Helicity and potential vorticity in surface turbulence

Koprov, B. M.; Koprov, V. M.; Kurgansky, M. V.; Chkhetiani, О. G.

doi:10.1134/s0001433815060092

Cited by 18 publications

(1 citation statement)

References 5 publications

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“…al., 2020;Borhani et al, 2022). Additionally, a quantity known as helicity serves as an indicator of atmospheric vortex strength, applicable to phenomena such as supercell thunderstorms, TCs, tornadoes, and dust devils(Hide, 1989 and2002;Kurgansky, 2008 and2017;Koprov, 2015;Farahani et al, 2017;Li et al, 2022). Among the thermodynamic and dynamic factors considered, low-level environmental helicity exhibits the strongest positive correlation with the size of TC outer-core(Li et al, 2022).…”

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

Karami,

ghassabi,

Khansalari

2024

Preprint

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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 three TCs (Biparjoy, Shaheen, and Mekunu), that developed in the AS and followed various paths were simulated using the WRF model. The most TCs occurred in the Indian Ocean during the negative or neutral phase of El Niño-Southern Oscillation (ENSO) and neutral phase of the Indian Ocean Dipole (IOD). These storms typically formed in the pre-monsoon season in the eastern AS, moving north/northeastward and in the post-monsoon, in southern regions of the AS and moved westward. Satellite analysis revealed the presence of ice-phase cirrus clouds with significant thickness at higher altitudes near the storm's eye. The simulation showed that TCs moved towards areas with lower pressure and wind shear. In well-developed TCs, a 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 and tropopause folding were occured. The WRF model underestimated the speed of Shaheen and its intensity and precipitation extent. In the Biparjoy, the model indicated precipitation over a broader area around the storm center. The model suggested less precipitation in regions surrounding the storm center in Mekunu. The comparison of daily cumulative precipitation between the GPM data and the WRF output revealed the highest correlation and the lowest RMSE for the Biparjoy.

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