Observational perspective of SST changes during life cycle of tropical cyclones over Bay of Bengal
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Sea surface temperature (SST) plays a significant role in tropical cyclone (TC) formation and intensity evolution, while at the same time, TC induces SST changes during its life cycle. This work deals with the TC-induced SST changes associated with 21 TCs of Bay of Bengal (BoB) during 2006–2013. The SST analyses obtained from National Centre for Oceanic Information Services (INCOIS-SST) and real-time global SST (RTG-SST) are used along with buoy observations. Initial analyses reveal that INCOIS-SST is consistently better than RTG-SST with a good correlation and least root-mean-square error for both post- and pre-monsoon seasons. Overall results demonstrated that mean SST cooling decreases with increased translation speed of TCs within a radius of 50, 100 and 200 km from its centre. Further, a maximum SST cooling of ~2 and ~1.8 °C is noticed in pre- and post-monsoon, respectively, within the radial distance of 50–100 km from centre for slow-moving TCs, 1.2 and 1.0 °C for moderate and 0.9 and 0.7 °C for fast-moving TCs. The TCs formed over the southern BoB have a greater SST cooling up to 200 km radial distance followed by those formed over central and northern BoB in pre- and post-monsoon; however, the magnitudes of cooling in pre-monsoon seasons are greater than post-monsoon season. The minimum cooling over northern BoB may be attributed to the strong haline stratification as compared to the central and southern BoB during both seasons. However, there is a higher magnitude of stratification in post- compared to pre-monsoon, which might play a significant role in lesser SST cooling in post-monsoon season compared to pre-monsoon season.
KeywordsTropical cyclones Sea surface temperature Bay of Bengal Post-monsoon Pre-monsoon
This work is supported through a research grant from Indian National Centre for Ocean Information Services (INCOIS), Hyderabad, Ministry of Earth Sciences, Govt. of India. Second author acknowledges the financial support (ECR/2016/001637) of SERB, Department of Science and Technology (DST), Govt. of India. The authors gratefully acknowledge INCOIS, National Centres for Environmental Prediction (NCEP) for providing SST analysis datasets. India Meteorological Department (IMD) is also acknowledged for making TC observations available. TMI data produced by Remote Sensing Systems and sponsored by the NASA Earth Science MEaSUREs DISCOVER Project (http://www.remss.com) are also acknowledged. Prof Bodo Ahrens of Goethe University, Frankfurt am Main is acknowledged for his support. We would also like to thank the anonymous reviewers for their valuable constructive comments.
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