Data assimilation and predictability of tropical cyclones

Abstract

Hurricanes are one of deadliest and costliest natural hazards, with total losses topping $100 billion for the first time in 2005 (Pielke et al., 2008). Accurate predictions of hurricanes, therefore, have enormous economic value, and demand is increasing for more accurate forecasts with longer lead times and more precise warnings to minimize losses due to hurricane preparation and evacuation as well as to destruction. Over the past decade, significant progress has been made in short-range (up to five days) track forecasts of tropical cyclones. The current day average 48-h forecast position is as accurate as a 24-h track forecast 10 yr ago (Franklin, 2004).