Spatiotemporal variation and mechanisms of temperature inversion in the Bay of Bengal and the eastern equatorial Indian Ocean
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Abstract: In the northern Bay of Bengal, the existence of intense temperature inversion during winter is a widely accepted phenomenon. However, occurrences of temperature inversion during other seasons and the spatial distribution within and adjacent to the Bay of Bengal are not well understood. In this study, a higher resolution spatiotemporal variation of temperature inversion and its mechanisms are examined with mixed layer heat and salt budget analysis utilizing long-term Argo (2004 to 2020) and RAMA (2007 to 2020) profiles data in the Bay of Bengal and eastern equatorial Indian Ocean (EEIO). Temperature inversion exists (17.5% of the total 39 293 Argo and 51.6% of the 28 894 RAMA profiles) throughout the year in the entire study area. It shows strong seasonal variation, with the highest occurrences in winter and the lowest in spring. Besides winter inversion in the northern Bay of Bengal, two other regions with frequent temperature inversion are identified in this study for the first time: the northeastern part of the Bay of Bengal and the eastern part of the EEIO during summer and autumn. Driving processes of temperature inversion for different subregions are revealed in the current study. Penetration of heat (mean ~25 W/m2) below the haline-stratified shallow mixed layer leads to a relatively warmer subsurface layer along with the simultaneous cooling tendency in mixed layer, which controls more occurrence of temperature inversion in the northern Bay of Bengal throughout the year. Comparatively lower cooling tendency due to net surface heat loss and higher mixed layer salinity leaves the southern part of the bay less supportive to the formation of temperature inversion than the northern bay. In the EEIO, slightly cooling tendency in the mixed layer along with the subduction of warm-salty Arabian Sea water beneath the cold-fresher Bay of Bengal water, and downwelling of thermocline creates a favorable environment for forming temperature inversion mainly during summer and autumn. Deeper isothermal layer depth, and thicker barrier layer thickness intensify the temperature inversion both in the Bay of Bengal and EEIO.
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Figure 1. The number distribution of Argo profiles at 1°×1° grid in the Bay of Bengal and the eastern equatorial Indian Ocean (EEIO). The red dashed line is the boundary between the Bay of Bengal and the EEIO. The eight RAMA mooring buoy are marked by the red diamonds. GBM is short for the Ganges-Brahmaputra-Meghna Rivers; SL is short for the country name Sri Lanka; and IND is for Indonesia.
Figure 2. Pictorial presentation of different parameters related to temperature inversion (a), and non-inversion (b) profiles. MLD: mixed layer depth; ILD: isothermal layer depth.
Figure 3. Monthly variations in ILD (a), and mixed layer depth (b) using two different calculation methods.
Figure 4. Distribution of temperature inversion profiles in various seasons over 2004 to 2020 (a–d), and monthly percentages of temperature inversion profiles (e).
Figure 5. Season-wise spatial distribution of ∆T (a–d), thicknesses of inversion layer (e–h), and depth of peak temperature with the contours of initial inversion depth (i–l).
Figure 6. Spatial distribution of the mixed layer temperature (a–d), mixed layer salinity (e–h) of temperature inversion profiles, and monthly variation in mixed layer temperature (i), and mixed layer salinity (j).
Figure 7. Spatiotemporal distribution of net surface heat flux (a–d), and E-P (e–h). Black dots refer to the location of temperature inversion profiles. Mixed layer (ML) heat budget and salt budget in the northern Bay of Bengal (i, j), southern Bay of Bengal (k, l), and EEIO (m, n), respectively.
Figure 8. Basin averaged monthly variation of the 32.5-isohaline depth and the percentages of temperature inversion (a), water column stratification (s−2) in temperature inversion and non-inversion profiles (b), spatiotemporal distribution of ∆S (c–f), monthly variation of ∆T and ∆S (g), and their correlations (h).
Figure 9. Spatiotemporal distribution of the 35-isohaline depth overlaid with the salinity (contours) at 50-m depth, and occurrence of temperature inversion (black dots).
Figure 10. Spatiotemporal distribution of the depth of 26°C isotherm overlaid with the temperature (contours) at 50-m depth, and surface current vectors (a–d), monthly variation of 35-isohaline depth, depth of 26°C isotherm, and temperature inversion profiles along the EEIO (e).
Figure 11. Spatiotemporal distribution of the wind turbulent kinetic energy (a–d), and monthly variation in wind turbulent kinetic energy and temperature inversion (e).
Figure 12. Spatial distribution of the amount of heat penetrated below mixed layer depth (MLD) (a–d), monthly distribution of the amount of heat penetrated below MLD (e), MLD in temperature inversion profiles, and incoming shortwave radiation (f), and stratification in the surface water (g).
Figure 13. Season-wise spatial distribution of mixed layer depth (MLD) (shading) overlaid with contours of initial inversion depth (a–d), isothermal layer depth (ILD) (shading) with contours of depth of peak temperature (e–h), and barrier layer thickness (BLT) (shading) with the contours of thickness of inversion layer (i–l).
Figure 14. A sketch of the spatiotemporal distribution and dominant formation mechanisms of temperature inversion in the Bay of Bengal and EEIO. Green dots refer to the location of temperature inversion profiles.
Table 1. Basin averaged monthly mean of different characteristic parameters of temperature inversion derived from Argo data
Parameters Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sept. Oct. Nov. Dec. Inversion profiles 1 518 1 316 567 98 106 226 214 239 427 496 718 978
Inversion/%22.0 19.1 8.2 1.4 1.5 3.3 3.1 3.5 6.2 7.2 10.4 14.2
∆T/°C1.6 1.3 0.7 0.4 0.3 0.4 0.3 0.5 0.3 0.4 0.6 0.9
Initial inversion depth/m19.4 20.9 21.6 11.1 17.3 22.9 29.3 21.5 16.5 14.9 14.8 18.0
Depth of peak temperature/m52.9 54.7 48.8 21.2 31.4 41.5 53.5 43.5 33.1 30.4 34.6 42.6
Thickness of the inversion layer/m52.2 52.6 43.2 19.4 23.2 28.1 34.5 35.1 27.0 26.1 31.1 38.5 
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Table 2. Temporal mean over 2007 to 2020 of different characteristic parameters of temperature inversion, and seasonal distribution of inversion in different RAMA buoy positions
RAMA position Total profiles Percentage of total TI/% Mean ∆T/°C Mean
DPT/mWinter
/%Spring
/%Summer
/%Autumn
/%0°, 80.5°E 3 511 2.2 0.32 51.7 24.7 7.2 47.4 20.6 0°, 90°E 3 612 2.3 0.28 55.7 23.2 8.5 26.8 41.5 1.5°S, 80.5°E 4 236 3.3 0.42 27.6 25.4 15.6 32.0 27.0 4°S, 80.5°E 3 513 1.5 0.34 29.5 20.8 22.6 28.3 28.3 4°N, 90°E 2 282 3.9 0.36 35.5 48.9 13.3 6.7 31.1 8°N, 90°E 2 910 6.1 0.35 48.4 70.4 10.6 2.8 16.2 12°N. 90°E 4 611 7.8 0.38 47.5 70.7 12.0 8.4 8.9 15°N, 90°E 4 219 24.5 0.73 44.4 70.6 6.2 10.9 12.3 Note: TI stands for temperature inversion and DPT stands for depth of peak temperature. Temperature inversion along EEIO during summer and autumn, and along the Bay of Bengal during winter are remarkable, and thus, shown to be “bold italic” faces.
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Table 3. Correlation between the number of temperature inversion with associated parameters in the study domain
MHF NHF MLT MFWF E–P MLS ∆S ∆D 32.5 isohaline W.TKE Number of temperature inversion −0.76 −0.79 −0.91 0.41 0.46 −0.54 0.94 0.70 0.44 −0.42 Note: MHF, NHF, MLT, MFWF, MLS, and W.TKE represent mixed layer heat flux, net surface heat flux, mixed layer temperature, mixed layer fresh-water flux, mixed layer salinity, and wind turbulent kinetic energy, respectively. More than 95% significant correlations are shown to be “bold italic” faces.
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