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<p>This study examines the influence of SST and two air-sea fluxes (Flux1 and Flux2) on the forecast of eight Arabian Sea TCs using the Advanced Version of Weather Research and Forecasting (ARW-WRF) model in a horizontal resolution 3&#xa0;km. The findings show that the track for the Cyclones Kyarr, Tauktae, Maha, Chapala, and Mekunu is improved by incorporating SST. In the air-sea flux (ASF) parametrization studies, it was found that updating SST improved the overestimated cyclone intensity. The results indicate that integrating SST feedback typically enhances track prediction and mitigates the overestimation of cyclone intensity by modulating surface heat and moisture fluxes. SST-induced tests show less latent heat flux, less mid- to upper-tropospheric latent heating, and less vertical motion. This makes warm-core structures and wind fields more realistic. Flux1 consistently outperforms Flux2 in replicating cyclone course, intensity, rainfall skill scores, and internal structure among the studied setups. Rainfall analysis indicates that every experiment capture both the light and quite heavy rainfall categories for both cyclones Maha and Tauktae. The simulations Flux2 and SST-Flux1 consistently yield the highest POD, PAG, and TS values for these Cyclones. However, high FAR values suggest that it is difficult to replicate heavy rains for both Cyclones. Overall, the study shows that for high-resolution models of tropical cyclones over the Arabian Sea, accurate representation of air-sea interaction processes, particularly the combined treatment of SST feedback is crucial.</p>

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Role of Air-Sea Flux Parameterization Schemes and Sea Surface Temperature on the Prediction of Arabian Sea Cyclonic Storms using the ARW-WRF Model

  • 期刊论文

  • 发表日期：

    2026年3月18日

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  • Rohini Ashok,
  • Kuvar Satya Singh

摘要

This study examines the influence of SST and two air-sea fluxes (Flux1 and Flux2) on the forecast of eight Arabian Sea TCs using the Advanced Version of Weather Research and Forecasting (ARW-WRF) model in a horizontal resolution 3 km. The findings show that the track for the Cyclones Kyarr, Tauktae, Maha, Chapala, and Mekunu is improved by incorporating SST. In the air-sea flux (ASF) parametrization studies, it was found that updating SST improved the overestimated cyclone intensity. The results indicate that integrating SST feedback typically enhances track prediction and mitigates the overestimation of cyclone intensity by modulating surface heat and moisture fluxes. SST-induced tests show less latent heat flux, less mid- to upper-tropospheric latent heating, and less vertical motion. This makes warm-core structures and wind fields more realistic. Flux1 consistently outperforms Flux2 in replicating cyclone course, intensity, rainfall skill scores, and internal structure among the studied setups. Rainfall analysis indicates that every experiment capture both the light and quite heavy rainfall categories for both cyclones Maha and Tauktae. The simulations Flux2 and SST-Flux1 consistently yield the highest POD, PAG, and TS values for these Cyclones. However, high FAR values suggest that it is difficult to replicate heavy rains for both Cyclones. Overall, the study shows that for high-resolution models of tropical cyclones over the Arabian Sea, accurate representation of air-sea interaction processes, particularly the combined treatment of SST feedback is crucial.