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Advances in Meteorology
Volume 2014, Article ID 248148, 11 pages
http://dx.doi.org/10.1155/2014/248148
Research Article

An ENSO-Forecast Independent Statistical Model for the Prediction of Annual Atlantic Tropical Cyclone Frequency in April

1Enloe High School, Raleigh, NC, USA
2Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Campus Box 8208, Raleigh, NC 27695, USA

Received 15 December 2013; Accepted 30 December 2013; Published 18 February 2014

Academic Editor: Lian Xie

Copyright © 2014 Kenny Xie and Bin Liu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Statistical models for preseason prediction of annual Atlantic tropical cyclone (TC) and hurricane counts generally include El Niño/Southern Oscillation (ENSO) forecasts as a predictor. As a result, the predictions from such models are often contaminated by the errors in ENSO forecasts. In this study, it is found that the latent heat flux (LHF) over Eastern Tropical Pacific (ETP, defined as the region 0°–5°N, 115°–125°W) in spring is negatively correlated with the annual Atlantic TC and hurricane counts. By using stepwise backward elimination regression, it is further shown that the March value of ETP LHF is a better predictor than the spring or summer ENSO index for Atlantic TC counts. Leave-one-out cross validation indicates that the annual Atlantic TC counts predicted by this ENSO-independent statistical model show a remarkable correlation with the actual TC counts (; value ). For Atlantic hurricanes, the predictions using March ETP LHF and summer (July–September) ENSO indices show only minor differences except in moderate to strong El Niño years. Thus, March ETP LHF is an excellent predictor for seasonal Atlantic TC prediction and a viable alternative to using ENSO index for Atlantic hurricane prediction.