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Atmospheric optical turbulence significantly impacts the efficacy of adaptive optics and various laser systems. The parameter known as the atmospheric refractive index structure constant, or C2n, is crucial for characterizing this turbulence. In response to this challenge, we have developed a model utilizing the Whale Optimization Algorithm combined with a Support Vector Machine (WOA-SVM) designed to estimate atmospheric optical turbulence profiles along Eastern China’s coast. The WOA-SVM model uses standard atmospheric sounding data from the region to forecast turbulence profiles at different times, subsequently comparing these estimates with actual observations. Our error analysis indicates that the model’s estimates have root mean square errors (RMSE) of 0.4441, 0.3012, 0.4734, and 0.4904 for the respective times, while correlation coefficients range from 85.10% to 93.66%. The research shows that despite minor discrepancies in atmospheric optical turbulence profiles estimated by the WOA-SVM model using standard atmospheric sounding data and those measured directly, the general trend is consistent. This consistency confirms the WOA-SVM model’s practicality for estimating atmospheric optical turbulence in coastal areas. Therefore, the study made an attempt for direct estimation of turbulence profiles using routine meteorological data and paves the way for future model development in this domain.
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