Vertical characteristics of tropical cyclone size over the North Atlantic, Eastern North Pacific, and North Indian Oceans
摘要
Based on ERA5 reanalysis data, this study analyzes the vertical distribution of tropical cyclone (TC) horizontal sizes across the North Atlantic (NA), eastern North Pacific (ENP), and North Indian Ocean (NIO) from 1998 to 2018, and examines their relationships with intensity, environmental factors, and ENSO. The results reveal distinct vertical and basin-dependent differences. In all three basins, the median radius of vorticity (Rvor) first decreases from 10 m to about 950 hPa, then increases with height in the lower troposphere, and finally decreases toward the upper troposphere. The level of the maximum, however, differs between basins: in the ENP the largest sizes occur near the surface, whereas in the NA and NIO they peak at 700–750 hPa. At the upper levels, Rvor at 200 hPa (Rvor200) in the NIO (155 km) is larger than that in the NA (151 km) and the ENP (148 km), indicating a broader upper-level circulation over the NIO. The relationship between intensity and size also varies with basin and height: Rvor200 is positively correlated with intensity, whereas Rvor at 10 m (Rvor10) shows negative correlations in the NA and NIO but positive correlations in the ENP. Environmental analysis reveals that relative humidity at 600 hPa (RH600) is positively correlated with mid-level TC size across all three basins, and the mean rain rate within a 500-km radius of the TC center shows positive correlations with upper-level TC size in the ENP and NIO. Vertical wind shear (VWS) significantly suppresses the upper-level size in all three basins, while relative sea surface temperature (RSST) is negatively correlated with the near-surface size, most notably in the NA and NIO. The ENP exhibits strong spatial correlations among TC sizes across vertical levels, yet generally smaller overall sizes, likely due to low RSST. ENSO modulates TC size basin-specifically: ENP TCs are larger during El Niño, while NA and NIO have more favorable environments during La Niña. Empirical orthogonal function (EOF) analysis highlights SST anomalies as key drivers of monthly variability. The findings highlight the importance of considering the three-dimensional structure of TCs in understanding their evolution.