Sea surface temperature (SST) uncertainty is one of the major sources of error in tropical cyclone rapid intensification (RI) forecasts, yet the spatial sensitivity of these errors remains poorly understood. Specifically, it is still unclear which spatial pattern of SST errors has the greatest impact on RI enhancement under nonlinear model dynamics. Using the Conditional Nonlinear Optimal Perturbation of boundary condition (CNOP-B) method within a cloud-resolving model, we identify the SST pattern most favorable for affecting RI in Super Typhoon Nanmadol (2022) under fully nonlinear dynamics. The CNOP-B produces a track-following warm-core anomaly, which strengthens RI and advances its onset by about 30 hours relative to the control simulation. The associated SST-sensitive region is confined to a narrow corridor within three times the radius of maximum wind along the storm track, highlighting that near-core ocean conditions control RI error growth. The optimal SST perturbation is strongly asymmetric, with larger warming on the right side of the storm track. Sensitivity experiments demonstrate that RI is more sensitive to right-of-track warming, which is driven by two synergetic mechanisms. First, the superposition of the storm’s cyclonic circulation and forward translation, together with an enhanced background pressure gradient on the right side, strengthens near-surface winds and local surface enthalpy fluxes. Second, forward trajectory analysis shows that boundary-layer air parcels originating on the right side are more readily ingested into the storm’s inner-core circulation near the eyewall, improving the efficiency with which surface flux anomalies intensify convection and vortex. These results provide a quantitative basis for SST-targeted observations and may help improve RI prediction.

Predictability,tropical cyclone,rapid intensification