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This study investigates the effect of adaptive (or targeted) observation on improving the midrange (30 days) forecast skill of ocean state of the South China Sea (SCS). A region associated with the South China Sea Western Boundary Current (SCSWBC) is chosen as the “target” of the adaptive observation. The Conditional Nonlinear Optimal Perturbation (CNOP) approach is applied to a three‐dimensional ocean model and its adjoint model for determining the sensitive region. Results show that the initial errors in the sensitive region determined by the CNOP approach have significant impacts on the forecast of ocean state in the target region; thus, reducing these initial errors through adaptive observation can lead to a better 30 day prediction of ocean state in the target region. Our results suggest that implementing adaptive observation is an effective and cost‐saving way to improve an ocean model's forecast skill over the SCS. Adaptive observation can effectively improve the forecast in SCSWBC regionThe nonlinear propagation of initial errors is important for SCSWBC regionThe CNOP approach is applied in adaptive observation through a 3‐D ocean model