Summary/Abstract
Understanding climate change impacts on Tropical Storm (TS) activity is crucial for effective adaptation planning and risk assessment, particularly in densely populated low-lying delta rivers basins like the Ganges and Mekong. The change to TS characteristics with warming is uncertain due to limitations in global climate model resolution and process-representation and storm tracking algorithms (trackers). In this study, the authors use 13 HighResMIP models and two trackers to estimate the uncertainty in projections of TS characteristics. The study found that different trackers producing qualitatively similar but quantitatively different results. The study’s results show a decline (median ∼52%) in the frequency of TS but increase in the strongest TS and Available Cyclone Energy (ACE) of TS over both basins. The higher-resolution models extract TS with much higher intensity and ACE values compared to the lower-resolution models. These results have implications for adaptation planning and risk assessment for TS and suggest the need for further high-resolution modeling studies.