Abstract
This study conducts a comprehensive analysis of hurricane trajectories and their variabilities in categories 1–5 over several decades for the North Atlantic Basin. Utilizing HURDAT2 data from 1961 to 2021, the analysis categorizes hurricanes based on the rate of pressure drop within a 6-h interval, revealing distinct patterns of intensification and weakening among different categories. The K-means clustering method synthesizes hurricane trajectories into representative paths, illustrating significant variations across decades. The research indicates that hurricanes in categories 1 and 2 predominantly originate from tropical depressions, with this trend slightly intensifying in categories 3 and 4. In contrast, Category 5 displayed variation, revealing an increased frequency in the subsequent decades. Additionally, the study analyzes the monthly distribution of hurricanes, identifying September as the peak month across all categories. The analysis further detects significant interannual variability with a noticeable intensification in hurricane activity since the 1990s, albeit with some reductions in the early 2010s. The Accumulated Cyclone Energy (ACE) is used to summarize cyclonic activities, with results indicating a decrease from 1970 to 1995, followed by a consistent surge over the last 15 years. This aligns with previous research suggesting an approximately 60% increase in ACE since the 1980s. Furthermore, an analysis of North Atlantic Basin data reflects a progressive increase in the frequency of named storms (NS) and hurricanes, particularly from 1991 onwards. In conclusion, the study highlights not only an escalating frequency of hurricanes, but also increased variability and unpredictability, necessitating further research to comprehend the underlying causes and evaluate potential socioeconomic and environmental consequences.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The datasets generated during and/or analyzed during the current study are available upon request on the corresponding author.
References
Bell GD, Chelliah M (2006) Leading tropical modes associated with interannual and multidecadal fluctuations in North Atlantic hurricane activity. J Clim 19:590–612. https://doi.org/10.1175/JCLI3659.1
Beven JL, Avila LA, Blake ES et al (2008) Atlantic hurricane season of 2005. Mon Weather Rev 136:1109–1173. https://doi.org/10.1175/2007MWR2074.1
Boudreault M, Caron L-P, Camargo SJ (2017) Reanalysis of climate influences on Atlantic tropical cyclone activity using cluster analysis. J Geophys Res Atmos 122:4258–4280. https://doi.org/10.1002/2016JD026103
Bueti MR, Ginis I, Rothstein LM, Griffies SM (2014) Tropical cyclone-induced thermocline warming and its regional and global impacts. J Clim 27:6978–6999. https://doi.org/10.1175/JCLI-D-14-00152.1
Camargo SJ, Sobel AH (2005) Western North Pacific tropical cyclone intensity and ENSO. J Clim 18:2996–3006. https://doi.org/10.1175/JCLI3457.1
Cione JJ, Uhlhorn EW (2003) Sea surface temperature variability in hurricanes: implications with respect to intensity change. Mon Weather Rev 131:1783–1796. https://doi.org/10.1175//2562.1
Corporal-Lodangco IL, Richman MB, Leslie LM, Lamb PJ (2014) Cluster analysis of north atlantic tropical cyclones. Proc Comput Sci 36:293–300. https://doi.org/10.1016/j.procs.2014.09.096
Delgado S, Landsea CW, Willoughby H (2018) Reanalysis of the 1954–63 Atlantic hurricane seasons. J Clim 31:4177–4192. https://doi.org/10.1175/JCLI-D-15-0537.1
Ellis KN, Sylvester LM, Trepanier JC (2015) Spatiotemporal patterns of extreme hurricanes impacting US coastal cities. Nat Hazards 75:2733–2749. https://doi.org/10.1007/s11069-014-1461-4
Elsner JB, Kara AB, Owens MA (1999) Fluctuations in North Atlantic hurricane frequency. J Clim 12:427–437. https://doi.org/10.1175/1520-0442(1999)012%3c0427:FINAHF%3e2.0.CO;2
Emanuel K (2003) Tropical cyclones. Annu Rev Earth Planet Sci 31:75–104. https://doi.org/10.1146/annurev.earth.31.100901.141259
Emanuel K (2005a) Increasing destructiveness of tropical cyclones over the past 30 years. Nature 436:686–688. https://doi.org/10.1038/nature03906
Emanuel K (2005b) Emanuel replies. Nature 438:E13–E13. https://doi.org/10.1038/nature04427
Grondin NS, Ellis KN (2021) Tropical cyclone occurrence dates in the North Atlantic and eastern North Pacific basins: climatology, trends, and correlations with overall seasonal activity. Theor Appl Climatol 146:311–329. https://doi.org/10.1007/s00704-021-03734-6
Hagen AB, Strahan-Sakoskie D, Luckett C (2012) A reanalysis of the 1944–53 atlantic hurricane seasons—the first decade of aircraft reconnaissance. J Clim 25:4441–4460. https://doi.org/10.1175/JCLI-D-11-00419.1
Hellin J, Haigh M, Marks F (1999) Rainfall characteristics of hurricane Mitch. Nature 399:316–316. https://doi.org/10.1038/20577
Holland G, Bruyère CL (2014) Recent intense hurricane response to global climate change. Clim Dyn 42:617–627. https://doi.org/10.1007/s00382-013-1713-0
Information (NCEI) NC for E International Best Track Archive for Climate Stewardship (IBTrACS) Project, Version 4 (2013) https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C01552. Accessed 17 May 2023
Klotzbach PJ, Landsea CW (2015) Extremely intense hurricanes: revisiting Webster et al. after 10 Years. J Clim 28:7621–7629. https://doi.org/10.1175/JCLI-D-15-0188.1
Knapp KR, Kruk MC, Levinson DH et al (2010) The International Best Track Archive for Climate Stewardship (IBTrACS): unifying tropical cyclone data. Bull Am Meteor Soc 91:363–376. https://doi.org/10.1175/2009BAMS2755.1
Kossin JP (2018) A global slowdown of tropical-cyclone translation speed. Nature 558:104–107. https://doi.org/10.1038/s41586-018-0158-3
Kossin JP, Camargo SJ, Sitkowski M (2010) Climate modulation of North Atlantic hurricane tracks. J Clim 23:3057–3076. https://doi.org/10.1175/2010JCLI3497.1
Kossin JP, Olander TL, Knapp KR (2013) Trend analysis with a new global record of tropical cyclone intensity. J Clim 26:9960–9976. https://doi.org/10.1175/JCLI-D-13-00262.1
Kozar ME, Misra V (2014) Statistical prediction of integrated kinetic energy in north atlantic tropical cyclones. Mon Weather Rev 142:4646–4657. https://doi.org/10.1175/MWR-D-14-00117.1
Kozar ME, Mann ME, Camargo SJ et al (2012) Stratified statistical models of North Atlantic basin-wide and regional tropical cyclone counts. J Geophys Res Atmos. https://doi.org/10.1029/2011JD017170
Landsea CW (1993) A climatology of intense (or major) Atlantic hurricanes. Mon Weather Rev 121:1703–1713. https://doi.org/10.1175/1520-0493(1993)121%3c1703:ACOIMA%3e2.0.CO;2
Landsea CW, Franklin JL (2013) Atlantic hurricane database uncertainty and presentation of a new database format. Mon Weather Rev 141:3576–3592. https://doi.org/10.1175/MWR-D-12-00254.1
Landsea CW, Franklin JL, McAdie CJ et al (2004) A reanalysis of hurricane Andrew’s intensity. Bull Am Meteor Soc 85:1699–1712. https://doi.org/10.1175/BAMS-85-11-1699
Landsea CW, Harper BA, Hoarau K, Knaff JA (2006) Can we detect trends in extreme tropical cyclones? Science 313:452–454. https://doi.org/10.1126/science.1128448
Landsea CW, Glenn DA, Bredemeyer W et al (2008) A reanalysis of the 1911–20 Atlantic hurricane database. J Clim 21:2138–2168. https://doi.org/10.1175/2007JCLI1119.1
Landsea CW, Feuer S, Hagen A et al (2012) A Reanalysis of the 1921–30 Atlantic Hurricane Database. J Clim 25:865–885
Loyd S (1982) Least squares quantization in PCM. IEEE Trans Inf Theory 28:129–137. https://doi.org/10.1109/TIT.1982.1056489
Mainelli M, DeMaria M, Shay LK, Goni G (2008) Application of oceanic heat content estimation to operational forecasting of recent Atlantic category 5 hurricanes. Weather Forecast 23:3–16. https://doi.org/10.1175/2007WAF2006111.1
McTaggart-Cowan R, Deane GD, Bosart LF et al (2008) Climatology of tropical cyclogenesis in the North Atlantic (1948–2004). Mon Weather Rev 136:1284–1304. https://doi.org/10.1175/2007MWR2245.1
Mei W, Kamae Y, Xie S-P, Yoshida K (2019) Variability and predictability of North Atlantic hurricane frequency in a large ensemble of high-resolution atmospheric simulations. J Clim 32:3153–3167. https://doi.org/10.1175/JCLI-D-18-0554.1
Mendes D, de Oliveira Júnior JF, Mendes MCD, Filho WLFC (2023) Simple hurricane model: asymmetry and dynamics. Clim Dyn 60:1467–1480. https://doi.org/10.1007/s00382-022-06396-w
Moon Y, Nolan DS (2010) The dynamic response of the hurricane wind field to spiral Rainband heating. J Atmos Sci 67:1779–1805. https://doi.org/10.1175/2010JAS3171.1
Murakami H, Li T, Hsu P-C (2014) Contributing factors to the recent high level of accumulated cyclone energy (ACE) and Power Dissipation Index (PDI) in the North Atlantic. J Clim 27:3023–3034. https://doi.org/10.1175/JCLI-D-13-00394.1
Needham HF, Keim BD, Sathiaraj D (2015) A review of tropical cyclone-generated storm surges: global data sources, observations, and impacts. Rev Geophys 53:545–591. https://doi.org/10.1002/2014RG000477
NOAA (2005) Climate Prediction Center—Atlantic Hurricane Outlook. https://www.cpc.ncep.noaa.gov/products/outlooks/hurricane2020/May/hurricane.shtml. Accessed 17 May 2023
Oouchi K, Yoshimura J, Yoshimura H et al (2006) Tropical cyclone climatology in a global-warming climate as simulated in a 20 km-mesh global atmospheric model: frequency and wind intensity analyses. J Meteorol Soc Jpn Ser II. 84:259–276. https://doi.org/10.2151/jmsj.84.259
Patel A, Singh P (2012) New approach for K-mean and K-medoids algorithm. IJCATR 2:1–5. https://doi.org/10.7753/IJCATR0201.1001
Patricola CM, Saravanan R, Chang P (2017) A teleconnection between Atlantic sea surface temperature and eastern and central North Pacific tropical cyclones. Geophys Res Lett 44:1167–1174. https://doi.org/10.1002/2016GL071965
Pistrika AK, Jonkman SN (2010) Damage to residential buildings due to flooding of New Orleans after hurricane Katrina. Nat Hazards 54:413–434. https://doi.org/10.1007/s11069-009-9476-y
Ramsay H (2017) The global climatology of tropical cyclones. Oxford research encyclopedia of natural hazard science. Oxford University Press, Oxford
Rezaee S, Pelot R, Finnis J (2016) The effect of extratropical cyclone weather conditions on fishing vessel incidents’ severity level in Atlantic Canada. Saf Sci 85:33–40. https://doi.org/10.1016/j.ssci.2015.12.006
Sadler JC, Usaf LC (1962) The first hurricane track determined by meteorological satellite. Mausam 13:29–44. https://doi.org/10.54302/mausam.v13i1.4284
Saunders MA, Lea AS (2008) Large contribution of sea surface warming to recent increase in Atlantic hurricane activity. Nature 451:557–560. https://doi.org/10.1038/nature06422
Seekins D (2009) State, society and natural disaster: cyclone Nargis in Myanmar (Burma). Asian J Soc Sci 37:717–737. https://doi.org/10.1163/156848409X12474536440500
Shaman J, Maloney ED (2012) Shortcomings in climate model simulations of the ENSO-Atlantic hurricane teleconnection. Clim Dyn 38:1973–1988. https://doi.org/10.1007/s00382-011-1075-4
Simpson R, Saffir H (1974) The hurricane disaster—potential scale. Weatherwise 27:169–186. https://doi.org/10.1080/00431672.1974.9931702
Titley HA, Yamaguchi M, Magnusson L (2019) Current and potential use of ensemble forecasts in operational TC forecasting: results from a global forecaster survey. Trop Cyclone Res Rev 8:166–180. https://doi.org/10.1016/j.tcrr.2019.10.005
Tourre YM, Paz S, Kushnir Y, White WB (2010) Low-frequency climate variability in the Atlantic basin during the 20th century. Atmos Sci Lett 11:180–185. https://doi.org/10.1002/asl.265
Vecchi GA, Soden BJ (2007) Increased tropical Atlantic wind shear in model projections of global warming. Geophys Res Lett. https://doi.org/10.1029/2006GL028905
Velden CS, Hayden CM, Menzel WP et al (1992) The impact of satellite-derived winds on numerical hurricane track forecasting. Weather Forecast 7:107–118. https://doi.org/10.1175/1520-0434(1992)007%3c0107:TIOSDW%3e2.0.CO;2
Walsh KJE, Camargo SJ, Vecchi GA et al (2015) Hurricanes and climate: the U.S. CLIVAR working group on hurricanes. Bull Am Meteor Soc 96:997–1020
Wang C, Lee S-K (2009) Co-variability of tropical cyclones in the North Atlantic and the eastern North Pacific. Geophys Res Lett. https://doi.org/10.1029/2009GL041469
Acknowledgements
We would like to thank the “Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)” for the grant of productivity, for their support and contribution to the development of this article.
Funding
Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq—Grant ID: 304681/2022-9.
Author information
Authors and Affiliations
Contributions
JAFN: conceptualization, methodology, data curation, formal analysis and investigation, visualization, writing. DM: conceptualization, methodology, data curation, analysis and investigation, visualization. WAG: writing—review and editing. MMC: writing—review and editing. JFOJ: review and editing.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no competing interests.
Ethical approval
Not applicable.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Neto, J.A.F., Mendes, D., Gonçalves, W.A. et al. Temporal evolution of hurricane activity: insights from decades of category 1–5 analysis. Environ Earth Sci 83, 202 (2024). https://doi.org/10.1007/s12665-024-11504-6
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12665-024-11504-6