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Observed sub-daily variability of latent and sensible heat fluxes in the Bay of Bengal during the summer

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Abstract

The sub-daily variability of latent (LHF) and sensible heat flux (SHF) in the Bay of Bengal (BoB) during the summer (May–September) is examined using moored buoys data at 8° N (2008 and 2011), 12° N (2010, 2011, 2012, 2013, 2014, and 2015), and 15° N (2009, 2013, 2014, and 2015) along 90° E. In the weak wind regime (< 6 ms−1), LHF loss from the ocean shows semi-diurnal variability with a higher range at 8° N (~ 21 Wm−2) than at 12° N (~ 13 Wm−2) and 15° N (~ 8 Wm−2). However, LHF depicts a diurnal variability in the strong wind regime (> 6 ms−1) with a range of ~ 13 Wm−2 at 8° N and ~ 17 Wm−2 at 12° N and 15° N. In the strong wind regime, SHF shows heat gain by the ocean with a maximum (minimum) value during the daytime (night), while it shows heat loss from the ocean in the weak wind regime with maximum (minimum) value during the night (daytime). The diurnal range of SHF does not show significant meridional variation in the strong (~ 3.5 Wm−2) and weak (~ 2 Wm−2) wind regime. The difference in sub-daily evolution of air-temperature, air-specific humidity, and wind speed determines distinct evolutions of LHF and SHF in different wind regimes, which appears to be driven by atmospheric boundary layer processes and eastward propagating land-sea breeze signals over the BoB. Finally, we also establish the relationship between sub-daily evolutions of turbulent heat fluxes in the different wind regimes with synoptic conditions associated with the active and break phases of the Indian summer monsoon.

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Acknowledgment

The encouragement and facilities provided by the Director, INCOIS are gratefully acknowledged. The authors thank two anonymous reviewers for their extensive and constructive comments and suggestions which greatly helped to improve the manuscript. HV is grateful to the Director, Indian Institute of Tropical Meteorology for providing the research facility. Jofia Joseph acknowledges support provided by Department of Science and Technology (DST) under the “INSPIRE” fellowship as part of the PhD programme. We thank the Vessel Management Cell (VMC) from NIOT, to provide Sagar Nidhi ship-time for radiosonde operation. We also thank the Captain, crew, and all scientists of the voyage for their support during the data collection. RAMA data quality controlled and distributed by Global Tropical Moored Buoy Array (GTMBA) project office of NOAA/Pacific Marine Environmental Laboratory, RAMA data are available from PMEL (https://www.pmel.noaa.gov/gtmba/pmel-theme/indian-ocean-rama). The TropFlux data is produced under a collaboration between Laboratoired’Océanographie: Expérimentation et Approches Numériques (LOCEAN) from Institut Pierre Simon Laplace (IPSL, Paris, France) and National Institute of Oceanography/CSIR (NIO, Goa, India), and supported by Institut de Recherche pour le Développement (IRD, France). The radiosonde is purchased under the MoES funded project Coupled Physical Processes in the Bay of Bengal and Monsoon Air-Sea Interaction and it is operated during the scientific field campaign under MoES funded INCOIS programme Ocean Observation Network (OON). TropFlux relies on data provided by the ECMWF Re-Analysis interim (ERA-I) and ISCCP projects. Data are available at https://incois.gov.in/tropflux/data_access.jsp. CCMP Version-2.0 vector wind analyses are produced by Remote Sensing Systems. The CCMP data are available at www.remss.com. The OLR data provided by the MoES/IITM, Pune, India, data are available at https://tropmet.res.in. The CERES data are available at https://ceres-tool.larc.nasa.gov/ord-tool/jsp/SYN1degEd41Selection.jsp. The Matlab code for coare3.6 is obtained from ftp://ftp1.esrl.noaa.gov/BLO/Air-Sea/bulkalg/cor3_6/. Graphics were generated using PyFerret. This is INCOIS contribution number 397.

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Correspondence to M. S. Girishkumar.

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Joseph, J., Girishkumar, M.S., Varikoden, H. et al. Observed sub-daily variability of latent and sensible heat fluxes in the Bay of Bengal during the summer. Clim Dyn 56, 917–934 (2021). https://doi.org/10.1007/s00382-020-05512-y

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