Abstract
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.
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Acknowledgements
The research was supported by the following programmes: (1) the National Key Research and Development Program of China (Grant 2016YFC1402608, 2016YFC1401008); (2) the Qingdao National Laboratory for Marine Science and Technology (Grant QNLM2016ORP0105); and (3) the Natural Science Foundation of China (Grant 41527901, U1606405).
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Yu, F., Zhang, X., Chen, X. et al. Altimetry-derived ocean thermal structure reconstruction for the Bay of Bengal cyclone season. Ocean Dynamics 70, 1449–1459 (2020). https://doi.org/10.1007/s10236-020-01409-w
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DOI: https://doi.org/10.1007/s10236-020-01409-w