3.1 Bjerknes Feedback
Bjerknes feedback where surface wind forcing leads to east-west SST gradient in the equatorial Pacific basin, which in turn feeds back to strengthen the original surface winds is at the heart of the ENSO (Bjerknes 1969) phenomenon. The Bjerknes feedback has been shown to be also operative in the IO, leading to the Indian Ocean Dipole mode (Saji et al. 1999; Webster et al. 1999; Murtugudde et al. 2000) on an interannual time scale. Here, we explore if a similar feedback contributes to the multi-decadal variability of the ISMR.
The modification of the SST, sea-level and HC distribution by surface winds through equatorial dynamics of Wyrtki jets (Wyrtki 1973) is an important component of ocean-atmosphere interaction in this region. For the period 1901-1957 (referred to as P1), the first empirical mode of zonally averaged surface winds explains 38.9% variance while the same for the period 1958-2007 (referred to as P2) explains 49.3% variance. The leading EOF (henceforth, referred to as EOF1) of surface winds zonally averaged over 70°E to 90°E during the two periods P1and P2 (Fig. 2a and Fig. 2b) show some interesting differences in large scale circulation during the two periods. While the deep equatorial belt was dominated by higher frequency of occurrence of easterly forcing during the early period (1901-1957), the later period is dominated by higher frequency of occurrence of westerly wind forcing (Fig. S1b,c). The corresponding PCs (Fig. 2c,d), while having large interannual variation, do not indicate any significant trend. The propensity of zonal mean easterly wind forcing at the equator during the period P1, and westerly forcing in the period P2 contribute to the easterly trends of surface winds at the equator in the period P1 between 70⁰E and 100⁰E (Fig. 3a) as against westerly trends of surface winds at the equator during the period P2 (Fig. 3b) between 60oE and 90oE. The trends in the zonal winds are also consistent with trends of SST during both periods (Fig. 3a,b). Much stronger and wide-spread increasing trends of SST during P2 compared to that during P1 are consistent with a weaker increasing trend of area averaged SST in Fig. 1b compared to a relatively stronger increasing trend of area averaged SST during the period (P2) . Also, maximum SST trend during P2 is over the west-central equatorial IO, as noted in earlier studies (Swapna et al. 2014; Koll et al. 2014).
A regression of PC1 of zonally averaged zonal winds on seasonal mean rainfall anomaly over India during the periods P1 and P2 (Fig. 4a,b) show that the zonal wind variations during P1 are associated with the increasing tendency of rainfall over the core monsoon region and west of the Western Ghat consistent with Fig. 1a, while that during period P2 are associated with a decreasing tendency of rainfall over core monsoon and west of Western Ghat, consistent with Fig. 1a. The SST anomaly patterns associated with the zonal wind variations (regression with PC1) during the period P1 (P2) (Fig. 4c,d) are closely similar to a positive (negative) IOD pattern (Saji et al., 1999). They are consistent with easterly (westerly) driving as evident from Fig. S1a (Fig. S1a). During an easterly driving regime, shoaling of thermocline to the east gives rise to cold anomaly while depression of thermocline to the west gives rise to warm anomaly. The situation reverses during the westerly driving regime. During P1 the SST dipole has a cold anomaly over a smaller region in the east and a much larger region of warm anomaly to the west. In contrast, during the period P2, the SST dipole has a warm anomaly over a smaller region in the east, with a much larger region of cold anomaly to the west (Fig. 4c,d). The overall easterly (westerly) driving during P1 (P2) is due to the fact that the equatorial zonal winds averaged over (70⁰E to 90⁰E, 5⁰S to 5⁰N) have higher propensity of easterly zonal wind during P1, while the propensity of westerly zonal wind is higher during P2 ( Fig. S1d,e). The easterly (westerly) winds at the equator during P1 (P2) is a result of the stronger (weaker) than normal ISMR while the warmer (colder) SST to the western part of IO as a result of equatorial dynamics leads to higher (lower) moisture flux to the continent and tends to strengthen (weaken) the monsoon further. This is how the Bjerknes feedback at the equator and ISMR, an off-equatorial heat source are linked. The decadal variability of the IOD has also been documented (e.g., Ashok et al. 2001, 2004).
We find westward surface currents around the equatorial belt, forced by predominantly easterly surface winds during the period P1 (Fig. 5a). Associated equatorial upwelling and coastal upwelling depletes the HC in the eastern IO flanked by a horseshoe pattern build-up of HC in the western IO (Fig. 5a). The off-equatorial heat depletion in the eastern IO seems to be due to episodes of equatorial upwelling Kelvin waves that were driven by the easterly winds, and subsequently travelled as a coastal Kelvin wave towards north after hitting the eastern boundary and radiated westwards as Rossby waves. The signature of a coastal Kelvin wave in the Bay of Bengal is rather apparent (Fig. 5a). Similarly, the buildup of HC in the eastern IO during the period P2 seems to be due to episodes of down welling equatorial Kelvin waves driven by the westerly zonal winds, which subsequently have travelled north and south as coastal Kelvin waves and radiated as down welling as Rossby waves (Fig. 5b). Even in this case, coastal Kelvin waves in the Bay of Bengal could be seen clearly. The surface currents during the period P2 are also consistent with surface wind forcing. However, the westward surface currents in this case are limited to the central and eastern equatorial IO east of 70OE (Fig. 5b). This explanation is supported by the sea surface height (SSH) anomaly patterns associated with zonal mean zonal winds (regression with PC1) over the two periods (Fig. 5c,d).
3.2 Large-scale vorticity of surface zonal winds and SST
While there is considerable evidence that a Bjerknes feedback operates in maintaining the MDM of ISMR, the large increasing trend of SST during the later period (P2) cannot be explained by this feedback. In fact, purely due to this feedback SST should have a decreasing trend. As ISMR is a result of low-level moisture convergence, a higher SST over the IO would be associated with higher moisture availability and should be associated with stronger ISMR. Therefore, the association of a decreasing trend of ISMR and an increasing trend of SST over the IO during this period is counterintuitive. Hence, instead of the increasing trend of SST over the IO during this period driving the decreasing trend of ISMR, it is more likely that the large-scale wind changes associated with the decreasing trend of ISMR is driving the increasing trend of SST. We propose that the change in large-scale vorticity due to the weakening of monsoon circulation during that period played a role in the warming trend. There are two other manifestations of low-level atmospheric circulation, which might have potentially contributed to SST changes over the IO during the P2. Firstly, apart from the equatorial zonal wind, the large-scale low-level monsoon winds over IO, are associated with off-equatorial vorticity, which leads to deepening or shoaling of the thermocline. This mechanism is particularly effective in influencing SST in regions where the mean thermocline is shallow, such as the eastern equatorial IO and the central Indian Ocean thermocline dome, south of the equator. The other factor that could also contribute to the SST changes is the net heat flux (Qnet) at the surface as a result of surface wind changes and changes in the cloudiness. In this section, we explore the contributions of large-scale vorticity.
The leading EOFs of vorticity of zonal mean surface zonal winds during the monsoon season for the periods P1 and P2 are shown in Fig. 6a,b while the corresponding PCs for the two periods are shown in Fig. 6c,d. From Fig. 6c and 6d, we see a decreasing trend during P1 and an increasing trend during P2, both statistically significant at 0.05 level from a Mann-Kendall test. The leading EOFs (Fig. 6a,b) indicate important changes in the large-scale monsoon winds over the IO from P1 to P2. While during P1, a cyclonic vortex centered on the equator dominated the wind pattern, during P2, a pair of cyclonic vortices on either side of the equator seems to dominate the low-level wind pattern. This is clearly evident in the vector wind pattern associated with the PC1 of vorticity arising from meridional shear of the zonal mean surface zonal winds (Fig. 7a,b). A regression of the PC1 of vorticity of zonal mean surface zonal winds on seasonal mean rainfall over India (Fig. 6e,f) indicates that the significantly increasing trend of the PC1 contributes to a strong negative trend of ISMR during the period P2. On the other hand, during the period P1, the decreasing trend of the PC1 is associated with a positive trend of rainfall anomaly pattern over most of India strengthening ISMR more in the early part of the period and less during the latter part of the period resulting in a relatively weak increasing trend of ISMR consistent with Fig. 1a.
Furthermore, a regression of JJAS SST on to the PC1 indicates a positive SST anomaly in the central IO (Fig. 7c) induced by the trend in low level meridional shear of zonal wind (-d[u]/dy) in P1. Similar regression analysis for the P2 indicates a positive SST anomaly in the equatorial eastern IO flanked by colder SST anomaly in the western equatorial IO (Fig. 7d). The larger positive SST anomaly over the central south-equatorial IO is consistent with the cyclonic low-level wind vortex sitting over the thermocline dome in that region. In period P2, large-scale vorticity forcing increases the positive SST anomaly over a much larger region (Fig. 7d) compared to that due to direct zonal wind forcing at the equator (Fig. 4d). The positive SST anomaly over the Bay of Bengal is consistent with the northern component of the twin cyclonic vortices (Fig. 7b). The fact that PC1 during the P2 has a significant increasing trend indicates that the large-scale vorticity of the monsoon flow over the region does contribute to the increasing trend of SST over IO during P2.
Like the SST over the tropical IO, the vertically integrated moisture content in the atmosphere over the Indian monsoon region (70oE-100oE, 10oN-30oN) is increasing steadily from 1901 to 2007 (Fig. S2a) while the ISMR has an increasing trend during P1 and a decreasing trend during P2. As the ISMR is driven largely by moisture convergence rather than local moisture availability, an increasing trend of vertically integrated moisture convergence during P1 and decreasing trend of the same during P2 are consistent with trends of ISMR during the two periods (Fig. S2b). What makes the moisture convergence decrease during P2 in the backdrop of the moisture content of the atmosphere that has been increasing? The answer lies in the changes of the large-scale winds. The wind changes have led to a decreasing trend of wind convergence (Fig. S2c) that forced the moisture convergence to decrease even when the moisture content was increasing.
3.3 Net heat flux (Qnet) driving of SST trend
However, the increasing trend of SST during P2 is much stronger than that during P1 (Fig. 1b) the changes in SST forced by Bjerknes feedback or by the large-scale vorticity of zonal winds appear inadequate to explain the differences in the trends. As we noted, the two different phases of the ISMR MDM P1 and P2 are associated with significant changes in the large-scale circulation, particularly surface winds. These changes in circulation are bound to be associated with changes in cloudiness distribution. As a result, it may be natural to expect that the net heat flux (Qnet) would have similar changes during the two periods. The climatological mean Qnet during JJAS over the tropical IO between 20⁰S and 20⁰N is positive (~10Wm-2, see Fig. 8) leading to seasonal warming of SST over the region during the summer season. Here we explore if the changes in Qnet over the period could also contribute to an increasing trend of the seasonal warming leading to an overall weaker increasing trend of SST during P1 and a stronger increasing trend during P2.
The net heat flux into the ocean is a sum of different heat exchange processes at ocean surface, which includes heating due to net shortwave radiation (NSWR), net outgoing longwave radiation (NLWR), sensible heat flux (SHF), and latent heat flux (LHF). Climatologically, the first one is the contributor to the heat gain of the ocean, and all the other processes lead to heat loss, except for SHF, which depends on air–sea temperature difference. From all the four variables net heat flux can be calculated using the formula:
Qnet = NSWR-NLWR-LHF-SHF (1)
Where, NSWR = DSWR − USWR and NLWR = ULWR – DLWR, together with,
Downward shortwave radiation (DSWR), Upward shortwave radiation (USWR), Upward longwave radiation (ULWR), Downward longwave radiation (DLWR) (e.g., Pokhrel et al. 2020)
A simple thermodynamic understanding about the upper ocean is that the rate of change of SST is proportional to net heat flux. Such a balance can be expressed as
hCρ (δ/δt SST) = Qnet , (2)
where, h is the depth of the mixed layer, C is the specific heat of seawater; ρ is the density of seawater and Qnet is net heat flux (e.g., Sengupta et al. 2001). Here mixed layer depth is calculated using the density criteria (Kazunori et al. 2004), i.e., starting from the upper- most available observation to the depth at which the density is equal or greater than a specific value (e.g., 0.125 g/cm3 ) than that at the surface is considered as the mixed layer depth (MLD).
To be consistent with SST and precipitation (ISMR), here we use the mean JJAS Qnet between 1901 to 2007 to estimate its contribution to the SST trends during the two periods, P1 and P2. However, we recognize that all heat flux products, whether from reanalysis or ‘observations’ have their own biases (Pokhrel et al. 2020). To have an idea of biases in Qnet climatology from NCEPv3, we compare the climatology of JJAS Qnet from NECPv3 for the two periods (Fig. 8a,b) with those from two other flux products namely from ERA-20CM (Fig. 8c,d) and TROPFlux (Fig. 8e). The TROPFlux data is available only for the period 1979-2018 and hence its climatology may be compared only with P2.
It is interesting to note that the Qnet averaged over the tropical IO region, defined as bound by 50⁰E-100⁰E, 20⁰S-20⁰N, during P1 has a statistically significant decreasing trend (p = 0.001) from about +13 Wm-2 to about +5 Wm-2 while that during P2 has a weakly significant increasing trend from about +24 Wm-2 to about +29 Wm-2 (Fig. 9a,b). The net heat flux leads to a statistically significant (p = 0.003) decreasing trend of mixed layer temperature (Fig. 9c) resulting in approximately 0.5OC decrease during P1. It is interesting to note that the Qnet during the P2 drive a statistically significant increasing trend (p = 0.02) of mixed layer depth temperature resulting in an increase of 0.75OC during P2 (Fig. 9d).