Effect of uncertainties in sea surface temperature dataset on the simulation of typhoon Nangka (2015)

Abstract

Accurate sea surface temperature (SST) datasets are critical to typhoon simulation/prediction, especially to the intensity forecast. In this study, four SST datasets were used to perform a series of experiments to examine the effects of different SST datasets and a cold SST feature on the simulation of typhoon Nangka (2015) using the Advanced Weather Research and Forecast model. Results show that the simulated typhoon intensity is very sensitive to the SST dataset used. The experiments with the SST dataset in which a cold SST feature to the south of the storm track was present/absent succeeded/failed to simulate the peak intensity and the subsequent rapid weakening of typhoon Nangka. Among the four datasets examined, only the SST dataset from the National Centers for Environmental Prediction Global Forecast System analysis captured the cold SST feature, which was likely induced by typhoon Chan-Hom (2015) before the arrival of typhoon Nangka.