Tropical Cyclones: Variability


Tropical Oceanic Influences on Observed Global Tropical Cyclone Frequency

Boxplots of annual global named storm days for years in which the January–December averaged ENSO Longitude Index (ELI, °E; magenta), Niño 3.4 index (red), and AMM index (blue) were observed within the bottom, middle, and top percentiles over the years 1980–2021. Solid and dashed black lines denote the mean and mean ± one standard deviation, respectively, for the TC metric.

The global tropical cyclone (TC) number has historically been relatively constant from year-to-year, however, the reason remains unknown. Furthermore, climate projections are inconclusive regarding future global TC frequency changes. Here, we investigated years in which observed global TC activity deviated from the mean and potential links to ocean drivers from 1980 to 2021. We found that the annual global number of named storm days and accumulated cyclone energy (ACE) were significantly linked with El Niño–Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM). La Niña and positive AMM are associated with the bottom percentiles of both TC metrics, and vice versa for El Niño and negative AMM. The ENSO Longitude Index explains variability in annual global named storm days and ACE as well as the Niño 3.4 index. This research reveals that reliable future projections of ENSO are necessary, but not sufficient, to understand future changes in global TC frequency.

  • Patricola, C. M., Cassidy, D. J., & Klotzbach, P. J. (2022). Tropical Oceanic Influences on Observed Global Tropical Cyclone Frequency. Geophysical Research Letters, 49(13), e2022GL099354.

This research was supported by the U.S. Department of Energy Office of Science (BER RGMA program) under Early Career Research Program Award Number DE-SC0021109.


ENSO diversity and tropical cyclone variability

ENSO diversity
Warm sea-surface temperature anomalies during an El Nino event.

El Niño, the occurrence of unusually warm sea-surface temperature over the equatorial East Pacific Cold Tongue, is an important predictor of seasonal Atlantic tropical cyclone activity.  In recent decades El Niño has been characterized more often by Central Pacific Ocean warming, and there is no consensus regarding how this shift in location of ocean warming impacts Atlantic tropical cyclones due to a short data record.  In addition, an increasing trend in the intensity of Central Pacific, or “Warm Pool,” El Niño has been observed recently and projected in the future.  It is unknown how this potential change will impact Atlantic tropical cyclones.  We find, using climate model simulations, that for observed warming intensities characteristic of the top 90th percentile, Warm Pool El Niño is 50% less effective at suppressing Atlantic tropical cyclones than Cold Tongue El Niño.  However, for the same absolute warming intensity (~2.25°C), Warm Pool El Niño is 50% more effective than Cold Tongue El Niño.  Atlantic tropical cyclones are suppressed regardless of El Niño type, since both are characterized by sufficient warming east of the Pacific warm pool, which satisfies the sea-surface temperature threshold for an eastward migration of deep convection leading to tropical cyclone suppression via tropical Atlantic vertical wind shear enhancements.  This work highlights the necessity to understand how the frequency, location, and intensity of El Niño are expected to change in the future in order to make the best-informed forecasts and projections of Atlantic tropical cyclone activity.

  • Patricola, C. M., Chang, P., & Saravanan, R. (2016). Degree of simulated suppression of Atlantic tropical cyclones modulated by flavour of El Niño. Nature Geoscience, 9(2), 155–160.
  • Patricola, C. M., Camargo, S. J., Klotzbach, P. J., Saravanan, R., & Chang, P. (2018). The Influence of ENSO Flavors on Western North Pacific Tropical Cyclones. Journal of Climate, 31(14), 5395-5416.
  • Mueller, T. J., Patricola, C. M., & Bercos-Hickey, E. (2024). The Influence of ENSO Diversity on Future Atlantic Tropical Cyclone Activity. Journal of Climate, in revision.

This research was supported by the U.S. National Science Foundation award AGS-1347808.  High-performance computing resources provided by the Texas Advanced Computing Center (TACC) at The University of Texas at Austin and by the Texas A&M Supercomputing Facility.


Constructive and Compensating Influences of Tropical Atlantic and Pacific Sea-Surface Temperatures on Atlantic Tropical Cyclone Activity

Atlantic tropical cyclone (TC) activity is influenced by interannual tropical Pacific sea surface temperature (SST) variability characterized by the El Niño–Southern Oscillation (ENSO), as well as interannual-to-decadal variability in the interhemispheric gradient in tropical Atlantic SST characterized by the Atlantic meridional mode (AMM). Individually, the negative AMM phase (cool northern and warm southern tropical Atlantic SST anomalies) and El Niño each inhibit Atlantic TCs, and vice versa. We investigated the influence of concurrent strong phases of the ENSO and AMM on Atlantic TC activity using observations and regional climate model simulations. We found that ENSO and AMM can amplify or dampen the influence of one another on Atlantic TCs. In particular, simultaneous strong El Niño and strongly positive AMM, as well as strong concurrent La Niña and negative AMM, produce near-average Atlantic ACE suggesting compensation between the two influences. Strong La Niña and strongly positive AMM together produce extremely intense Atlantic TC activity, while strong El Niño and negative AMM together are not necessary conditions for significantly reduced Atlantic tropical cyclone activity.

  • Patricola, C. M., Saravanan, R., & Chang, P. (2014). The Impact of the El Niño-Southern Oscillation and Atlantic Meridional Mode on Seasonal Atlantic Tropical Cyclone Activity. Journal of Climate, 27(14), 5311–5328.

This research was supported by the U.S. National Science Foundation award AGS-1347808.  High-performance computing resources provided by the Texas Advanced Computing Center (TACC) at The University of Texas at Austin and by the Texas A&M Supercomputing Facility.


The Influence of Climate Variability and Future Climate Change on Atlantic Hurricane Season Length

Atlantic hurricane season length is important for emergency management preparation, motivating the need to understand its variability and change. We investigated the influence of ocean variability on Atlantic hurricane season length in observations and a future climate simulated by the Energy Exascale Earth System Model (E3SM).  We found that multiple factors influence hurricane season length, through their influence on season start and end.  Warm western subtropical Atlantic sea-surface temperature anomalies (SSTAs) during boreal spring (before the official hurricane season start) drive early starts to the hurricane season, and vice versa for cool SSTAs.  Meanwhile, La Niña in autumn (before the official hurricane season end) drives late ends to the hurricane season, and vice versa for El Niño. E3SM projects a 27 day increase in future Atlantic hurricane season length given La Niña and warm northern tropical Atlantic SSTAs.  This research documents sources of predictability for Atlantic hurricane season length.

Seasonal composites of sea-surface temperature anomalies (SSTAs; °C) relative to the corresponding seasonal 1980-2022 climatology based on HadISST observations, for Atlantic hurricane season start and end. Mar-May SSTAs corresponding to Atlantic hurricane seasons with (a) an early start and (b) a late start.  Aug-Oct SSTAs corresponding to Atlantic hurricane seasons with (c) a late end and (d) an early end. Purple marks denote the genesis location of the (a-b) first tropical storm and (c-d) last tropical storm to dissipate for the hurricane seasons.
  • Patricola, C. M., Hansen, G. E., & Sena A. C. T. (2024) The Influence of Climate Variability and Future Climate Change on Atlantic Hurricane Season Length. Geophysical Research Letters, in revision.

This research was supported by the U.S. Department of Energy Office of Science (BER RGMA program) under Early Career Research Program Award Number DE-SC0021109 and under Award Number DE-AC02-05CH11231. E3SM simulations were performed using BER Earth System Modeling program's Compy computing cluster located at Pacific Northwest National Laboratory.  High-performance computing resources also provided by the National Energy Research Scientific Computing Center (NERSC).


updated 3/13/2024