The Role of Ocean–Atmosphere Interactions in Tropical Cyclone Intensity Predictability

Abstract

Abstract The negative feedback between tropical cyclone (TC) intensity and sea surface temperature (SST) plays an important role in TC development. In this study, ocean–atmosphere coupled and uncoupled ensemble forecasts are conducted to investigate the dynamics of error growth and predictability of TC intensity in an ocean–atmosphere coupled system. For the TC–ocean coupled system, the TC intensity–SST negative feedback is the essential mechanism to reduce the error growth of TC intensity by two routes, and thereby improves the TC intensity predictability. For the first route (atmosphere-limited route), the TC-induced SST cooling slows the intensification rate of the TC and weakens the final TC intensity, thereby reducing the error growth of TC intensity. In this route, the TC intensity spread is limited by the magnitude of TC intensity, while SST can be regarded as an environmental forcing. For the second route (atmosphere–ocean mutually influenced route), the interaction between the TC intensity spread and SST spread is dominant. The increasing TC intensity spread could lead to an increase in SST cooling spread, and then reduce the TC intensity spread through the negative feedback. In other words, the more (less) intense TC produces stronger (weaker) SST cooling, and thereby limits (enhances) further TC intensification in an ensemble forecast. In the second route, initial ocean temperature uncertainty could suppress the TC intensity spread reduction. Significance Statement Tropical cyclones force the sea surface and can lead to its cooling. This cooled sea surface can then suppress tropical cyclone intensification. The purpose of this study is to better examine the influence of such an interaction between a tropical cyclone and the ocean on tropical cyclone forecasts. We explore how accurately representing the interaction can improve the capacity to forecast tropical cyclone intensity. Given that many weather forecasting centers have considered this interaction in their models, this study should help them to understand and improve their forecasts.