Using extreme frequency analysis to explain the impact of hurricanes Pauline (1997) and Otis (2023) on Acapulco, Mexico

• Autorzy: Gutierrez-López Alfonso , Mandujano Martin Muñoz , Ibarra-Corona Mauricio Arturo , Vargas-Diaz Jose Alejandro

Identyfikatory

DOI

10.26491/mhwm/205741

• Języki publikacji: EN

Abstrakty

EN

The severity of hurricanes and cyclones in Mexico increases each year. A key area of research represents the development of a mathematical model to predict their tracks and points of impact. The IBTrACS database contains data on hurricanes and tropical cyclone tracking; it is the most comprehensive global collection of tropical cyclones. This database was developed in collaboration with all Regional Specialized Meteorological Centers of the World Meteorological Organization (WMO). Using the track, wind speed, and atmospheric pressure data for each of the hurricane and cyclone occurrences from 1851 to 2022, probabilistic type I extreme value models were applied to extreme winds and atmospheric pressure. With the help of a simple Bayesian model the probabilities were computed of a hurricane or cyclone withwind of a certain magnitude occurring at a given latitude and longitude; an event occurs when specified atmospheric pressure conditions are met. The data collected correspond to the area between west longitudes 115.5° and 85° and north latitudes 10° and 32°. This database can be managed, in the future, for the forecast of hurricane and cyclone tracks.

Słowa kluczowe

EN

hurricane; cyclone; hurricane track; wind speed; atmospheric pressure; Gumbel distribution; probabilistic analysis; hurricane Otis; hurricane Paulina

• Wydawca: Instytut Meteorologii i Gospodarki Wodnej - Państwowy Instytut Badawczy
• Czasopismo: Meteorology Hydrology and Water Management. Research and Operational Applications
• Rocznik: 2024
• Tom: Vol. 12, Iss. 2
• Strony: 74--83
• Opis fizyczny: Bibliogr. 36 poz., rys.

Twórcy

autor

Gutierrez-López Alfonso

• Universidad Autonoma de Queretaro, Mexico

autor

Mandujano Martin Muñoz

• Universidad Autonoma de Queretaro, Mexico

autor

Ibarra-Corona Mauricio Arturo

• Universidad Autonoma de Queretaro, Mexico

autor

Vargas-Diaz Jose Alejandro

• Universidad Autonoma de Queretaro, Mexico

Bibliografia

• Aberson S.D., Franklin J.L., 1999, Impact on hurricane track and intensity forecasts of GPS dropwindsonde observations from the first-season flights of the NOAA Gulfstream-IV Jet Aircraft, Bulletin of the American Meteorological Society, 80 (3), 421-427., DOI: 10.1175/1520-0477(1999)0802.0.CO;2.
• Bieli M., Sobel A.H., Camargo S.J., Tippett M.K., 2019, A statistical model to predict the extratropical transition of tropical cyclones. Weather and Forecasting, 35 (2), 451-466, DOI: 10.1175/WAF-D-19-0045.1.
• Breña-Naranjo A., Pedrozo-Acuña A., Pozos-Estrada O., Jiménez-López S.A., López-López M.R., 2015, The contribution of tropical cyclones to rainfall in Mexico, Physics and Chemistry of the Earth, Parts A/B/C, 83-84, 111-122, DOI: 10.1016/j.pce.2015.05.011.
• Chavas D.R., Lin N., Dong W., Lin Y., 2016, Observed tropical cyclone size revisited, Journal of Climate, 29 (8), 2923-2939, DOI: 10.1175/JCLI-D-15-0731.1.
• Chen G., Yu H., Cao Q., Zeng Z., 2013, The performance of global models in TC track forecasting over the Western North Pacific from 2010 to 2012, Tropical Cyclone Research and Review, 2 (3), 149-158, DOI: 10.6057/2013TCRR03.02.
• Collins J., Polen A., McSweeney K., Colón-Burgos D., Jernigan I., 2021, Hurricane risk perceptions and evacuation decision-making in the age of COVID-19, Bulletin of the American Meteorological Society, 102 (4), E836-E848, DOI: 10.1175/BAMS-D-20-0229.1.
• Cui L., Shi L., Yin Q., Yu W., Lu X., Liu J., 2013, Application of satellite cloud imagery in track analysis of tropical cyclones, Tropical Cyclone Research and Review, 2 (4), 222-232, DOI: 10.6057/2013TCRR04.04.
• Feng K., Lin N., Gori A., Xi D., Ouyang M., Oppenheimer M., 2025, Hurricane Ida’s blackout-heatwave compound risk in a changing climate, Nature Communications, 16 (1), DOI: 10.1038/s41467-025-59737-8.
• Geiger T., Frieler K., Bresch D.N., 2018, A global historical data set of tropical cyclone exposure (TCE-DAT), Earth System Science Data, 10 (1), 185-194, DOI: 10.5194/essd-10-185-2018.
• Gori A., Lin N., Xi D., Emanuel K., 2022, Tropical cyclone climatology change greatly exacerbates US extreme rainfall-surge hazard, Nature Climate Change, 12 (2), 171-178, DOI: 10.1038/s41558-021-01272-7.
• Gran Castro J.A., Ramos De Robles S.L., 2019, Climate change and flood risk: vulnerability assessment in an urban poor community in Mexico, Environment and Urbanization, 31 (1), 75-92, DOI: 10.1177/0956247819827850.
• Gutierrez-Lopez A., 2022, Methodological guide to forensic hydrology, Water, 14 (23), DOI: 10.3390/w14233863.
• Hallegatte S., Green C., Nicholls R.J., Corfee-Morlot J., 2013, Future flood losses in major coastal cities, Nature Climate Change, 3 (9), 802-806, DOI: 10.1038/nclimate1979.
• Hallegatte S., Maruyama R., Jun E., Walsh B., 2018, Building back better: achieving resilience through stronger, faster, and more inclusive post-disaster reconstruction, World Bank Group, Washington, D.C., available online at https://documents.worldbank.org/en/publication/documents-reports/documentdetail/420321528985115831 (data access 30.05.2025).
• Heming J.T., Prates F., Bender M.A., Bowyer R., Cangialosi J., Caroff P., Coleman T., Doyle J.D., Dube A., Faure G., Fraser J., Howell B.C., Igarashi Y., McTaggart-Cowan R., Mohapatra M., Moskaitis J.R., Murtha J., Rivett R., Sharma M., Short C.J., 2019, Review of recent progress in tropical cyclone track forecasting and expression of uncertainties, Tropical Cyclone Research and Review, 8 (4), 181-218, DOI: 10.1016/j.tcrr.2020.01.001.
• Hon K.-K., 2020, Tropical cyclone track prediction using a large-area WRF model at the Hong Kong Observatory, Tropical Cyclone Research and Review, 9 (1), 67-74, DOI: 10.1016/j.tcrr.2020.03.002.
• Hook B., 2025, Mangrove Loss in Acapulco Likely Worsened the Devastation of Hurricane Otis, Scripps Institution of Oceanography, available online at https://scripps.ucsd.edu/news/mangrove-loss-acapulco-likely-worsened-devastation-hurricane-otis(data access 30.05.2025).
• Jaimes M.A., Niño M., Huerta B., 2014, Hurricane event-based method to create regional hazard maps for heavy rainfall-induced translational landslides, Natural Hazards, 76 (2), 1143-1161, DOI: 10.1007/s11069-014-1539-z.
• Khurana T., Bhattacharya S.K., Kotal S.D., 2017, Some special characteristics of track and intensity of typhoons over the Western North Pacific, Tropical Cyclone Research and Review, 6 (3-4), 82-93, DOI: 10.6057/2017TCRRh3.03.
• Knapp K.R., Kruk M.C., Levinson D.H., Diamond H.J., Neumann C.J., 2010, The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying tropical cyclone best track data, Bulletin of the American Meteorological Society, 91, 363-376, DOI: 10.1175/2009BAMS2755.1.
• Koks E.E., Rozenberg J., Zorn C., Tariverdi M., Vousdoukas M., Fraser S., Hallegatte S., 2019, A global multi-hazard risk analysis of road and railway infrastructure assets, Nature Communications, 10, 2677, DOI: 10.1038/s41467-019-10442-3.
• Leroux M.-D., Wood K., Elsberry R.L., Cayanan E.O., Hendricks E., Kucas M., Otto P., Rogers R., Sampson B., Yu Z., 2018, Recent advances in research and forecasting of tropical cyclone track, intensity, and structure at landfall, Tropical Cyclone Research and Review, 7 (2), 85-105, DOI: 10.6057/2018TCRR02.02.
• Lewis C.T., 2022, Climate change and the Caribbean: challenges and vulnerabilities in building resilience to tropical cyclones, Climate, 10 (11), DOI: 10.3390/cli10110178.
• Magnusson L., Doyle J.D., Komaromi W.A., Torn R.D., Tang C.K., Chan J.C.L., Yamaguchi M., Zhang F., 2019, Advances in understanding difficult cases of tropical cyclone track forecasts, Tropical Cyclone Research and Review, 8 (3), 109-122, DOI: 10.1016/j.tcrr.2019.10.001.
• Molina-Aguilar J.P., Gutiérrez-López A., 2020, Daños económicos y sociales por huracanes e inundaciones en México: periodo de 2010 a 2015, Aqua-LAC, 12 (2), 67-77, DOI: 10.29104/phi-aqualac/2020-v12-2-06.
• Molina-Aguilar J.P., Gutierrez-Lopez A., Raynal-Villaseñor J.A., Garcia-Valenzuela L.G., 2019, Optimization of parameters in the generalized extreme-value distribution type 1 for three populations using harmonic search, Atmosphere, 10 (5), DOI: 10.3390/atmos10050257.
• Nath S., Kotal S.D., Kundu P.K., 2015, Application of fuzzy clustering technique for analysis of North Indian Ocean tropical cyclone tracks, Tropical Cyclone Research and Review, 4 (3), 110-123, DOI: 10.6057/2015TCRRh3.02.
• Nishimura M., Yamaguchi M., 2015, Selective ensemble mean technique for tropical cyclone track forecasts using multi-model ensembles, Tropical Cyclone Research and Review, 4 (2), 71-78, DOI: 10.6057/2015TCRR02.03.
• Ramírez-Herrera M.T., Coca O., Gaidzik K., Vargas Espinosa V.H., 2025, Hurricane Otis: category 5 storm effects and cascading hazards in Acapulco Bay, Mexico, Global and Earth Surface Processes Change, 3, DOI: 10.1016/j.gespch.2025.100004.
• Rodríguez Esteves J.M., 2017, Los desastres recurrentes en México: el huracán Pauline y la tormenta Manuel en Acapulco, Guerrero, Disertaciones Anuario Electrónico Estudios de Comunicación Social, 10 (2), DOI: 10.12804/revistas.urosario.edu.co/disertaciones/a.4778.
• Saporta G., 2011, Probabilités analyse et des données et statistique, TECHNIP, Paris, France, 493 pp.
• Simpson N.P., Williams P.A., Mach K.J., Berrang-Ford L., Biesbroek R., Haasnoot M., Segnon A.C., Campbell D., Musah-Surugu J.I., Joe E.T., Nunbogu A.M., Sabour S., Meyer A.L.S., Andrews T.M., Singh C., Siders A.R., Lawrence J., van Aalst M., Trisos C.H., 2023, Adaptation to compound climate risks: a systematic global stocktake, IScience, 26 (2), DOI: 10.1016/j.isci.2023.105926.
• Tang C.K., Chan J.C.L., Yamaguchi M., 2021, Large tropical cyclone track forecast errors of global numerical weather prediction models inwestern North Pacific basin, Tropical Cyclone Research and Review, 10 (3), 151-169, DOI: 10.1016/j.tcrr.2021.07.001.
• Trošelj J., Lee H.S., 2021, Modelling typhoon-induced extreme river discharges: a case study of Typhoon Hagibis in Japan, Journal of Hydrology: Regional Studies, 34, DOI: 10.1016/j.ejrh.2021.100776.
• Weng F., Zhu T., Yan B., 2007, Satellite data assimilation in numerical weather prediction models. Part II: Uses of rain-affected radiances from microwave observations for hurricane vortex analysis, Journal of the Atmospheric Sciences, 64 (11), 3910-3925, DOI: 10.1175/2006JAS2051.1.
• Zscheischler J., Westra S., van den Hurk B.J.J.M., Seneviratne S.I., Ward P.J., Pitman A., AghaKouchak A., Bresch D.N., Leonard M., Wahl T., Zhang X., 2018, Future climate risk from compound events, Nature Climate Change, 8 (6), 469-477, DOI: 10.1038/s41558-018-0156-3.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).