Last-moment changes in predicted landfall location of cyclones have become frequent in recent years, underscoring the importance of accurate weather forecasts. 

A recent study provides new insights into the energy dynamics of Tropical Cyclones (TCs), which are highly destructive natural disasters. The team includes researchers led by PhD student Devang Falor from the Geophysical Fluid Dynamics lab headed by Bishakhdatta Gayen at the Centre for Atmospheric and Oceanic Sciences, IISc.

A tropical cyclone gets its energy from the ocean surface. Higher sea surface temperatures (SST) intensify cyclones. SST can cool naturally by either directly losing surface heat (due to various processes like evaporation and wind) or due to the mixing of the warm surface water and the cooler water beneath it. Conventional prediction models do not take into account small‐scale turbulence and mixing of ocean waters, and instead rely on tuning the mathematical parameters to adjust their models to the data.

In the current study, the researchers used high‐resolution large‐eddy simulations to model three-dimensional turbulent flow in the upper ocean, combining these with data collected from sensor-equipped moorings. Their model could accurately predict the upper ocean mixing and SST changes during the passage of a cyclone in the Bay of Bengal.

The researchers suggest that this type of ultra-high turbulence resolving model could improve biases in SST determination, thus leading to better cyclone intensity predictions and seasonal forecasts in general.