A satellite altimeter measures sea surface height (SSH) along the nadir track. Multiple satellite altimeters have been in orbit, and the measurements been merged for mapping mesoscale eddies of ~100 km in size in the oceans. The capability of the mapped SSH for resolving mesoscale eddies depends on mapping algorithms. A two-dimensional variational (2DVAR) algorithm was implemented to generate mapped SSH at a grid size of 1/12° in the South China Sea. A range of comparisons were performed between the mapped SSH and the commonly used AVISO (Archiving, Validation, and Interpretation of Satellite Oceanographic satellite data) mapped SSH data product at a grid size of 1/8° and 1/4°. The effective resolution, which represents the spatial scale that the data can resolve, was examined. The effective resolution of the mapped SSH using the 2DVAR algorithm is approximately 100 km, while it is 250 km with the 1/8° and 1/4° AVISO data products. The difference in the effective resolution results from the difference in the background state and thus the background error. The result suggests that the effective resolution of the mapped data could be increased by choosing a background state so that the associated errors could have a smaller decorrelation length scale.

As a category-3 typhoon, Hato (2017) experienced the notable rapid intensification (RI) over the hot sea surface before its landfall. The RI process and the influences of local sea surface temperature (SST) patterns on the evolution of Hato were well captured and carefully investigated using a high-resolution air–sea coupled model. To further explore the close relationship between the radial distributions of SST and storm evolution, a sensitive experiment with time-fixed SST was also performed. Results showed that the time-fixed SST experiment produced earlier RI following the rapid core structure adjustment, as higher SST in the core region was found favorable to increasing the near-surface water vapor and latent heat flux. Strong updrafts were thus facilitated inside the eyewall, inducing the eyewall contraction and RI of the storm. In contrast, cooler SST inside the core region should account for the delay of RI as the intense convection located in the outer rainbands, inhibiting the transportation of energy into the inner-core. Momentum tendency analysis also proves these mechanisms. Therefore, not only the value of SST but also its radial-gradient, plays an important role in the evolution of tropical cyclones, highlighting the need for an advanced air–sea coupled model.

Grasping the physical interactions when two tropical cyclones (TCs) (TC) are in proximity is essential for boosting the accuracy of TC forecasts. This study dissects an uncommon scenario wherein the merging with Tropical Depression 13 W significantly hastened the rapid weakening of Super Typhoon Hinnamnor (2022), utilizing comparative experiments with and without 13 W in simulation's initial field. The findings reveal strong correlations between the merger, amplified environmental vertical wind shear (VWS), and Hinnamnor's consecutive weakening, unfolding in two stages— “top‐down” (Stage 1) and “bottom‐up” weakening (Stage 2) stage. In Stage 1, 13 W led to downdrafts from upper level, hindering the eyewall updrafts and weakening the warm core. In Stage 2, 13 W merged into Hinnamnor's outer rainband, introduced low‐entropy air into the boundary layer and also vied with the eyewall for energy. This research emphasizes that even minor, less‐intense vortices can have profound impacts on the rapid intensity change in TCs.

High-resolution mooring observations captured diverse upper-ocean responses during typhoon passage, showing strong agreement with satellite-derived sea surface temperature and salinity. Analysis indicates that significant wind-induced mixing drove pronounced near-surface cooling and salinity increases at the mooring site. This mixing enhancement was predominantly governed by rapid intensification of near-inertial shear in the surface layer, revealed by mooring observations. Unlike shear instability, near-inertial horizontal kinetic energy displays a unique vertical distribution, decreasing with depth before rising again. Interestingly, the subsurface peak in diurnal tidal energy coincides vertically with the minimum in near-inertial energy. While both barotropic tidal forcing and stratification changes negligibly influence diurnal tidal energy emergence, significant energy transfer occurs from near-inertial internal waves to the diurnal tide. This finding highlights a critical tide–wave interaction process and demonstrates energy cascading within the oceanic internal wave spectrum.

Rapid expansion (RE) of tropical cyclones (TCs), which quickly increases their outer size and destructive potential, has not been thoroughly investigated in the merger of binary TCs. This study examines a rare case where typhoon Hinnamnor (2022) experienced RE during its merger with tropical depression (TD) 13W, growing from 125 to 275 km within 24 hr. Two experiments (with/without 13W in the initial field of simulation) were conducted to examine the roles of merger on RE. Only the experiment involving TD 13W successfully replicated the observed changes in size and intensity. While the favorable large‐scale flow caused relatively steady growth and contributed approximately 70% to the total expansion, the binary TC interaction abruptly induced the remaining 30% contribution by substantial asymmetric positive radial flux of vorticity into the outer core on the mesoscale. The influx of vorticity resulted from the in‐phase superposition of the positive vorticity anomaly of 13W and enhanced boundary layer inflow. On the basis of large‐scale low‐level southwesterlies in downshear, the binary interaction with 13W introduced inflow in the downwind region, while the stratiform‐induced mesoscale descending inflow driven by latent cooling also assisted in the enhancement of inflow. By pinpointing the role of binary TC interaction in size expansion, this study shows that accurately describing such interactions is essential for improving TC size forecasting.