Tropical Cyclones Across Global Basins: Dynamics, Tracking Algorithms, Forecasting, and Emerging Scientometric Research Trends

ABSTRACT Tropical cyclones (TCs) pose significant threats to life and property across global ocean basins, and forecasting their structural evolution, track, and intensity remains a major scientific challenge. This review synthesizes the current understanding of TCs across major basins, that is, the Pacific, Atlantic, and North Indian Oceans, with a focus on the key environmental factors influencing TC behavior, such as sea surface temperature (SST), vertical wind shear (VWS), mid‐tropospheric moisture, and land surface conditions. A special emphasis is further placed on the comparative skill of operational numerical weather prediction (NWP) models employed globally for TC forecasting. The review also discusses TC tracking algorithms, structural diagnostics, and the evolution of forecasting frameworks, along with emerging research trends revealed through scientometric mapping. The 51 peer‐reviewed studies were selected and analyzed, and scientometric analysis was conducted on these 51 studies. Out of these selected studies, 37.25% focused on the Pacific, 23.52% on the Atlantic, and 17.64% on the North Indian Ocean (NIO, that is, the Bay of Bengal (BoB) and Arabian Sea). Out of these 51 studies, it has been found that while most studies utilized satellite‐based methods, data assimilation (DA) techniques were emerging during 2006–2013, gaining momentum with machine learning (ML) applications post‐2019. Notably, research since 2019 highlights a shift toward machine‐based algorithms aimed at improving intensity predictions. While these AI/ML‐based TC prediction models show promise, challenges remain in scalability, interpretability, and integration into forecasting workflows. The review emphasizes the need for assimilating next‐generation satellite datasets (e.g., CYGNSS, TROPICS, rapid‐scan AMVs, LIDAR), improved storm surge modeling, and real‐time ensemble forecasting with high spatiotemporal resolution. Ultimately, advancing TC forecasting requires a collaborative, interdisciplinary approach involving model developers, operational centers, and observational programs. Bridging short‐term forecasting with climate‐informed strategies will be pivotal in enhancing global resilience to cyclonic hazards in a warming world.