Contribution of the winter salinity barrier layer to summer ocean-atmosphere variability in the Bay of Bengal
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Abstract: It is found that the winter (December–February) barrier layer (BL) in the Bay of Bengal (BoB) acts as a dynamical thermostat, modulating the subsequent summer BoB sea surface temperature (SST) variability and potentially affecting the Indian summer monsoon (ISM) onset and associated rainfall variability. In the years when the prior winter BL is anomalously thick, anomalous sea surface cooling caused by intensified latent heat flux loss appears in the BoB starting in October and persists into the following year by positive cloud-SST feedback. During January–March, the vertical entrainment of warmer subsurface water induced by the anomalously thick BL acts to damp excessive cooling of the sea surface caused by atmospheric forcing and favors the development of deep atmospheric convection over the BoB. During March–May, the thinner mixed layer linked to the anomalously thick BL allows more shortwave radiation to penetrate below the mixed layer. This tends to maintain existing cold SST anomalies, advancing the onset of ISM and enhancing June ISM precipitation through an increase in the land-sea tropospheric thermal contrast. We also find that most of the coupled model intercomparison project phase 5 (CMIP5) models fail to reproduce the observed relationship between June ISM rainfall and the prior winter BL thickness. This may be attributable to their difficulties in realistically simulating the winter BL in the BoB and ISM precipitation. The present results indicate that it is important to realistically capture the winter BL of the BoB in climate models for improving the simulation and prediction of ISM.
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Key words:
- Bay of Bengal /
- barrier layer /
- Indian summer monsoon /
- rainfall /
- CMIP5
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Figure 1. Seasonal evolution of sea surface temperature (SST, ℃; red line) and temperature averaged within the barrier layer (BL, ℃) (blue line) for the period of 1951–2010, averaged over the Bay of Bengal (5°–25°N, 75°–95°E).
Figure 2. Different regions of India. The map is modified after reference (Kothawale and Rajeevan, 1995).
Figure 3. Pearson’s correlation coefficients between DJF BLT averaged over BoB and subsequent rainfall in total India (white dots), central northeast India (CNE, red dots), northeast India (NE, purple dots), northwest India (NW, yellow dots), peninsular India (cyan dots), and west central India (WC, black dots) (a) and Pearson’s correlation coefficients between DJF BLT and each month’s AO index (black dots), IOD index (white dots), and Niño 3.4 index (cyan dots) in the year (0) and year (+1) (b). The current period is from 1952 to 2010, and the earlier period is from 1951 to 2009. The black lines (chain dotted) denote 95% confidence level.
Figure 5. BLT normalized by its mean and standard deviation (a), and BLT (b), ILD (c), and MLD (d) averaged over the BoB (5°–25°N, 75°–95°E) in December–February from 1951 to 2010. When the BLT averaged over December–February is higher (lower) than one standard deviation, it is defined as a thick (thin) BL year. The grey chain dotted lines denote one standard deviation. The red (cyan) dots denote the thick (thin) BL years.
Figure 6. Seasonal evolution of meridional gradient of the daily tropospheric air temperature (℃) in 200–500 hPa over the region of (10°–20°N, 90°–110°E) (a), and meridional difference of the daily tropospheric air temperature (℃) in 200–500 hPa between a northern box (5°–35°N, 30°–110°E) and a southern box (15°S–5°N, 30°–110°E) (b) from April to July, for climatology (black dashed lines), year (+1) of prior winter thick BL years (red lines) and thin BL years (blue lines) (b).
Figure 8. Seasonal evolution of SST (℃) averaged over BoB (a) and land-sea thermal contrast in the tropospheric (200–500 hPa average) temperature (b) from January to December, for climatology (black solid lines), year (+1) of prior winter thick BL years (red lines) and thin BL years (blue lines); and composite of moisture flux [kg/(m·s)] anomalies averaged over April (+1)–June (+1) for prior winter thick BL years (c) and thin BL years (d); and scatterplots between June (+1) moisture flux convergence [×105 kg/(m2·s)] averaged over India (10°–30°N, 70°–90°E) and DJF BLT (m) averaged over the BoB (e) and June (+1) precipitation (mm) averaged over India (f). In a and b, the land-sea thermal contrast in the troposphere (200–500 hPa) is estimated as the difference in the values between the boxes over the South Tibetan Plateau (25°–40°N, 65°–95°E) and the BoB (5°–25°N, 75°–95°E). The definition of land-sea thermal contrast follows Li and Xiao (2021). The black chain dotted line denotes the temperature of 28℃. The triangles denote statistical significance at the 90% confidence level by two-tailed Student’s t test. In b and c, the red arrows denote statistical significance at the 90% confidence level by two–tailed Student’s t test. In e and f, the gray lines indicate the least-squared fits and the correlation coefficients (r) are statistically significant at the 95% confidence level.
Figure 10. Anomalous evolution of net heat flux (a), net shortwave radiation flux (b), penetrative shortwave radiation flux (c), longwave radiation flux (d), sensible heat flux (e), latent heat flux (f), SST (g), mixed layer depth (MLD, h), total cloud cover (TCDC, i), and wind speed (j), averaged over the BoB from September (0) to September (+1), for prior winter thick BL years (blue bars) and thin BL years (red bars). Note that Y-axis ranges in a–f are inconsistent. The red asterisks (*) denote statistical significance at the 90% confidence level by two-tailed Student’s t test.
Figure 11. Seasonal evolution of anomalous SST tendency induced by surface heat flux and ML. Anomalous evolution of net surface heat flux term (a, f), net shortwave radiation flux term (b, g), longwave radiation flux term (c, h), sensible heat flux term (d, i), and latent heat flux term (e, j) in Eq. (5) averaged over the BoB from September (0) to September (+1), for prior winter thick BL years (the first column) and thin BL years (the second column). The blue bars denote the anomalous surface heat flux component
$\delta \dfrac{{{Q_{\mathrm{net}}}}}{{\rho {C_{\mathrm{p}}}}} \times \left(\overline {\dfrac{1}{h}}\right)$ , and the red bars denote the anomalous MLD component$ \dfrac{{ {{\overline Q_{\mathrm{net}}}} }}{{\rho {C_{\mathrm{p}}}}} \times \delta \dfrac{1}{h} $ . The red lines denote the sum of the anomalous surface heat flux component and anomalous MLD component. The blue lines denote the anomalies simultaneously considering surface heat flux and MLD.
Figure 12. Anomalous evolution of temperature averaged over BoB from January (0) to December (+1), for prior winter thick BL years (a) and thin BL years (b). The black lines denote the zero contour. The black spots denote statistical significance at the 90% confidence level by two-tailed Student’s t test.
Figure 13. Anomalous evolution of penetrative shortwave radiation (a), vertical entrainment (b),
${T_{ - h}} - \overline {T\;} $ (℃; the temperature at the base of mixed layer minus the temperature of mixed layer average) (c), and BLT (d), averaged over the BoB from September (0) to September (+1), for prior winter thick BL years (blue bars) and thin BL years (red bars). The red asterisks (*) denote statistical significance at the 90% confidence level by two-tailed Student’s t test.
Figure 14. Scatterplots between DJF BLT and MAM (+1) MLD (a), and between MAM (+1) precipitation rate and MAM (+1) MLD (b) and DJF BLT (c), averaged over BoB. The gray lines indicate the least-squared fits.
Figure 15. Initial fields in the experiments are the composited temperature (a) and salinity (b) profiles averaged over BoB (5°–25°N, 75°–95°E) from December (0) to February (+1), for the selected prior winter thick (thin) BL years, and the evolution of averaged temperature of the ML (c) and MLD (d) simulated by the Price-Weller-Pinkel mixed layer model. For a and b, the model is driven by the composited atmospheric forcings averaged over the BoB, for prior winter thick (thin) BL years. The solid (dot) black and solid (dot) red lines represent the BL and removed BL (Rm-BL) conditions.
Figure 16. Schematic of the mechanisms of the prior winter’s anomalously thick BL modulating the June rainfall over India. The meridional section is the average temperature anomalies from 75°E to 95°E over the BoB. The zonal section is the average temperature anomalies from 5°N to 25°N over the BoB. The horizontal section is the sea surface temperature anomalies in the BoB. The solid (dashed) black lines indicate MLD (ILD). The little pink (light blue) arrows indicate an increase (decrease) of the atmospheric and oceanic factors. In December–February, the vertical entrainment of the subsurface warm water associated with prior winter thick BL anomalies damps the sea surface cooling to maintain the deep atmospheric convection. In March–May, sufficient near-surface humidity increases rainfall, enhancing salinity stratification and reducing MLD. More shortwave radiation penetrates the ML, maintaining surface cooling and increasing the land-sea thermal gradient. In June, more moisture is transported into the South Asian subcontinent, which therefore results in the increase of rainfall over India.
Table 1. Impact of different factors on June rainfall over India
No. Region Variable Correlation coefficient Partial correlation coefficient Removing IOD (SON) Removing ENSO (DJF) Removing BLT (DJF) 1 Total India IOD –0.12 – –0.01 0.05 ENSO –0.21 –0.17 – 0.06 BLT 0.46* 0.45* 0.42* – 2 Central northeast India IOD –0.02 – 0.19 0.14 ENSO –0.32* –0.37* – –0.14 BLT 0.40* 0.42* 0.28* – 3 Northeast India IOD 0.05 – 0.12 0.12 ENSO –0.09 –0.14 – 0.10 BLT 0.16 0.19 0.14 – 4 Northwest India IOD –0.10 – –0.11 –0.03 ENSO –0.01 0.05 – 0.12 BLT 0.20 0.18 0.23* – 5 Peninsular India IOD –0.18 – –0.26 –0.19 ENSO 0.07 0.21 – 0.08 BLT –0.01 –0.08 0.04 – 6 West-central India IOD –0.12 – –0.04 0.05 ENSO –0.17 –0.12 – 0.13 BLT 0.48* 0.47* 0.47* – Note: This table shows Pearson’s correlation coefficients and partial correlation coefficients between SON (0) IOD, DJF ENSO indices, and DJF BLT with respect to June (+1) ISM rainfall over different regions of India. The asterisks (*) indicate statistical significance at the 95% level using Student’s t test. The dash (−) indicates no available data. 
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