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The study investigates the rapid intensification (RI) of tropical cyclones (TCs) in the Northwestern Pacific. We found that rapid changes in the maximum wind speed (Vmax) and the minimum central pressure (Pmin) are not always concurrent. RI cases can be categorized into three types: (a) RIv, only Vmax strengthens rapidly; (b) RIp, only Pmin decreases rapidly; (c) RIpv, rapid changes in Vmax and Pmin occur concurrently. At the onset of RI, RIv‐type TCs exhibit the weakest intensity and the smallest size, with deep convection concentrated in the inner‐core region; RIp‐type TCs are characterized by the strongest cyclone intensity and the largest outer‐core size, with strong convection covering the inner‐ and outer‐core regions; RIpv‐type TCs show moderate intensity, size, and convection distribution. For RIpv, significant strengthening of wind profile is concentrated in the inner‐core region, while for RIp it is more prominent in the outer‐core. Plain Language Summary: The rapid intensification (RI) of tropical cyclones (TCs) continues to pose challenges in both operational forecasting and scientific research. The maximum wind speed (Vmax) and the minimum central pressure (Pmin) are two commonly used TC intensity indicators. In most of existing studies, one single indicator (usually Vmax) is used to investigate the RI process. Whether there is a difference between RI cases defined by 24‐hr strengthening of Vmax and 24‐hr deepening of Pmin is an issue deserving discussion. The study found that rapid changes in Vmax and Pmin are not always concurrent. In the cases where only Vmax strengthens rapidly, the outer‐core size of TC expands slowly. While in the cases where only Pmin deepens rapidly, the enhancement of outer circulation is distinctive. Since the Pmin, as an integral variable, reflects TC information of both the intensity and the size, RI cases classified via these two commonly used indicators (Vmax and Pmin) could help us further understand the relationship between TC intensity and size. Key Points: Rapid changes in the maximum wind speed (Vmax) and the minimum central pressure (Pmin) are not always concurrent in tropical cyclones (TCs)TCs that only experience a rapid increase in Vmax (RIv) tend to have a significantly weaker lifetime maximum intensityThe evident expansion of the outer circulation occurs in TCs of which only Pmin deepens rapidly (RIp) [ABSTRACT FROM AUTHOR]

This study aimed to explore the predictability of the most long‐lived tropical cyclone (TC) Freddy in 2023 while it traversed westward across the southern tropical Indian Ocean during the first 18 days of its existence. Global ensemble forecasts revealed southward track deflection and intensity underestimation of Freddy. We identified three key factors contributing to the limited predictability of Freddy, which are associated with the Mascarene High, Storm Dingani, and Freddy itself. The large track errors of Freddy can be attributed to the underestimated strength of the Mascarene High, the more northeastern position of Dingani, and the presence of excessively large or small sizes of Freddy. These findings were further validated through a high‐resolution regional model. Specifically, Freddy's track and intensity most closely matched the observations when these three factors were most closely represented. It underscores the pivotal role played by the interaction between TCs and multi‐scale systems in TC forecasts. Plain Language Summary: In 2023, Storm Freddy emerged as the most long‐lived tropical cyclone (TC) in record, lasting 35 days over the southern tropical Indian Ocean and spanning both weather and sub‐seasonal to seasonal time ranges. The primary objective of this study is to understand the factors contributing to the poor predictability of Freddy in forecasts spanning over 2 weeks. This holds significant importance as our understanding about the ability of the numerical models to predict long‐lived TCs remains limited. Using over 7,000 global ensemble forecasts from five global Numerical Weather Prediction (NWP) centers and a high‐resolution regional model, we identified three key factors contributing to the limited predictability of Freddy: the strength of the Mascarene High, the position of Storm Dingani (2023), and the size of Freddy. In large track‐error results of the global forecasts and regional simulations for Freddy, the strength of the Mascarene High was underestimated, Dingani was located further northeast, and Freddy was either too large or too small. Our investigation emphasizes the crucial role played by the interaction between the TC and multi‐scale systems in TC forecasts. This is meaningful for the improvement of Numerical Weather Prediction models to deal with extreme TC events in the future. Key Points: Due to the long lifespan of Storm Freddy, many forecasting challenges across several numerical models aroseThe limited predictability of Freddy was related to the underestimated Mascarene High and the more northeastern position of Storm DinganiThe inaccurately forecasted size of Freddy, whether excessively large or small, also contributed to the large track errors [ABSTRACT FROM AUTHOR]