, 7(1):142–161.
Guimond, S. R., Heymsfield, G. M., and Turk, F. J. (2010). Multiscale observations of hurricane dennis (2005): The effects of hot towers on rapid intensification. Journal of the atmospheric sciences, 67(3):633–654.
Guinn, T. A. and Schubert, W. H. (1993). Hurricane spiral bands. Journal of the atmospheric sciences, 50(20):3380–3403.
Hakim, G. J. (2013). The variability and predictability of axisymmetric hurricanes in statistical equilibrium. Journal of the atmospheric sciences, 70(4):993–1005.
Hanley, D., Molinari, J., and Keyser, D. (2001). A composite study of the interactions between tropical cyclones and upper-tropospheric troughs. Monthly weather review, 129(10):2570–2584.
Hendricks, E. A., Montgomery, M. T., and Davis, C. A. (2004). The role of “vortical” hot towers in the formation of tropical cyclone diana (1984). Journal of the atmospheric sciences, 1(11):1209–1232.
Holliday, C. R. and Thompson, A. H. (1979). Climatological characteristics of rapidly intensifying typhoons. Monthly Weather Review, 107(8):1022–1034.
Hong, X., Chang, S. W., Raman, S., Shay, L. K., and Hodur, R. (2000). The interaction between hurricane opal (1995) and a warm core ring in the gulf of mexico. Monthly Weather Review, 28(5):1347–1365.
Houze Jr, R. A., Lee, W.-C., and Bell, M. M. (2009). Convective contribution to the genesis of hurricane ophelia (2005). Monthly Weather Review, 137(9):2778–2800.
Irwin III, R. P. and Davis, R. E. (1999). The relationship between the southern oscillation index and tropical cyclone tracks in the eastern north pacific. Geophysical research letters, 26(15):2251–2254.
Janjić, Z. I. (1990). The step-mountain coordinate: Physical package. Monthly Weather Review, 118(7):1429–1443.
Jordan, C. L. (1958). Mean soundings for the west indies area. Journal of Meteorology, 15(1):91–97.
Judt, F. and Chen, S. S. (2016). Predictability and dynamics of tropical cyclone rapid intensification deduced from high-resolution stochastic ensembles. Monthly Weather Review, 144(11):4395–4420.
Judt, F., Chen, S. S., and Berner, J. (2016). Predictability of tropical cyclone intensity: scaledependent forecast error growth in high-resolution stochastic kinetic-energy backscatter ensembles. Quarterly Journal of the Royal Meteorological Society, 142(694):43–57.
Kaplan, John, Rozoff, Mark, Sampson, R., C., Kossin, P., J., J., J., P., J., and et al. (2015). Evaluating environmental impacts on tropical cyclone rapid intensification predictability utilizing statistical models. Weather and Forecasting.
Kaplan, J. and DeMaria, M. (2003). Large-scale characteristics of rapidly intensifying tropical cyclones in the north atlantic basin. Weather and forecasting, 18(6):1093–1108.
Kaplan, J., DeMaria, M., and Knaff, J. A. (2010). A revised tropical cyclone rapid intensification index for the atlantic and eastern north pacific basins. Weather and forecasting, 25(1):220–241.
Kessler, E. (1969). On the distribution and continuity of water substance in atmosphericcirculations. In On the distribution and continuity of water substance in atmospheric circulations, pages 1–84. Springer.
Khain, A., Lynn, B., and Shpund, J. (2016). High resolution wrf simulations of hurricane irene: Sensitivity to aerosols and choice of microphysical schemes. Atmospheric Research, 167:129–145.
Kieu, C. Q. and Moon, Z. (2016). Hurricane intensity predictability. Bulletin of the American Meteorological Society, 97(10):1847–1857.
Kim, H.-M., Webster, P. J., and Curry, J. A. (2011). Modulation of north pacific tropical cyclone activity by three phases of enso. Journal of Climate, 24(6):1839–1849.
Kimball, S. K. (2006). A modeling study of hurricane landfall in a dry environment. Monthly weather review, 134(7):1901–1918.
Klemp, J. B. and Wilhelmson, R. B. (1978). The simulation of three-dimensional convective storm dynamics. Journal of the Atmospheric Sciences, 35(6):1070–1096.
Klotzbach, P. J. (2010). On the madden–julian oscillation–atlantic hurricane relationship. Journal of Climate, 23(2):282–293.
Klotzbach, P. J. (2012). El niño-southern oscillation, the madden-julian oscillation and atlantic basin tropical cyclone rapid intensification. Journal of Geophysical Research: Atmospheres, 117(D14).
Klotzbach, P. J. (2014). The madden–julian oscillation’s impacts on worldwide tropical cyclone activity. Journal of Climate, 27(6):2317–2330.
Kossin, J. P. and Eastin, M. D. (2001). Two distinct regimes in the kinematic and thermodynamic structure of the hurricane eye and eyewall. Journal of the atmospheric sciences, 58(9):1079–1090.
Kotal, S. and Roy Bhowmik, S. (2013). Large-scale characteristics of rapidly intensifying tropical cyclones over the bay of bengal and a rapid intensification (ri) index. Mausam, 64(1):13–24.
Kowch and Emanuel (2015). Are special processes at work in the rapid intensification of tropical cyclones? Monthly Weather Review.
Kuo, H.-C., Chang, C.-P., Yang, Y.-T., and Jiang, H.-J. (2009). Western north pacific typhoons with concentric eyewalls. Monthly Weather Review, 137(11):3758–3770.
Landsea, C. W. and Franklin, J. L. (2013). Atlantic hurricane database uncertainty and presentation of a new database format. Monthly Weather Review, 141(10):3576–3592.
Lee, C.-Y., Tippett, M. K., Sobel, A. H., and Camargo, S. J. (2016). Rapid intensification and the bimodal distribution of tropical cyclone intensity. Nature communications, 7(1):1–5.
Lin, Y.-L., Farley, R. D., and Orville, H. D. (1983). Bulk parameterization of the snow field in a cloud model. Journal of climate and applied meteorology, 22(6):1065–1092.
Lorenz, E. N. (1969a). Atmospheric predictability as revealed by naturally occurring analogues. Journal of the Atmospheric sciences, 26(4):636–646.
Lorenz, E. N. (1969b). Three approaches to atmospheric predictability. Bull. Amer. Meteor. Soc, 50(3454):349.
Lorenz, E. N. (1996). Predictability: A problem partly solved. In Proc. Seminar on predic- tability, volume 1.
Macdonald, N. J. (1968). The evidence for the existence of rossby-like waves in the hurricane vortex. Tellus, 20(1):138–150.
Madden, R. A. and Julian, P. R. (1972). Description of global-scale circulation cells in the tropics with a 40–50 day period. Journal of the atmospheric sciences, 29(6):1109–1123.
Malkus, J. S. and Riehl, H. (1960). On the dynamics and energy transformations in steady-state hurricanes. Tellus, 12(1):1–20.
Mawren, D. and Reason, C. (2017). Variability of upper-ocean characteristics and tropical cyclones in the south west indian ocean. Journal of Geophysical Research: Oceans, 122(3):2012–2028.
Melander, M., McWilliams, J., and Zabusky, N. (1987). Axisymmetrization and vorticity gradient intensification of an isolated two-dimensional vortex through filamentation. Journal of Fluid Mechanics, 178:137–159.
Mellor, G. L. and Yamada, T. (1982). Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20(4):851–875.
Miglietta, M. M., Mastrangelo, D., and Conte, D. (2015). Influence of physics parameterization schemes on the simulation of a tropical-like cyclone in the mediterranean sea. Atmospheric Research, 153:360–375.
Mohan, P. R., Srinivas, C. V., Yesubabu, V., Baskaran, R., and Venkatraman, B. (2019). Tropical cyclone simulations over bay of bengal with arw model: Sensitivity to cloud microphysics schemes. Atmospheric Research, 230:104651.
Molinari, J. and Vollaro, D. (1989). External influences on hurricane intensity. part i: Outflow layer eddy angular momentum fluxes. Journal of the Atmospheric Sciences, 46(8):1093-1105.
Möller, J. D. and Montgomery, M. T. (1999). Vortex rossby waves and hurricane intensification in a barotropic model. Journal of the atmospheric sciences, 56(11):1674–1687.
Montgomery, M., Nicholls, M., Cram, T., and Saunders, A. (2006). A vortical hot tower route to tropical cyclogenesis. Journal of the atmospheric sciences, 63(1):355–386.
Montgomery, M. T. and Kallenbach, R. J. (1997). A theory for vortex rossby-waves and its application to spiral bands and intensity changes in hurricanes. Quarterly Journal of the Royal Meteorological Society, 123(538):435–465.
Montgomery, M. T., Persing, J., and Smith, R. K. (2015). Putting to rest wishe-ful mis-conceptions for tropical cyclone intensification. Journal of Advances in Modeling Earth Systems, (1):92–109.
Montgomery, M. T., Persing, J., and Smith, R. K. (2019). On the hypothesized outflow control of tropical cyclone intensification. Quarterly Journal of the Royal Meteorological Society, 145(721):1309–1322.
Montgomery, M. T. and Smith, R. K. (2014). Paradigms for tropical cyclone intensification. Technical report, NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF METEOROLOGY.
Montgomery, M. T. and Smith, R. K. (2017). Recent developments in the fluid dynamics of tropical cyclones. Annual Review of Fluid Mechanics, 49:541–574.
Moon, Y. and Nolan, D. S. (2015). Spiral rainbands in a numerical simulation of hurricane bill (2009). part ii: Propagation of inner rainbands. Journal of the Atmospheric Sciences, 72(1):191–215.
Morrison, H., Thompson, G., and Tatarskii, V. (2009). Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Monthly weather review, 137(3):991–1007.
National Hurricane Center, S. R. S. (2012). Tropical cyclone report hurricane kenneth.
Neelin, J., Chou, C., and Su, H. (2003). Tropical drought regions in global warming and el niño teleconnections. Geophysical Research Letters, 30(24).
Nguyen, M. C., Reeder, M. J., Davidson, N. E., Smith, R. K., and Montgomery, M. T. (2011). Inner-core vacillation cycles during the intensification of hurricane katrina. Quarterly Journal of the Royal Meteorological Society, 137(657):829–844.
Noh, Y., Cheon, W., Hong, S., and Raasch, S. (2003). Improvement of the k-profile model for the planetary boundary layer based on large eddy simulation data. Boundary-layer meteorology, 107(2):401–427.
Nolan, D. S. and Farrell, B. F. (1999). The intensification of two-dimensional swirling flows by stochastic asymmetric forcing. Journal of the atmospheric sciences, 56(23):3937–3962.
Nolan, D. S. and Grasso, L. D. (2003). Nonhydrostatic, three-dimensional perturbations to balanced, hurricane-like vortices. part ii: Symmetric response and nonlinear simulations. Journal of the atmospheric sciences, 60(22):2717–2745.
Nolan, D. S., Miyamoto, Y., Wu, S.-n., and Soden, B. J. (2019). On the correlation between total condensate and moist heating in tropical cyclones and applications for diagnosing intensity. Monthly Weather Review, 147(10):3759–3784.
Nolan, D. S., Moon, Y., and Stern, D. P. (2007). Tropical cyclone intensification from asymmetric convection: Energetics and efficiency. Journal of the Atmospheric Sciences, 64(10):3377–3405.
Nolan, D. S., Zhang, J. A., and Stern, D. P. (2009). Evaluation of planetary boundary layer parameterizations in tropical cyclones by comparison of in situ observations and high- resolution simulations of hurricane isabel (2003). part i: Initialization, maximum winds,and the outer-core boundary layer. Monthly weather review, 137(11):3651–3674.
Nystrom, R. G. and Zhang, F. (2019). Practical uncertainties in the limited predictability of the record-breaking intensification of hurricane patricia (2015). Monthly Weather Review, 147(10):3535–3556.
Ooyama, K. (1969). Numerical simulation of the life cycle of tropical cyclones. Journal of the Atmospheric Sciences, 26(1):3–40.
Ooyama, K. V. (1982). Conceptual evolution of the theory and modeling of the tropical cyclone. Journal of the Meteorological Society of Japan. Ser. II, 60(1):369–380.
Pattnaik, S., Inglish, C., and Krishnamurti, T. (2011). Influence of rain-rate initialization, cloud microphysics, and cloud torques on hurricane intensity. Monthly weather review, 139(2):627–649.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12:2825–2830.
Persing, J., Montgomery, M. T., McWilliams, J. C., and Smith, R. K. (2013). Asymmetric and axisymmetric dynamics of tropical cyclones. Atmospheric Chemistry and Physics, 13(24):12299.
Ravela, S., Emanuel, K., and McLaughlin, D. (2007). Data assimilation by field alignment. Physica D: Nonlinear Phenomena, 230(1-2):127–145.
Reasor, P. D., Montgomery, M. T., Marks Jr, F. D., and Gamache, J. F. (2000). Low-wavenumber structure and evolution of the hurricane inner core observed by airborne dual-doppler radar. Monthly Weather Review, 128(6):1653–1680.
Reynolds, R. W. and Marsico, D. C. (1993). An improved real-time global sea surface temperature analysis. Journal of climate, 6(1):114–119.
Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W. (2002). An improved in situ and satellite sst analysis for climate. Journal of climate, 15(13):1609–1625.
Rogers, R. (2010). Convective-scale structure and evolution during a high-resolution simulation of tropical cyclone rapid intensification. Journal of the Atmospheric Sciences, 67(1):44–70.
Rogers, R., Reasor, P., and Lorsolo, S. (2013). Airborne doppler observations of the inner-core structural differences between intensifying and steady-state tropical cyclones. Monthly Weather Review, 141(9):2970–2991.
Rogers, R. F., Black, M. L., Chen, S. S., and Black, R. A. (2007). An evaluation of microphysics fields from mesoscale model simulations of tropical cyclones. part i: Comparisons with observations. Journal of the atmospheric sciences, 64(6):1811–1834.
Rotunno, R., Chen, Y., Wang, W., Davis, C., Dudhia, J., and Holland, G. (2009). Large-eddy simulation of an idealized tropical cyclone. Bulletin of the American Meteorological Society, 90(12):1783–1788.
Rotunno, R. and Emanuel, K. A. (1987). An air–sea interaction theory for tropical cyclones. part ii: Evolutionary study using a nonhydrostatic axisymmetric numerical model. Journal of the Atmospheric Sciences, 44(3):542–561.
Schmit, T. J., Gunshor, M. M., Menzel, W. P., Gurka, J. J., Li, J., and Bachmeier, A. S. (2005). Introducing the next-generation advanced baseline imager on goes-r. Bulletin of the American Meteorological Society, 86(8):1079–1096.
Shapiro, L. J. (1987). Month-to-month variability of the atlantic tropical circulation and its relationship to tropical storm formation. Monthly Weather Review, 115(11):2598–2614.
Shay, L. K., Goni, G. J., and Black, P. G. (2000). Effects of a warm oceanic feature on hurricane opal. Monthly Weather Review, 128(5):1366–1383.
Shu, S., Ming, J., and Chi, P. (2012). Large-scale characteristics and probability of rapidly intensifying tropical cyclones in the western north pacific basin. Weather and forecasting, 27(2):411–423.
Simpson, J., Halverson, J., Ferrier, B., Petersen, W., Simpson, R., Blakeslee, R., and Durden, S. (1998). On the role of “hot towers” in tropical cyclone formation. Meteorology and Atmospheric Physics, 67(1-4):15–35.
Sippel, J. A. and Zhang, F. (2008). A probabilistic analysis of the dynamics and predictability of tropical cyclogenesis. Journal of the Atmospheric Sciences, 65(11):3440–3459.
Sitkowski, M., Kossin, J. P., and Rozoff, C. M. (2011). Intensity and structure changes during hurricane eyewall replacement cycles. Monthly Weather Review, 139(12):3829–3847.
Smith, R. K. and Montgomery, M. T. (2015). Toward clarity on understanding tropical cyclone intensification. Journal of the Atmospheric Sciences, 72(8):3020–3031.
Smith, R. K. and Montgomery, M. T. (2016). Understanding hurricanes. Weather, 71(9):219–223.
Sriver, R. L. and Huber, M. (2007). Observational evidence for an ocean heat pump induced by tropical cyclones. Nature, 447(7144):577–580.
Stern, D. P. and Nolan, D. S. (2012). On the height of the warm core in tropical cyclones. Journal of the Atmospheric Sciences, 69(5):1657–1680.
Tao, D. and Zhang, F. (2015). Effects of vertical wind shear on the predictability of tropical cyclones: Practical versus intrinsic limit. Journal of Advances in Modeling Earth Systems, 7(4):1534–1553.
Tao, W.-K., Shi, J. J., Chen, S. S., Lang, S., Lin, P.-L., Hong, S.-Y., Peters-Lidard, C., and Hou, A. (2011). The impact of microphysical schemes on hurricane intensity and track. Asia-Pacific Journal of Atmospheric Sciences, 47(1):1–16.
Terwey, W. D. and Montgomery, M. T. (2008). Secondary eyewall formation in two idealized, full-physics modeled hurricanes. Journal of Geophysical Research: Atmospheres, 113(D12).
Torn, R. D. (2016). Evaluation of atmosphere and ocean initial condition uncertainty and stochastic exchange coefficients on ensemble tropical cyclone intensity forecasts. Monthly Weather Review, 144(9):3487–3506.
Trabing, B. C. and Bell, M. M. (2020). Understanding error distributions of hurricane intensity forecasts during rapid intensity changes. Weather and Forecasting, pages 1–43.
Visser, K., Thunell, R., and Stott, L. (2003). Magnitude and timing of temperature change in the indo-pacific warm pool during deglaciation. Nature, 421(6919):152–155.
Wang, B. and Chan, J. C. (2002). How strong enso events affect tropical storm activity over the western north pacific. Journal of Climate, 15(13):1643–1658.
Wang, C., Wang, X., Weisberg, R. H., and Black, M. L. (2017). Variability of tropical cyclone rapid intensification in the north atlantic and its relationship with climate variations. Climate Dynamics, 49(11-12):3627–3645.
Wang, X., Wang, C., Zhang, L., and Wang, X. (2015). Multidecadal variability of tropical cyclone rapid intensification in the western north pacific. Journal of Climate, 28(9):3806–3820.
Wang, Y. (2002a). An explicit simulation of tropical cyclones with a triply nested movable mesh primitive equation model: Tcm3. part ii: Model refinements and sensitivity to cloud microphysics parameterization. Monthly weather review, 130(12):3022–3036.
Wang, Y. (2002b). Vortex rossby waves in a numerically simulated tropical cyclone. part ii: The role in tropical cyclone structure and intensity changes. Journal of the atmospheric sciences, 59(7):1239–1262.
Wang, Y. and Wu, C.-C. (2004). Current understanding of tropical cyclone structure and intensity changes–a review. Meteorology and Atmospheric Physics, 87(4):257–278.
Wheeler, M. C. and Hendon, H. H. (2004). An all-season real-time multivariate mjo index: Development of an index for monitoring and prediction. Monthly weather review, 132(8):1917–1932.
Willoughby, H. E., Jin, H.-L., Lord, S. J., and Piotrowicz, J. M. (1984). Hurricane structure and evolution as simulated by an axisymmetric, nonhydrostatic numerical model. Journal of the atmospheric sciences, 41(7):1169–1186.
Wu, L., Su, H., Fovell, R. G., Dunkerton, T. J., Wang, Z., and Kahn, B. H. (2015). Impact of environmental moisture on tropical cyclone intensification. Atmospheric Chemistry and Physics, 15(24):14041–14053.
Wu, L., Su, H., Fovell, R. G., Wang, B., Shen, J. T., Kahn, B. H., Hristova-Veleva, S. M., Lambrigtsen, B. H., Fetzer, E. J., and Jiang, J. H. (2012). Relationship of environmental relative humidity with north atlantic tropical cyclone intensity and intensification rate. Geophysical research letters, 39(20).
Ying, Y. and Zhang, Q. (2012). A modeling study on tropical cyclone structural changes in response to ambient moisture variations. Journal of the Meteorological Society of Japan. Ser. II, 90(5):755–770.
Zapata Henao, M., Hoyos Ortiz, C., and Cardona, Y. (2018). Climatological atmosphere-ocean response to tropical cyclone passage and the role of turbulent heat fluxes. In AGU Fall Meeting Abstracts.
Zhang, F. and Emanuel, K. (2016). On the role of surface fluxes and wishe in tropical cyclone intensification. Journal of the Atmospheric Sciences, 73(5):2011–2019.
Zhang, F. and Tao, D. (2013). Effects of vertical wind shear on the predictability of tropical cyclones. Journal of the Atmospheric Sciences, 70(3):975–983.
Zhao, H., Yoshida, R., and Raga, G. (2015). Impact of the madden–julian oscillation on western north pacific tropical cyclogenesis associated with large-scale patterns. Journal of Applied Meteorology and Climatology, 54(7):1413–1429.
Zhong, Q., Li, J., Zhang, L., Ding, R., and Li, B. (2018). Predictability of tropical cyclone intensity over the western north pacific using the ibtracs dataset. Monthly Weather Review, 146(9):2741–2755.
Zhu, P., Menelaou, K., and Zhu, Z. (2014). Impact of subgrid-scale vertical turbulent mixing on eyewall asymmetric structures and mesovortices of hurricanes. Quarterly Journal of the Royal Meteorological Society, 140(679):416–438.
Zipser, E. J. and Gautier, C. (1978). Mesoscale events within a gate tropical depression. Monthly Weather Review, 106(6):789–805.
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dc.publisher.spa.fl_str_mv 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 David27686cec87756851bf3b2f6ce68e0839600Pérez Carrasquilla, Jhayron Stevenc2d5741b0be42dfbbe68067e76a8eb3a2021-06-24T18:56:36Z2021-06-24T18:56:36Z2021https://repositorio.unal.edu.co/handle/unal/79714Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/Ilustraciones, mapasUnderstanding the full range of dynamic and thermodynamic mechanisms that trigger or intensify tropical cyclones remains a significant challenge for tropical meteorology. Over the past five decades, there have been substantial scientific efforts, with a wide range of perspectives, aimed to the construction of a robust theoretical framework of the problem, as well as the development of crucial computational and observational resources that have improved significantly our understanding ot these deadly weather systems. Despite the advances, there are still unanswered questions and a high degree of uncertainty about the relative importance and implications of the processes modulating the intensity of the storms, and considerable room for improvement in tropical storm forecasting. During the present thesis, the problem of intensification of tropical cyclones is approa ched from three individual, but related among them studies. In Chapter 2, we discuss the environment-based variability and predictability of tropical cyclone intensity changes, using historical data, we explore the intrinsic error growth of the intensity changes, and the impact of the environment over these weather systems. In Chapter 3, we present a modeling approach in order to contribute to the understanding of the TCs inner core dynamics, focusing mainly on the characteristics and variability of small-scale convective features, and their main impacts over the symmetric structure of the storms. There, we propose a hypothesis for the role of the small-scale convective features on TCs intensification, all under the light of the existing theoretical framework. In chapter 4, we present a preliminary approach for understanding the temporal variability of VHTs and updrafts based on satellite observations. (Tomado de la fuente)Comprender la gama completa de mecanismos dinámicos y termodinámicos que desencadenan o intensifican los ciclones tropicales sigue siendo un desafío importante para la meteorología tropical. Durante las últimas cinco décadas, se han realizado importantes esfuerzos científicos, con una amplia gama de perspectivas, dirigidos a la construcción de un marco teórico robusto del problema, así como al desarrollo de recursos computacionales y de observación cruciales que han mejorado significativamente nuestra comprensión. ot estos sistemas climáticos mortales. A pesar de los avances, aún quedan preguntas sin respuesta y un alto grado de incertidumbre sobre la importancia relativa e implicaciones de los procesos que modulan la intensidad de las tormentas, y un margen considerable para mejorar el pronóstico de tormentas tropicales. Durante la presente tesis, el problema de la intensificación de los ciclones tropicales se aborda a partir de tres estudios individuales, pero relacionados entre ellos. En el Capítulo 2, discutimos la variabilidad basada en el medio ambiente y la previsibilidad de los cambios de intensidad de los ciclones tropicales, utilizando datos históricos, exploramos el crecimiento del error intrínseco de los cambios de intensidad y el impacto del medio ambiente sobre estos sistemas meteorológicos. En el Capítulo 3, presentamos un enfoque de modelado para contribuir a la comprensión de la dinámica del núcleo interno de las CT, centrándonos principalmente en las características y variabilidad de las características convectivas a pequeña escala, y sus principales impactos sobre la estructura simétrica de las tormentas. Allí, proponemos una hipótesis sobre el papel de las características convectivas a pequeña escala en la intensificación de las CT, todo ello a la luz del marco teórico existente. En el capítulo 4, presentamos un enfoque preliminar para comprender la variabilidad temporal de los VHT y las corrientes ascendentes basados ​​en observaciones satelitales. (Tomado de la fuente)MaestríaMaestría en Ingeniería - Recursos Hidráulicos142 páginasapplication/pdfengUniversidad Nacional de ColombiaUniversidad 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, meteorología530 - Física::532 - Mecánica de fluidos620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulicaCiclonesCiclones tropicalesConvección húmedaIntensificación rápidaTropical cyclonesMoist convectionRapid intensificationIntensificación rápida de ciclones tropicales: análisis de su variabilidad espacio-temporal y su respuesta a dinámicas del núcleo interno y forzamiento externoTropical cyclone rapid intensification: spatio-temporal variability, inner-core dynamics and environmental control.Trabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAnthes, R. A., Kuo, Y.-H., Baumhefner, D. P., Errico, R. M., and Bettge, T. W. (1985). Predictability of mesoscale atmospheric motions. In Advances in geophysics, volume 28, pages 159–202. Elsevier.Bell, M. M., Montgomery, M. T., and Emanuel, K. A. (2012). Air–sea enthalpy and momentum exchange at major hurricane wind speeds observed during cblast. Journal of the Atmospheric Sciences, 69(11):3197–3222.Bister, M. and Emanuel, K. A. (1998). Dissipative heating and hurricane intensity. Meteorology and Atmospheric Physics, 65(3-4):233–240.Bosart, L. F., Bracken, W. E., Molinari, J., Velden, C. S., and Black, P. G. (2000). Environmental influences on the rapid intensification of hurricane opal (1995) over the gulf of mexico. Monthly Weather Review, 128(2):322–352.Bryan, G. H. (2012). Effects of surface exchange coefficients and turbulence length scales on the intensity and structure of numerically simulated hurricanes. Monthly weather review, 140(4):1125–1143.Bryan, G. H. and Fritsch, J. M. (2002). A benchmark simulation for moist nonhydrostatic numerical models. Monthly Weather Review, 130(12):2917–2928.Camargo, S. J., Robertson, A. W., Barnston, A. G., and Ghil, M. (2008). Clustering of eastern north pacific tropical cyclone tracks: Enso and mjo effects. Geochemistry, Geophysics, Geosystems, 9(6).Camargo, S. J., Robertson, A. W., Gaffney, S. J., Smyth, P., and Ghil, M. (2007). Cluster analysis of typhoon tracks. part ii: Large-scale circulation and enso. Journal of climate, 20(14):3654–3676.Camargo, S. J. and Sobel, A. H. (2005). Western north pacific tropical cyclone intensity and enso. Journal of Climate, 18(15):2996–3006.Carr III, L. and Williams, R. (1989). Barotropic vortex stability to perturbations from axisymmetry. Journal of the atmospheric sciences, 46(20):3177–3191.Chan, J. C. (2000). Tropical cyclone activity over the western north pacific associated with el niño and la niña events. Journal of Climate, 13(16):2960–2972.Charney, J. G. and Eliassen, A. (1964). On the growth of the hurricane depression. Journal of the Atmospheric Sciences, 21(1):68–75.Chen, B., Li, J., and Ding, R. (2006). Nonlinear local lyapunov exponent and atmospheric predictability research. Science in China Series D: Earth Sciences, 49(10):1111–1120.Chiang, J. C. and Sobel, A. H. (2002). Tropical tropospheric temperature variations caused by enso and their influence on the remote tropical climate. Journal of climate, 15(18):2616– 2631.Chu, P. (2004). Enso and tropical cyclone activity. hurricanes and typhoons: Past, present, and potential, rj murnane and k.-b. liu, eds. Columbia University Press, 297:332.Cione, J. J. and Uhlhorn, E. W. (2003). Sea surface temperature variability in hurricanes: Implications with respect to intensity change. Monthly Weather Review, 131(8).Dare, R. A. and McBride, J. L. (2011). Sea surface temperature response to tropical cyclones. Monthly Weather Review, 139(12):3798–3808.Davis, C., Wang, W., Chen, S. S., Chen, Y., Corbosiero, K., DeMaria, M., Dudhia, J., Holland, G., Klemp, J., Michalakes, J., et al. (2008). Prediction of landfalling hurricanes with the advanced hurricane wrf model. Monthly weather review, 136(6):1990–2005.Davis, C. A. and Emanuel, K. A. (1991). Potential vorticity diagnostics of cyclogenesis. Monthly weather review, 119(8):1929–1953.DeMaria, M. and Kaplan, J. (1994). A statistical hurricane intensity prediction scheme (ships) for the atlantic basin. Weather and Forecasting, 9(2):209–220.DeMaria, M., Kaplan, J., and Baik, J.-J. (1993). Upper-level eddy angular momentum fluxes and tropical cyclone intensity change. Journal of the atmospheric sciences, 50(8):1133–1147.DeMaria, M., Sampson, C. R., Knaff, J. A., and Musgrave, K. D. (2014). Is tropical cyclone intensity guidance improving? Bulletin of the American Meteorological Society, 95(3):387–398.Emanuel, K., DesAutels, C., Holloway, C., and Korty, R. (2004). Environmental control of tropical cyclone intensity. Journal of the atmospheric sciences, 61(7):843–858.Emanuel, K. and Zhang, F. (2016). On the predictability and error sources of tropical cyclone intensity forecasts. Journal of the Atmospheric Sciences, 73(9):3739–3747.Emanuel, K. A. (1986). An air-sea interaction theory for tropical cyclones. part i: Steady- state maintenance. Journal of the Atmospheric Sciences, 43(6):585–605.Emanuel, K. A. (1989). Dynamical theories of tropical. Australian Meteorological Magazine, 37(1).Fan, Y., Ginis, I., and Hara, T. (2009). The effect of wind–wave–current interaction on air–sea momentum fluxes and ocean response in tropical cyclones. Journal of Physical Oceanography, 39(4):1019–1034.Finocchio, P. M. and Majumdar, S. J. (2017). The predictability of idealized tropical cyclones in environments with time-varying vertical wind shear. Journal of Advances in Modeling Earth Systems, 9(8):2836–2862.Frank, W. M. and Ritchie, E. A. (2001). Effects of vertical wind shear on the intensity and structure of numerically simulated hurricanes. Monthly weather review, 129(9):2249–2269.Frank, W. M. and Roundy, P. E. (2006). The role of tropical waves in tropical cyclogenesis. Monthly W eather Review, 134(9):2397–2417.Fudeyasu, H., Ito, K., and Miyamoto, Y. (2018). Characteristics of tropical cyclone rapid intensification over the western north pacific. Journal of Climate, 31(21):8917–8930.Giannini, A., Chiang, J. C., Cane, M. A., Kushnir, Y., and Seager, R. (2001). The enso teleconnection to the tropical atlantic ocean: Contributions of the remote and local ssts to rainfall variability in the tropical americas. Journal of Climate, 14(24):4530–4544.Girishkumar, M. and Ravichandran, M. (2012). The influences of enso on tropical cyclone activity in the bay of bengal during october–december. Journal of Geophysical Research: Oceans, 117(C2).Girishkumar, M., Suprit, K., Vishnu, S., Prakash, V. T., and Ravichandran, M. (2015). The role of enso and mjo on rapid intensification of tropical cyclones in the bay of bengal during october–december. Theoretical and Applied Climatology, 120(3-4):797–810.Gloeckler III, L. C. and Roundy, P. E. (2019). A statistical analysis of relationships between western north pacific tropical cyclones and extratropical circulation patterns accompanying the madden–julian oscillation. Journal of the Atmospheric Sciences, 76(2):583–604.Goldenberg, S. B. and Shapiro, L. J. (1996). Physical mechanisms for the association of el niño and west african rainfall with atlantic major hurricane activity. Journal of Climate, 9(6):1169–1187.Goodman, S. J., Blakeslee, R. J., Koshak, W. J., Mach, D., Bailey, J., Buechler, D., Carey, L., Schultz, C., Bateman, M., McCaul Jr, E., et al. (2013). The goes-r geostationary lightning mapper (glm). Atmospheric research, 125:34–49.Gray, W. M. (1984). Atlantic seasonal hurricane frequency. part i: El niño and 30 mb quasi-biennial oscillation influences. Monthly Weather Review, 112(9):1649–1668.Green, B. W. and Zhang, F. (2014). Sensitivity of tropical cyclone simulations to parametric uncertainties in air–sea fluxes and implications for parameter estimation. Monthly Weather Review, 142(6):2290–2308.Green, B. W. and Zhang, F. (2015). Numerical simulations of h urricane k atrina (2005) in the turbulent gray zone. Journal of Advances in Modeling Earth Systems, 7(1):142–161.Guimond, S. R., Heymsfield, G. M., and Turk, F. J. (2010). Multiscale observations of hurricane dennis (2005): The effects of hot towers on rapid intensification. Journal of the atmospheric sciences, 67(3):633–654.Guinn, T. A. and Schubert, W. H. (1993). Hurricane spiral bands. Journal of the atmospheric sciences, 50(20):3380–3403.Hakim, G. J. (2013). The variability and predictability of axisymmetric hurricanes in statistical equilibrium. Journal of the atmospheric sciences, 70(4):993–1005.Hanley, D., Molinari, J., and Keyser, D. (2001). A composite study of the interactions between tropical cyclones and upper-tropospheric troughs. Monthly weather review, 129(10):2570–2584.Hendricks, E. A., Montgomery, M. T., and Davis, C. A. (2004). The role of “vortical” hot towers in the formation of tropical cyclone diana (1984). Journal of the atmospheric sciences, 1(11):1209–1232.Holliday, C. R. and Thompson, A. H. (1979). Climatological characteristics of rapidly intensifying typhoons. Monthly Weather Review, 107(8):1022–1034.Hong, X., Chang, S. W., Raman, S., Shay, L. K., and Hodur, R. (2000). The interaction between hurricane opal (1995) and a warm core ring in the gulf of mexico. Monthly Weather Review, 28(5):1347–1365.Houze Jr, R. A., Lee, W.-C., and Bell, M. M. (2009). Convective contribution to the genesis of hurricane ophelia (2005). Monthly Weather Review, 137(9):2778–2800.Irwin III, R. P. and Davis, R. E. (1999). The relationship between the southern oscillation index and tropical cyclone tracks in the eastern north pacific. Geophysical research letters, 26(15):2251–2254.Janjić, Z. I. (1990). The step-mountain coordinate: Physical package. Monthly Weather Review, 118(7):1429–1443.Jordan, C. L. (1958). Mean soundings for the west indies area. Journal of Meteorology, 15(1):91–97.Judt, F. and Chen, S. S. (2016). Predictability and dynamics of tropical cyclone rapid intensification deduced from high-resolution stochastic ensembles. Monthly Weather Review, 144(11):4395–4420.Judt, F., Chen, S. S., and Berner, J. (2016). Predictability of tropical cyclone intensity: scaledependent forecast error growth in high-resolution stochastic kinetic-energy backscatter ensembles. Quarterly Journal of the Royal Meteorological Society, 142(694):43–57.Kaplan, John, Rozoff, Mark, Sampson, R., C., Kossin, P., J., J., J., P., J., and et al. (2015). Evaluating environmental impacts on tropical cyclone rapid intensification predictability utilizing statistical models. Weather and Forecasting.Kaplan, J. and DeMaria, M. (2003). Large-scale characteristics of rapidly intensifying tropical cyclones in the north atlantic basin. Weather and forecasting, 18(6):1093–1108.Kaplan, J., DeMaria, M., and Knaff, J. A. (2010). A revised tropical cyclone rapid intensification index for the atlantic and eastern north pacific basins. Weather and forecasting, 25(1):220–241.Kessler, E. (1969). On the distribution and continuity of water substance in atmosphericcirculations. In On the distribution and continuity of water substance in atmospheric circulations, pages 1–84. Springer.Khain, A., Lynn, B., and Shpund, J. (2016). High resolution wrf simulations of hurricane irene: Sensitivity to aerosols and choice of microphysical schemes. Atmospheric Research, 167:129–145.Kieu, C. Q. and Moon, Z. (2016). Hurricane intensity predictability. Bulletin of the American Meteorological Society, 97(10):1847–1857.Kim, H.-M., Webster, P. J., and Curry, J. A. (2011). Modulation of north pacific tropical cyclone activity by three phases of enso. Journal of Climate, 24(6):1839–1849.Kimball, S. K. (2006). A modeling study of hurricane landfall in a dry environment. Monthly weather review, 134(7):1901–1918.Klemp, J. B. and Wilhelmson, R. B. (1978). The simulation of three-dimensional convective storm dynamics. Journal of the Atmospheric Sciences, 35(6):1070–1096.Klotzbach, P. J. (2010). On the madden–julian oscillation–atlantic hurricane relationship. Journal of Climate, 23(2):282–293.Klotzbach, P. J. (2012). El niño-southern oscillation, the madden-julian oscillation and atlantic basin tropical cyclone rapid intensification. Journal of Geophysical Research: Atmospheres, 117(D14).Klotzbach, P. J. (2014). The madden–julian oscillation’s impacts on worldwide tropical cyclone activity. Journal of Climate, 27(6):2317–2330.Kossin, J. P. and Eastin, M. D. (2001). Two distinct regimes in the kinematic and thermodynamic structure of the hurricane eye and eyewall. Journal of the atmospheric sciences, 58(9):1079–1090.Kotal, S. and Roy Bhowmik, S. (2013). Large-scale characteristics of rapidly intensifying tropical cyclones over the bay of bengal and a rapid intensification (ri) index. Mausam, 64(1):13–24.Kowch and Emanuel (2015). Are special processes at work in the rapid intensification of tropical cyclones? Monthly Weather Review.Kuo, H.-C., Chang, C.-P., Yang, Y.-T., and Jiang, H.-J. (2009). Western north pacific typhoons with concentric eyewalls. Monthly Weather Review, 137(11):3758–3770.Landsea, C. W. and Franklin, J. L. (2013). Atlantic hurricane database uncertainty and presentation of a new database format. Monthly Weather Review, 141(10):3576–3592.Lee, C.-Y., Tippett, M. K., Sobel, A. H., and Camargo, S. J. (2016). Rapid intensification and the bimodal distribution of tropical cyclone intensity. Nature communications, 7(1):1–5.Lin, Y.-L., Farley, R. D., and Orville, H. D. (1983). Bulk parameterization of the snow field in a cloud model. Journal of climate and applied meteorology, 22(6):1065–1092.Lorenz, E. N. (1969a). Atmospheric predictability as revealed by naturally occurring analogues. Journal of the Atmospheric sciences, 26(4):636–646.Lorenz, E. N. (1969b). Three approaches to atmospheric predictability. Bull. Amer. Meteor. Soc, 50(3454):349.Lorenz, E. N. (1996). Predictability: A problem partly solved. In Proc. Seminar on predic- tability, volume 1.Macdonald, N. J. (1968). The evidence for the existence of rossby-like waves in the hurricane vortex. Tellus, 20(1):138–150.Madden, R. A. and Julian, P. R. (1972). Description of global-scale circulation cells in the tropics with a 40–50 day period. Journal of the atmospheric sciences, 29(6):1109–1123.Malkus, J. S. and Riehl, H. (1960). On the dynamics and energy transformations in steady-state hurricanes. Tellus, 12(1):1–20.Mawren, D. and Reason, C. (2017). Variability of upper-ocean characteristics and tropical cyclones in the south west indian ocean. Journal of Geophysical Research: Oceans, 122(3):2012–2028.Melander, M., McWilliams, J., and Zabusky, N. (1987). Axisymmetrization and vorticity gradient intensification of an isolated two-dimensional vortex through filamentation. Journal of Fluid Mechanics, 178:137–159.Mellor, G. L. and Yamada, T. (1982). Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20(4):851–875.Miglietta, M. M., Mastrangelo, D., and Conte, D. (2015). Influence of physics parameterization schemes on the simulation of a tropical-like cyclone in the mediterranean sea. Atmospheric Research, 153:360–375.Mohan, P. R., Srinivas, C. V., Yesubabu, V., Baskaran, R., and Venkatraman, B. (2019). Tropical cyclone simulations over bay of bengal with arw model: Sensitivity to cloud microphysics schemes. Atmospheric Research, 230:104651.Molinari, J. and Vollaro, D. (1989). External influences on hurricane intensity. part i: Outflow layer eddy angular momentum fluxes. Journal of the Atmospheric Sciences, 46(8):1093-1105.Möller, J. D. and Montgomery, M. T. (1999). Vortex rossby waves and hurricane intensification in a barotropic model. Journal of the atmospheric sciences, 56(11):1674–1687.Montgomery, M., Nicholls, M., Cram, T., and Saunders, A. (2006). A vortical hot tower route to tropical cyclogenesis. Journal of the atmospheric sciences, 63(1):355–386.Montgomery, M. T. and Kallenbach, R. J. (1997). A theory for vortex rossby-waves and its application to spiral bands and intensity changes in hurricanes. Quarterly Journal of the Royal Meteorological Society, 123(538):435–465.Montgomery, M. T., Persing, J., and Smith, R. K. (2015). Putting to rest wishe-ful mis-conceptions for tropical cyclone intensification. Journal of Advances in Modeling Earth Systems, (1):92–109.Montgomery, M. T., Persing, J., and Smith, R. K. (2019). On the hypothesized outflow control of tropical cyclone intensification. Quarterly Journal of the Royal Meteorological Society, 145(721):1309–1322.Montgomery, M. T. and Smith, R. K. (2014). Paradigms for tropical cyclone intensification. Technical report, NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF METEOROLOGY.Montgomery, M. T. and Smith, R. K. (2017). Recent developments in the fluid dynamics of tropical cyclones. Annual Review of Fluid Mechanics, 49:541–574.Moon, Y. and Nolan, D. S. (2015). Spiral rainbands in a numerical simulation of hurricane bill (2009). part ii: Propagation of inner rainbands. Journal of the Atmospheric Sciences, 72(1):191–215.Morrison, H., Thompson, G., and Tatarskii, V. (2009). Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Monthly weather review, 137(3):991–1007.National Hurricane Center, S. R. S. (2012). Tropical cyclone report hurricane kenneth.Neelin, J., Chou, C., and Su, H. (2003). Tropical drought regions in global warming and el niño teleconnections. Geophysical Research Letters, 30(24).Nguyen, M. C., Reeder, M. J., Davidson, N. E., Smith, R. K., and Montgomery, M. T. (2011). Inner-core vacillation cycles during the intensification of hurricane katrina. Quarterly Journal of the Royal Meteorological Society, 137(657):829–844.Noh, Y., Cheon, W., Hong, S., and Raasch, S. (2003). Improvement of the k-profile model for the planetary boundary layer based on large eddy simulation data. Boundary-layer meteorology, 107(2):401–427.Nolan, D. S. and Farrell, B. F. (1999). The intensification of two-dimensional swirling flows by stochastic asymmetric forcing. Journal of the atmospheric sciences, 56(23):3937–3962.Nolan, D. S. and Grasso, L. D. (2003). Nonhydrostatic, three-dimensional perturbations to balanced, hurricane-like vortices. part ii: Symmetric response and nonlinear simulations. Journal of the atmospheric sciences, 60(22):2717–2745.Nolan, D. S., Miyamoto, Y., Wu, S.-n., and Soden, B. J. (2019). On the correlation between total condensate and moist heating in tropical cyclones and applications for diagnosing intensity. Monthly Weather Review, 147(10):3759–3784.Nolan, D. S., Moon, Y., and Stern, D. P. (2007). Tropical cyclone intensification from asymmetric convection: Energetics and efficiency. Journal of the Atmospheric Sciences, 64(10):3377–3405.Nolan, D. S., Zhang, J. A., and Stern, D. P. (2009). Evaluation of planetary boundary layer parameterizations in tropical cyclones by comparison of in situ observations and high- resolution simulations of hurricane isabel (2003). part i: Initialization, maximum winds,and the outer-core boundary layer. Monthly weather review, 137(11):3651–3674.Nystrom, R. G. and Zhang, F. (2019). Practical uncertainties in the limited predictability of the record-breaking intensification of hurricane patricia (2015). Monthly Weather Review, 147(10):3535–3556.Ooyama, K. (1969). Numerical simulation of the life cycle of tropical cyclones. Journal of the Atmospheric Sciences, 26(1):3–40.Ooyama, K. V. (1982). Conceptual evolution of the theory and modeling of the tropical cyclone. Journal of the Meteorological Society of Japan. Ser. II, 60(1):369–380.Pattnaik, S., Inglish, C., and Krishnamurti, T. (2011). Influence of rain-rate initialization, cloud microphysics, and cloud torques on hurricane intensity. Monthly weather review, 139(2):627–649.Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12:2825–2830.Persing, J., Montgomery, M. T., McWilliams, J. C., and Smith, R. K. (2013). Asymmetric and axisymmetric dynamics of tropical cyclones. Atmospheric Chemistry and Physics, 13(24):12299.Ravela, S., Emanuel, K., and McLaughlin, D. (2007). Data assimilation by field alignment. Physica D: Nonlinear Phenomena, 230(1-2):127–145.Reasor, P. D., Montgomery, M. T., Marks Jr, F. D., and Gamache, J. F. (2000). Low-wavenumber structure and evolution of the hurricane inner core observed by airborne dual-doppler radar. Monthly Weather Review, 128(6):1653–1680.Reynolds, R. W. and Marsico, D. C. (1993). An improved real-time global sea surface temperature analysis. Journal of climate, 6(1):114–119.Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W. (2002). An improved in situ and satellite sst analysis for climate. Journal of climate, 15(13):1609–1625.Rogers, R. (2010). Convective-scale structure and evolution during a high-resolution simulation of tropical cyclone rapid intensification. Journal of the Atmospheric Sciences, 67(1):44–70.Rogers, R., Reasor, P., and Lorsolo, S. (2013). Airborne doppler observations of the inner-core structural differences between intensifying and steady-state tropical cyclones. Monthly Weather Review, 141(9):2970–2991.Rogers, R. F., Black, M. L., Chen, S. S., and Black, R. A. (2007). An evaluation of microphysics fields from mesoscale model simulations of tropical cyclones. part i: Comparisons with observations. Journal of the atmospheric sciences, 64(6):1811–1834.Rotunno, R., Chen, Y., Wang, W., Davis, C., Dudhia, J., and Holland, G. (2009). Large-eddy simulation of an idealized tropical cyclone. Bulletin of the American Meteorological Society, 90(12):1783–1788.Rotunno, R. and Emanuel, K. A. (1987). An air–sea interaction theory for tropical cyclones. part ii: Evolutionary study using a nonhydrostatic axisymmetric numerical model. Journal of the Atmospheric Sciences, 44(3):542–561.Schmit, T. J., Gunshor, M. M., Menzel, W. P., Gurka, J. J., Li, J., and Bachmeier, A. S. (2005). Introducing the next-generation advanced baseline imager on goes-r. Bulletin of the American Meteorological Society, 86(8):1079–1096.Shapiro, L. J. (1987). Month-to-month variability of the atlantic tropical circulation and its relationship to tropical storm formation. Monthly Weather Review, 115(11):2598–2614.Shay, L. K., Goni, G. J., and Black, P. G. (2000). Effects of a warm oceanic feature on hurricane opal. Monthly Weather Review, 128(5):1366–1383.Shu, S., Ming, J., and Chi, P. (2012). Large-scale characteristics and probability of rapidly intensifying tropical cyclones in the western north pacific basin. Weather and forecasting, 27(2):411–423.Simpson, J., Halverson, J., Ferrier, B., Petersen, W., Simpson, R., Blakeslee, R., and Durden, S. (1998). On the role of “hot towers” in tropical cyclone formation. Meteorology and Atmospheric Physics, 67(1-4):15–35.Sippel, J. A. and Zhang, F. (2008). A probabilistic analysis of the dynamics and predictability of tropical cyclogenesis. Journal of the Atmospheric Sciences, 65(11):3440–3459.Sitkowski, M., Kossin, J. P., and Rozoff, C. M. (2011). Intensity and structure changes during hurricane eyewall replacement cycles. Monthly Weather Review, 139(12):3829–3847.Smith, R. K. and Montgomery, M. T. (2015). Toward clarity on understanding tropical cyclone intensification. Journal of the Atmospheric Sciences, 72(8):3020–3031.Smith, R. K. and Montgomery, M. T. (2016). Understanding hurricanes. Weather, 71(9):219–223.Sriver, R. L. and Huber, M. (2007). Observational evidence for an ocean heat pump induced by tropical cyclones. Nature, 447(7144):577–580.Stern, D. P. and Nolan, D. S. (2012). On the height of the warm core in tropical cyclones. Journal of the Atmospheric Sciences, 69(5):1657–1680.Tao, D. and Zhang, F. (2015). Effects of vertical wind shear on the predictability of tropical cyclones: Practical versus intrinsic limit. Journal of Advances in Modeling Earth Systems, 7(4):1534–1553.Tao, W.-K., Shi, J. J., Chen, S. S., Lang, S., Lin, P.-L., Hong, S.-Y., Peters-Lidard, C., and Hou, A. (2011). The impact of microphysical schemes on hurricane intensity and track. Asia-Pacific Journal of Atmospheric Sciences, 47(1):1–16.Terwey, W. D. and Montgomery, M. T. (2008). Secondary eyewall formation in two idealized, full-physics modeled hurricanes. Journal of Geophysical Research: Atmospheres, 113(D12).Torn, R. D. (2016). Evaluation of atmosphere and ocean initial condition uncertainty and stochastic exchange coefficients on ensemble tropical cyclone intensity forecasts. Monthly Weather Review, 144(9):3487–3506.Trabing, B. C. and Bell, M. M. (2020). Understanding error distributions of hurricane intensity forecasts during rapid intensity changes. Weather and Forecasting, pages 1–43.Visser, K., Thunell, R., and Stott, L. (2003). Magnitude and timing of temperature change in the indo-pacific warm pool during deglaciation. Nature, 421(6919):152–155.Wang, B. and Chan, J. C. (2002). How strong enso events affect tropical storm activity over the western north pacific. Journal of Climate, 15(13):1643–1658.Wang, C., Wang, X., Weisberg, R. H., and Black, M. L. (2017). Variability of tropical cyclone rapid intensification in the north atlantic and its relationship with climate variations. Climate Dynamics, 49(11-12):3627–3645.Wang, X., Wang, C., Zhang, L., and Wang, X. (2015). Multidecadal variability of tropical cyclone rapid intensification in the western north pacific. Journal of Climate, 28(9):3806–3820.Wang, Y. (2002a). An explicit simulation of tropical cyclones with a triply nested movable mesh primitive equation model: Tcm3. part ii: Model refinements and sensitivity to cloud microphysics parameterization. Monthly weather review, 130(12):3022–3036.Wang, Y. (2002b). Vortex rossby waves in a numerically simulated tropical cyclone. part ii: The role in tropical cyclone structure and intensity changes. Journal of the atmospheric sciences, 59(7):1239–1262.Wang, Y. and Wu, C.-C. (2004). Current understanding of tropical cyclone structure and intensity changes–a review. Meteorology and Atmospheric Physics, 87(4):257–278.Wheeler, M. C. and Hendon, H. H. (2004). An all-season real-time multivariate mjo index: Development of an index for monitoring and prediction. Monthly weather review, 132(8):1917–1932.Willoughby, H. E., Jin, H.-L., Lord, S. J., and Piotrowicz, J. M. (1984). Hurricane structure and evolution as simulated by an axisymmetric, nonhydrostatic numerical model. Journal of the atmospheric sciences, 41(7):1169–1186.Wu, L., Su, H., Fovell, R. G., Dunkerton, T. J., Wang, Z., and Kahn, B. H. (2015). Impact of environmental moisture on tropical cyclone intensification. Atmospheric Chemistry and Physics, 15(24):14041–14053.Wu, L., Su, H., Fovell, R. G., Wang, B., Shen, J. T., Kahn, B. H., Hristova-Veleva, S. M., Lambrigtsen, B. H., Fetzer, E. J., and Jiang, J. H. (2012). Relationship of environmental relative humidity with north atlantic tropical cyclone intensity and intensification rate. Geophysical research letters, 39(20).Ying, Y. and Zhang, Q. (2012). A modeling study on tropical cyclone structural changes in response to ambient moisture variations. Journal of the Meteorological Society of Japan. Ser. II, 90(5):755–770.Zapata Henao, M., Hoyos Ortiz, C., and Cardona, Y. (2018). Climatological atmosphere-ocean response to tropical cyclone passage and the role of turbulent heat fluxes. In AGU Fall Meeting Abstracts.Zhang, F. and Emanuel, K. (2016). On the role of surface fluxes and wishe in tropical cyclone intensification. Journal of the Atmospheric Sciences, 73(5):2011–2019.Zhang, F. and Tao, D. (2013). Effects of vertical wind shear on the predictability of tropical cyclones. Journal of the Atmospheric Sciences, 70(3):975–983.Zhao, H., Yoshida, R., and Raga, G. (2015). Impact of the madden–julian oscillation on western north pacific tropical cyclogenesis associated with large-scale patterns. Journal of Applied Meteorology and Climatology, 54(7):1413–1429.Zhong, Q., Li, J., Zhang, L., Ding, R., and Li, B. (2018). Predictability of tropical cyclone intensity over the western north pacific using the ibtracs dataset. Monthly Weather Review, 146(9):2741–2755.Zhu, P., Menelaou, K., and Zhu, Z. (2014). Impact of subgrid-scale vertical turbulent mixing on eyewall asymmetric structures and mesovortices of hurricanes. Quarterly Journal of the Royal Meteorological Society, 140(679):416–438.Zipser, E. J. and Gautier, C. (1978). Mesoscale events within a gate tropical depression. Monthly Weather Review, 106(6):789–805.EspecializadoUniversidad Nacional de Colombia, Sede Medellín, Facultad de Minas, Departamento de Geociencias y Medio Ambiente.Sistema de Alerta Temprana de Medellín y el Valle de Aburrá, SIATALICENSElicense.txtlicense.txttext/plain; charset=utf-83964https://repositorio.unal.edu.co/bitstream/unal/79714/1/license.txtcccfe52f796b7c63423298c2d3365fc6MD51ORIGINAL1037651747.2021.pdf1037651747.2021.pdfTesis de Maestría en Ingeniería - Recursos Hidráulicosapplication/pdf27163204https://repositorio.unal.edu.co/bitstream/unal/79714/2/1037651747.2021.pdfa12681295a8c23427741d3a16ef75b1fMD52THUMBNAIL1037651747.2021.pdf.jpg1037651747.2021.pdf.jpgGenerated Thumbnailimage/jpeg5137https://repositorio.unal.edu.co/bitstream/unal/79714/3/1037651747.2021.pdf.jpg50adbd90f8dfdf4979820640c41424a6MD53unal/79714oai:repositorio.unal.edu.co:unal/797142024-07-22 23:40:02.473Repositorio Institucional Universidad Nacional de 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GVyZWNob3MgZGUgYXV0b3IgcXVlIGNvbmxsZXZlIGxhIGRpc3RyaWJ1Y2nDs24gZGUgZXN0b3MgYXJjaGl2b3MgeSBtZXRhZGF0b3MuCkFsIGhhY2VyIGNsaWMgZW4gZWwgc2lndWllbnRlIGJvdMOzbiwgdXN0ZWQgaW5kaWNhIHF1ZSBlc3TDoSBkZSBhY3VlcmRvIGNvbiBlc3RvcyB0w6lybWlub3MuCgpVTklWRVJTSURBRCBOQUNJT05BTCBERSBDT0xPTUJJQSAtIMOabHRpbWEgbW9kaWZpY2FjacOzbiAyNy8yMC8yMDIwCg==