EMS Annual Meeting Abstracts
Vol. 20, EMS2023-123, 2023, updated on 06 Jul 2023
https://doi.org/10.5194/ems2023-123
EMS Annual Meeting 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Understanding predictability of tropical cyclones over the North Atlantic Ocean

Shun Yiu Brett Chung1, Andreas H. Fink1, and Michael Riemer2
Shun Yiu Brett Chung et al.
  • 1Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany (shun.chung@kit.edu)
  • 2Institute for Atmospheric Physics, Johannes Gutenberg University Mainz, Mainz, Germany (mriemer@uni-mainz.de)

Tropical cyclones (TCs) are extreme weather events capable of causing major loss of life and property. Despite continued improvements in our understanding of TC dynamics and the advancement of numerical models over the past few decades, accurate and precise forecasting of TCs beyond the short-term (<=72 hours) window remains an operational challenge. In other words, there seems to be a ‘predictability barrier’ for TCs at several days in lead time. For example, according to the US National Hurricane Centre (NHC), the average error for a 5-day track forecast of Atlantic TCs generally exceeds 300 km over the last ten years with little change in trend. The predictability of TCs is thus an interesting and practically relevant topic for investigation.

We evaluate TC-relevant ensemble statistics with lead time of up to 8 days before genesis for the Atlantic basin, starting from 2017. ECMWF operational ensemble forecast data are used on NHC best-tracked tropical and subtropical systems. TC-like vortices are first tracked using the feature-tracking algorithm TRACK based on lower-tropospheric relative vorticity. They are then matched against the respective TCs from the operational analysis data by a technique known as Dynamic Time Warping, which allows for some spatio-temporal discrepancies. Two main groups of TCs, i.e., those that form in the Main Development Region (MDR) and those that undergo tropical transition (TT) are selected for analysis due to their distinctly different genesis characteristics. Special attention is drawn to the phenomenon of ‘forecast jumps’ (i.e., sudden and substantial shifts in the ensemble probabilities with lead time) as identified in previous work on this topic. The evaluation parameters used include minimum central MSLP, maximum 10m mean wind, storm location and various parameters on tropospheric thermal structures (for storms with TT).

Preliminary results suggest MDR and TT storms do exhibit very different behaviours with regard to genesis predictability. The more ‘classical’ TCs that form in the deep tropics are typically better forecast in advance and provide a longer window of predictability, perhaps to more than a week. In contrast, their mid-latitude counterparts are sometimes only captured by the model a few days prior to the TT event. Ensemble members can struggle to distinguish between a warm or cold-core system, before converging on a solution rather abruptly. The case study of Hurricane Ophelia (2017) is useful to illustrate this phenomenon. Additional results will be presented as further work is done to establish and analyse behavioural statistics while enlarging the TC sample set.

How to cite: Chung, S. Y. B., Fink, A. H., and Riemer, M.: Understanding predictability of tropical cyclones over the North Atlantic Ocean, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-123, https://doi.org/10.5194/ems2023-123, 2023.