Multi-Model Ensemble Forecasting of North Atlantic Tropical Cyclone Activity

North Atlantic tropical cyclones (TCs) and hurricanes are responsible for a large number of fatalities and economic damage in the United States. According to the National Climatic Data Center (NCDC), over the period 1980-2011 these catastrophic events were responsible for 31 events that caused losses in excess of $1 billion (http://www.ncdc.noaa.gov/billions), corresponding to 23.1% of all the weather and climate disasters affecting the US causing damage in excess of $1 billion. An even more staggering number is the dollar amount of damage associated with these catastrophic events: TCs were responsible for $417.9 billion (Consumer Price Index adjusted), which correspond to 47.4% of all the damage caused by all the natural disasters responsible for $1+ billion combined. Improved forecasting of these catastrophic events will provide basic information critical towards 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 record. These predictors reflect the importance of both local and non-local effects on the genesis and development of TC in the North Atlantic basin. A set of retrospective predictions by four experimental seasonal-to-interannual prediction systems (Geophysical Fluid Dynamics Laboratory (GFDL)-CM2.1; NASA Global Modeling and Assimilation Office (NASA-GMAO)-GEOS-5; The Center for Ocean-Land-Atmosphere Studies – Rosenstiel School of Marine & Atmospheric Science (COLA-RSMAS)-CCSM3; Canadian Centre for Climate Modeling and Analysis (CCCma) - CanCM4) is used as covariates. The predictions are initialized over the period 1981-present, and each of them has a 10-member ensemble. Results will compare and contrast retrospective forecast skill for each of these four prediction systems for different TC quantities for forecasts initialized as early as November of the previous year. Moreover, different ways of merging these forecasts will be examined. Probabilistic predictions for the upcoming 2014 North Atlantic TC activity will also be presented.