Observed tropical cyclone-driven cold wakes in the context of rapid warming of the Arabian Sea

ABSTRACT

We present a detailed long-term (1997–2019) analysis of observed cyclone-induced surface cooling (or cold wake) in the Arabian Sea. Here, the analysis is performed for 33 cyclones that drove significant cooling at the sea surface in three different seasons: the pre-monsoon, monsoon and post-monsoon. Our study shows that cyclones can cool the sea surface up to 4.76° C after their passage, depending on the intensity, duration and other factors that contribute to cooling. The monsoon and pre-monsoon cyclones show stronger cooling, but the post-monsoon cyclones exhibit a longer duration (8–10 days) of cooling and slower recovery time (15 days). In general, the pre- and monsoon cyclones exhibit a strong positive correlation with the Latent Heat Flux, whereas the post-monsoon cyclones show a higher correlation with Ekman Pumping Velocity, wind stress and intensity of cyclones. The cold wake composite analysis for the El-Niño, La-Niña and Normal years shows that cyclone-induced cooling is similar in El-Niño and La-Niña years, and the cooling is more dominant during the negative Indian Ocean Dipole (IOD) than that in the positive IOD years. Co-occurrence of positive IOD and La Niña events has led to more intense cyclones in recent decades. The power dissipation index, accumulated cyclone energy and oceanic heat content also show an increasing trend in AS and favour rapid intensification of cyclones. Since the drop in SST normally impedes cyclones from intensification, our study is important and the findings of this study will aid in tropical cyclone predictions. In response to rapid warming of Indian Ocean in recent decades, extreme events such as cyclones are expected to increase in the context of climate change.

KEYWORDS:

• Ocean warming
• Climate change
• cyclones
• cold wakes
• Arabian Sea
• Indian Ocean

Acknowledgements

The authors thank the Department of Science and Technology for the SPLICE project, the Ministry of Human Resource Development, and the Indian Institute of Technology Kharagpur for facilitating and funding the study. The authors also thank all the data managers and the scientists who made available those data for this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data used in this study are publicly available. The analysis codes can be provided on request. The AVHRR-Only are acquired from http://las.incois.gov.in, IMD best-track data are available on http://www.rsmcnewdelhi.imd.gov.in, the ERA5 atmospheric reanalysis data are available at the Copernicus Climate Change Service’s Climate Data Store (http://cds.climate.copernicus.eu), the Ocean Niño Index: https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php, the Dipole Mode Index: https://psl.noaa.gov/gcos_wgsp/Timeseries/Data/dmi.had.long.data, the altimeter products distributed by E.U. Copernicus Marine Service Information (CMEMS): https://cmems-cas.cls.fr/ and the ORAS5 data http://apdrc.soest.hawaii.edu/las/v6/constrain?var = 16561 are found in the given websites. The authors are happy to share the data used in the manuscript upon request. Since the satellite data used are already freely available on public domains, the analysed data can also be provided for any scientific study.