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Multi-model ensemble forecasting of North Atlantic tropical cyclone activity

Abstract

North Atlantic tropical cyclones (TCs) and hurricanes are responsible for a large number of fatalities and economic damage. Skillful seasonal predictions of the North Atlantic TC activity can provide basic information critical to our improved preparedness. This study focuses on the development of statistical–dynamical seasonal forecasting systems for different quantities related to the frequency and intensity of North Atlantic TCs. These models use only tropical Atlantic and tropical mean sea surface temperatures (SSTs) to describe the variability exhibited by the observational records because they reflect the importance of both local and non-local effects on the genesis and development of TCs in the North Atlantic basin. A set of retrospective forecasts of SSTs by six experimental seasonal-to-interannual prediction systems from the North American Multi-Model Ensemble are used as covariates. The retrospective forecasts are performed over the period 1982–2015. The skill of these statistical–dynamical models is quantified for different quantities (basin-wide number of tropical storms and hurricanes, power dissipation index and accumulated cyclone energy) for forecasts initialized as early as November of the year prior to the season to forecast. The results of this work show that it is possible to obtain skillful retrospective forecasts of North Atlantic TC activity with a long lead time. Moreover, probabilistic forecasts of North Atlantic TC activity for the 2016 season are provided.

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Acknowledgments

The authors thank the NMME program partners and acknowledge the help of NCEP, IRI and NCAR personnel in creating, updating and maintaining the NMME archive, with the support of NOAA, NSF, NASA and DOE. The first three authors acknowledge funding from the National Science Foundation under Grant No. AGS-1262099, and Award NA14OAR4830101 from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce. Gabriele Villarini also acknowledges financial support from the USACE Institute for Water Resources.

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Correspondence to Gabriele Villarini.

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This paper is a contribution to the special collection on the North American Multi-Model Ensemble (NMME) seasonal prediction experiment. The special collection focuses on documenting the use of the NMME system database for research ranging from predictability studies, to multi-model prediction evaluation and diagnostics, to emerging applications of climate predictability for subseasonal to seasonal predictions. This special issue is coordinated by Annarita Mariotti (NOAA), Heather Archambault (NOAA), Jin Huang (NOAA), Ben Kirtman (University of Miami) and Gabriele Villarini (University of Iowa).

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Villarini, G., Luitel, B., Vecchi, G.A. et al. Multi-model ensemble forecasting of North Atlantic tropical cyclone activity. Clim Dyn 53, 7461–7477 (2019). https://doi.org/10.1007/s00382-016-3369-z

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  • DOI: https://doi.org/10.1007/s00382-016-3369-z

Keywords

  • North Atlantic TC Activity
  • Retrospective Forecasts
  • North American Multi-Model Ensemble (NMME)
  • Accumulated Cyclone Energy (ACE)
  • Power Dissipation Index (PDI)