Prediction of Seasonal Tropical Cyclone Activity in the NUIST-CFS1.0 Forecast System

Prediction skill for the seasonal tropical cyclone (TC) activity in the Northern Hemisphere is investigated using the coupled climate forecast system (version 1.0) of Nanjing University of Information Science and Technology (NUIST-CFS1.0). This assessment is based on the seven-month (May to November) hindcasts consisting of nine ensemble members during 1982–2019. The predictions are compared with the Japanese 55-year Reanalysis and observed tropical storms in the Northern Hemisphere. The results show that the overall distributions of the TC genesis and track densities in model hindcasts agree well with the observations, although the seasonal mean TC frequency and accumulated cyclone energy (ACE) are underestimated in all basins due to the low resolution (T106) of the atmospheric component in the model. NUIST-CFS1.0 closely predicts the interannual variations of TC frequency and ACE in the North Atlantic (NA) and eastern North Pacific (ENP), which have a good relationship with indexes based on the sea surface temperature. In the western North Pacific (WNP), NUIST-CFS1.0 can closely capture ACE, which is significantly correlated with the El Niño–Southern Oscillation (ENSO), while it has difficulty forecasting the interannual variation of TC frequency in this area. When the WNP is further divided into eastern and western subregions, the model displays improved TC activity forecasting ability. Additionally, it is found that biases in predicted TC genesis locations lead to inaccurately represented TC–environment relationships, which may affect the capability of the model in reproducing the interannual variations of TC activity.