Analysis and simulation of three tropical cyclones with different paths in the Arabian Sea

The Indian Ocean and the Arabian Sea (AS) are regularly influenced by tropical cyclones (TCs). In this study, the TCs in the AS during the period 1980–2022 were examined, and their correlation with the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) was identified. Three TCs Biparjoy, Shaheen, and Mekunu, that developed in the AS andF followed various paths were simulated using the WRF model. Climatic analysis indicated that most TCs occurred in the Indian Ocean during the negative or neutral phase of ENSO, as well as neutral phase of the IOD. These storms typically formed in the pre-monsoon season in the eastern AS, moving predominantly northward and northeastward. However, during the post-monsoon season, they often developed in more southern regions of the sea and shifted westward. Satellite product analysis of these three TCs revealed the presence of ice-phase cirrus clouds with significant thickness at higher altitudes near the storm’s eye. The simulation showed an intense low-pressure at the storm’s location and TCs moved towards areas with lower pressure and less wind shear. In well-developed TCs, a significant relative humidity reduction in the eye region and moisture gradient between rain bands and subsiding cold air areas were observed. During the peak days of cyclonic activity, the helicity reached its maximum. The vertical structure of potential vorticity displayed tropopause folding in the upper and middle levels of troposphere. The WRF model underestimated the speed of TC movement and the intensity and extent of precipitation during Shaheen TC. In the case of Biparjoy, the model indicated precipitation over a broader area around the storm center. The simulation of the Mekunu tropical storm suggested lesser precipitation in regions surrounding the storm center. The quantitative comparison of daily cumulative precipitation between the GPM satellite product and the WRF output across all grid points revealed the highest correlation and the lowest RMSE for Biparjoy.