资源环境科技发展态势分析平台

Colorado State University (CSU) has been issuing seasonal hurricane forecasts since 1984, with statistical modeling techniques primarily underpinning these outlooks. CSU has recently begun issuing statistical/dynamical forecasts, using the SEAS5 forecast system from the European Centre for Medium‐Range Weather Forecasts to forecast the three predictors that currently comprise CSU's early August statistical forecast model. SEAS5 shows skill at forecasting all three of these July predictors from an initialization as early as 1 March. The SEAS5 model forecasts for the three parameters are then regressed against seasonal Accumulated Cyclone Energy (ACE). The model has a cross‐validated correlation skill of r = 0.60 with ACE for a 1 March initialization, improving to r = 0.67 for a 1 June initialization over the period from 1982‐2019. The combination of the statistical/dynamical model with the currently‐existing statistical models shows improved skill over either model individually for the April, June and July outlooks.