The ocean thermal structure (OTS) is a significant element that affects tropical cyclone (TC) intensities, as energy drawn from the ocean fuels TCs. Satellite altimetry can be used to derive the OTS for TC research. The cooling of sea surface temperature (SST) caused by TCs is closely related to the OTS and differs according to differences in the OTS in different regions. However, the accuracy of existing methods in spatially describing the OTS is not sufficient. To overcome the limited resolution and accuracy of current OTS-derived methods, a ridge regression model is proposed for the Bay of Bengal (RRBOB) in this paper to derive isotherms for 47 layers (D5–D28) from satellite altimetry data and from in situ Argo thermal profiles. RRBOB improves the derivation accuracy by allowing small deviations to achieve higher precision than unbiased estimators. Compared with in situ observations, most errors are limited to within 20%. The accuracy of the derivations is within a reasonable range, and no significant biases are observed. Although the ridge regression derivation method has limitations in predicting the temperature inversion, which occurs in the northern of the BOB during the periods of post monsoon and winter, the derivation can characterize the subsurface OTS in detail in most regions. The ability to monitor the subsurface ocean will improve seasonal predictions of TCs.

海洋热结构（OTS）是影响热带气旋（TC）强度的重要因素，因为从海洋吸收的能量为TC提供了能量。卫星测高可用于推导用于TC研究的OTS。TC引起的海表温度降温与OTS密切相关，并且根据不同地区OTS的差异而有所不同。但是，现有方法在空间上描述OTS的准确性不足。为了克服当前OTS衍生方法的有限分辨率和准确性，本文针对孟加拉湾（RRBOB）提出了岭回归模型，以从卫星测高数据和原位推导47层（D5-D28）的等温线。 Argo温度曲线。RRBOB通过允许小的偏差获得比无偏估计量更高的精度，从而提高了推导精度。与现场观察相比，大多数误差限制在20％以内。推导的精度在合理范围内，没有观察到明显的偏差。尽管脊回归回归推导方法在季风后和冬季期间BOB北部发生的温度反演的预测中存在局限性，但该推导可以在大多数地区详细描述地下OTS的特征。监测地下海洋的能力将改善对热带气旋的季节性预测。尽管脊回归回归推导方法在季风后和冬季期间BOB北部发生的温度反演的预测中存在局限性，但该推导可以在大多数地区详细描述地下OTS的特征。监测地下海洋的能力将改善对热带气旋的季节性预测。尽管脊回归回归推导方法在预测季风和冬季后BOB北部发生的温度反演方面存在局限性，但该推导可以在大多数地区详细描述地下OTS的特征。监测地下海洋的能力将改善对热带气旋的季节性预测。