Evaluation of Tropical Cyclone Heat Potential Estimates from Ocean Models in the Northern Indian Ocean using in-situ Observations

Accurate estimation of Tropical Cyclone Heat Potential (TCHP) is critical for operational forecasting of tropical cyclone (TC) intensification in the Northern Indian Ocean (NIO). This study validates TCHP estimates derived from three ocean general circulation models, the Regional Ocean Modeling System (ROMS), the Hybrid Coordinate Ocean Model (HYCOM), and the Global Ocean Data Assimilation System (GODAS), using in-situ observations from eight OMNI buoys and 1,899 ARGO profiling floats across the Arabian Sea and Bay of Bengal during January 2023–December 2024. A three-stage hierarchical validation framework employing temporal and spatial matching protocols was implemented. Results indicate that assimilative models (GODAS, HYCOM) consistently outperform the non-assimilative regional model (ROMS) in reproducing observed TCHP with lower root mean square error (RMSE: 7.9–8.7 kJ/cm 2 vs. 11.6–14.9 kJ/cm 2 ), higher correlation coefficients (r: 0.86–0.89 vs. 0.67–0.76), and reduced systematic bias across both basins. The assimilative frameworks of HYCOM and INCOIS-GODAS, together with the hybrid-coordinate system of HYCOM, enable a better representation of thermocline dynamics and seasonal heat content variability, particularly in the complex stratification regime of the Bay of Bengal. However, ROMS shows good skill in representing the spatial and temporal variability of TCHP, with only marginal differences likely associated with the absence of direct data assimilation within the model domain. Overall, all three modelling systems show good agreement with observations, while data assimilation and advanced vertical coordinate schemes enhance accuracy and consistency, highlighting their use for operational TCHP analysis and forecasting, and their contribution to tropical cyclone intensity prediction, early warning systems, and tropical cyclone-related studies in the NIO.