Can Long-Term Modeling Improve Forecast Accuracy and Disaster Response Efforts?
In 2013, most major forecasting centers predicted an above-average Hurricane Season for the Atlantic basin. It turned out to be one of the least active years in decades. With most organizations focused on short-term (6 months to 1 year) oscillation models and ocean-atmosphere interactions (such as El Nino and La Nina), could a different long-term prediction model provide a more accurate forecast? If so, what could we do with local disaster planning and response efforts to take advantage of this longer “lead time” before an event occurs?
This webinar features David Dilley, CEO of Global Weather Oscillations (GWO), an Ocala, Florida-based company that uses past weather cycles to predict the number storms during a hurricane season. GWO accurately predicted last year’s inactivity in the Atlantic and Gulf of Mexico, and their “Climate Pulse Technology” model has been also accurate the last 5 years.
Mr. Dilley discusses how predictive models based on long-term weather cycles may indeed prove to be more accurate than the traditional short-term oscillation models, and if this information can assist local responders.
Duration: 1 Hour
Featured Speaker: David Dilley, CEO of Global Weather Oscillations (GWO)