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A Bayesian forecast model of Australian region tropical cyclone formation

Werner, A and Holbrook, NJ 2011 , 'A Bayesian forecast model of Australian region tropical cyclone formation' , Journal of Climate , doi:

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A new and potentially skilful seasonal forecast model of tropical cyclone formation
(genesis, TCG) is developed for the Australian region. The model is based on Poisson
regression using the Bayesian approach. Predictor combinations are chosen using a stepby-
step predictor selection. The three-predictor model based on derived indices of June-
July-August average convective available potential energy, May-June-July average
meridional winds at 850 hPa (v850) and July-August-September geopotential height at 500
hPa produces the smallest standard error (se = 0.36) and root-mean-squared error (RMSE
= 5.20) for the leave-one-out cross-validated TCG hindcasts over the 40-year record
between 1968/89-2007/08. The corresponding correlation coefficient between observed
annual TCG totals and cross-validated model hindcasts is r = 0.73. Using four-fold crossvalidation,
model hindcast skill is robust with 85% of the observed seasonal TCG totals
hindcast within the model standard deviations. Seasonal TCG totals during ENSO events
are typically well captured with RMSE = 5.14 during El Niño and RMSE = 6.04 during
La Niña years. The model is shown to be valuable in hindcasting seasonal TCG totals in
the Eastern Australian subregion (r = 0.73) and also provides some skill for the Western
Australian region (r = 42), while it not useful for the Northern region. In summary, we
find that the three-predictor Bayesian model provides substantial improvement over
existing statistical TCG forecast models, with remarkably skilful hindcasts (forecasts) of
Australian region and subregional seasonal TCG totals provided one month ahead of the
TC season.

Item Type: Article
Authors/Creators:Werner, A and Holbrook, NJ
Journal or Publication Title: Journal of Climate
ISSN: 0894-8755
DOI / ID Number:
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Copyright © 2011 American Meteorological Society

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