1. Indian Ocean circulation and climate variability
Jay McCreary, Fritz Schott & Shang-Ping Xie
Summer School on:
Dynamics of the North Indian Ocean
National Institute of Oceanography
Dona Paula, Goa
June 17 – July 29, 2010
About 10 years ago, the IO was viewed as a slave to ENSO, with no known impacts of IO SST anomalies on climate.
The ENSO/IOD event was the trigger that broke this view, providing the most obvious example of air-sea coupling in the IO.
It is remarkable how rapidly our understanding of IO impacts on climate has advanced since that time.
In addition to the upwelling region off Sumatra/Java, a region of importance to the IOD, another key region of air-sea coupling is now known to be the 5–10ºS thermocline ridge in the western ocean. Its importance was completely unknown 10 years ago.
The field is now changing so rapidly that whatever I say today is likely already out-of-date! 1

2. References
(SXM09) Schott, F.A., S.-P. Xie, and J.P. McCreary, 2009: Indian Ocean circulation and climate variability. Rev. Geophys., 47, RG1002, doi: /2007RG
My talk today is taken mostly from our recent review paper, and includes some new ideas about the impact of IO SST anomalies on the SWM and western Pacific.
This field, though, is large and rapidly expanding. This paper will be out-dated soon.

3. Outline Climatological background state Impact of ENSO in IO
Influence of thermocline depth
Impact of ENSO in IO
IO warming after ENSO
Indian Ocean dipole
An IO “La Nina”
Longer-term variability & trends
IO warming & IOD decadal variability
The sections of my talk cover four of the sections of Schott et al. (2009; Rev. Geophys.).
Hopefully, I will have time to complete all the sections, but I may have to skip the last one. 3

4. Influence of thermocline depth
Climatological
background state
Influence of thermocline depth
The climatological state of the ocean sets up the processes of air-sea coupling that can occur. Key regions are where the thermocline is shallow, since that is where cold water can be easily upwelled to the surface to affect the atmosphere.
The background state of the IO is very different than it is in the Atlantic and Pacific, a consequence of the lack of steady trades (equatorial easterlies). 4

5. Seasonally reversing monsoon winds Quasi-steady Southeast Trades
Wind forcing
Seasonally reversing monsoon winds
Quasi-steady Southeast Trades
The IO winds (NCEP, 1990–1998) are remarkably different from those in the Atlantic and Pacific Oceans, causing significantly different ocean circulations.
Note that the zonal winds are weak on the equator, so that the wind field tends to be antisymmetric about the equator forming “horseshoe patterns.”
Key aspects are the reversing monsoon winds in the NIO, and the quasi-steady trades in the SIO.
There are areas of Ekman divergence where h is shallow, namely, along the Somali Coast and near the tip of India during the SWM (July), and along the northern edge of the Southeast trades throughout the year.

6. Thermocline structure
Key regions of air-sea interaction are where the thermocline is shallow, where wind-stress variability can produce large SST anomalies. In the IO, these regions include: i) off Somalia, ii) around the tip of India, and iii) in the 5–10ºS band. Indeed, the latter region appears to very important for IO air-sea interaction.
An additional region, not evident in this climatological plot, is the upwelling region off Sumatra/Java. Air-sea interaction in this region is a key process in IO Dipole (IOD) events (also known as IOZM, IODZM, and IOZDM).
Figure 1: Monsoon wind stress fields from the 1990–1998 National Centers for Environmental Prediction (NCEP) [Kalnay et al., 1996] climatology (vectors) and depths of 20C isotherm (Z20) from Simple Ocean Data Assimilation (SODA) (mean for 1992–2001, color shaded) for (a) January, (b) June, (c) August, and (d) November.
Key regions for air-sea interaction are where the thermocline is shallow. In these regions, wind-stress variability can produce large SST anomalies.
There are several such regions in the IO: i) off Somalia, ii) around the tip of India, and particularly iii) in the 5–10ºS band. Indeed, the latter region appears to very important for IO air-sea interaction.
Note the aspects of the wind that thin the thermocline: alongshore winds off Somalia and Oman, wind-stress curl around the tip of India, and wind stress curl along the northern flank of the Southeast Trades.
An area not as apparent in the climatological annual cycle is the shallowing of the thermocline off Sumatra/Java, which occurs during IOD events. As noted below, however, the thermocline off Sumatra/Java is shallowest during the fall (due to equatorial winds?)
The 20ºC isotherm also rises to the surface near 25ºS, but not due to the winds.

7. SST and precipitation
There is a close connection between SST and precipitation in the 5–10ºS band. During DJF, precipitation extends into the western IO where SST is warm. During JJA, it is confined to the eastern/central ocean because SST is cool in the west.
SST in the 5–10ºS band is related to the thermocline depth there, the shallower and longer region during JJA cooling SST. Precipitation appears to be prevented in the west by the cool SSTs.
Figure 2: (a) December, January, and February (DJF) and (b) June, July, and August (JJA) climatology of sea surface temperature (SST) (intervals at 1C; 28C or higher in red) and precipitation (color shade in mm/month) based on advanced very high resolution radiometer [Armstrong and Vazquez-Cuervo, 2001] and Tropical Rain Measuring Mission [Huffman et al., 2007] satellite observations, respectively. Monsoon wind stress fields from the 1990–1998 National Centers for Environmental Prediction (NCEP) [Kalnay et al., 1996] climatology (vectors) and depths of 20C isotherm (Z20) from Simple Ocean Data Assimilation (SODA) (mean for 1992–2001, color shaded) for (a) January and (b) June.
Note how the precipitation extends over the 5–10ºS band. Moreover, precipitation seems to be cut off in JJA in the western IO due to the cooler SST there.

8. Impacts of ENSO in the IO
IO warming after ENSO
There is a remarkable warming of the IO after an ENSO event. This warming impacts the atmosphere both in the IO and Pacific. 8

9. ENSO
1) ENSO drives a delayed warming in the IO, part (all?) of which is attributable to the 5–10ºS Rossby wave.
2) The EEIO curve is very different from the others because of the cooling off Sumatra, due to the IOD response associated with ENSO.
3) There are ongoing studies at the IPRC and elsewhere, which demonstrate the impact of this delayed warming back on the atmosphere.
Figure 12: Correlations between Nino3 SST for Nov(0)-Jan(1) with SST in the eastern equatorial Pacific (160W–120W, 5S–5N; black), the tropical IO (40–100E, 20S–20N; red), the Southwest IO (50–70E, 15–5S; green), and the eastern equatorial IO (90–110E, 10S–Eq.; blue).
What processes cause the warming? What causes the delay? What are the impacts of these SST anomalies on the atmosphere?

10. ENSO January June November August
The thermocline ridge is shallow throughout the year. One can expect that ENSO-related IO winds generate large SST anomalies there. 10

11. ENSO
r(Z20,SST)
There is a close connection between thermocline depth and SST in the western, tropical IO at interannual time scales.
As might be expected, interannual SST variability is large in regions where Z20 is shallow or undergoes a large annual variation.
Figure 14: a) Annual-mean depth of the 20ºC isotherm (contours in m) and correlation of its interannual anomalies with local SST (color shades) (from Xie et al., 2002).

12. ENSO
r(Z20,SST)
Precipitation 15
Xie et al. (2002)
The thermocline ridge provides a “window” for coupling ocean dynamics (thermocline depth) to SST and, hence, to atmospheric convection.

13. ENSO
Xie et al. (2002)
Figure 17: Correlation with eastern Pacific SST during Oct-Dec (months 10–12) as a function of x and t: Z20, SST, and rainfall averaged from 8–12ºS. Shading denotes where correlation exceeds 0.6 with Z20 in (a) and (b), and with SST in (c).
The SWIO delay results from Rossby-wave propagation. A downwelling Rossby wave is generated by anomalous winds in the southeastern IO, which propagates into the western ocean and deepens the pycnocline in the 5–10ºS ridge.
As a result, SST warms there, and this warming increases rainfall.
Subsequent research has pointed out the significant impact of this anomalous convection on developing El Nino and elsewhere.
The SWIO delay results from a downwelling Rossby wave generated in the southeastern IO, which deepens the pycnocline in the 5–10ºS ridge after its arrival there. As a result, SST warms there, and this warming increases rainfall.

14. ENSO
IOD
ENSO
Figure 15: Partial correlation of 1000 hPa winds (vectors) and wind curl (colors) with a) an IOD index and b) NINO3; only correlations at 99% level are shown (from Yu et al., 2005).
ENSO is associated with positive wind curl. It forces a downwelling Rossby wave that propagates into the SWIO to impact the 5–10ºS ridge several months later.
ENSO is associated with strong wind curl from 8–12ºS.
This wind curl drives a downwelling Rossby wave that propagates into the western IO to impact the 5–10ºS ridge.
At the end of this slide, show Irina Sakova’s Indo-Pacfic movie band-passed for 4–8 years.

15. ENSO
Nino
SWIO
NIO
The SWIO convection induces a local cyclonic circulation. It also forces a cross-equatorial response with northeasterlies throughout the NIO. They weaken the SWM, causing NIO warming for the second time.
Regressions of Nino SST during NDJ(0) on SST, wind and solar radiation (–precipitation) during May-Jun(1). R
There are also precipitation anomalies in the tropical WNP. As discussed next, they appear to be remotely generated by the IO warming via the radiation of an atmospheric warm Kelvin wave.
SR stands for solar radiation. Over the TIO, convective clouds dominate so a reduction in SR corresponds to an increase in rainfall/convection. Note that not only is precipitation stronger along the thermocline ridge, but it is weaker in the western Pacific north of the equator.
The SWIO warming induces not only a local cyclonic circulation (slightly to the south) but also an across-equatorial response associated with anomalous northeasterlies throughout the region. These anomalous northeasterlies weaken the winds of the SWM, thereby causing the NIO to warm for the second time.
Du et al. (2009, J Climate)

16. ENSO
Xie et al. (2009, J. Climate)
mb temp,
surface winds
precip
A warm atmospheric Kelvin wave radiates from the TIO, and because of damping generates northeasterlies and a divergence on its northern flank. With the additional “push” of convective feedback, this divergence suppresses convection over the tropical NW Pacific.
A warm atmospheric Kelvin wave radiates from the TIO, and because of damping generates northeasterlies and surface divergence on its northern flank, which suppresses convection over the tropical NWP.

17. ENSO
p, (u, v)
A warm atmospheric Kelvin wave radiates from the TIO, and because of damping generates northeasterlies and a divergence on its northern flank. With the additional “push” of convective feedback, this divergence suppresses convection over the tropical NW Pacific.
The response is represented simply by the Gill atmospheric model, which models the response of a baroclinic mode of the atmosphere to a prescribed heating. The solution has a local response and radiates damped Kelvin and Rossby waves, which are damped by Newtonian cooling (–κp).

18. ENSO
The figure shows the response when an additional diabatic heating is imposed in the tropical WNP that is proportional to the average wind convergence in the blue area. In this case, a pronounced anticyclonic circulation develops, consistent with the observations.
SLP & sfc wind
The atmospheric model is dry, linearized about the NCEP mean state for JJA, with 20 vertical levels. It is forced by a prescribed diabatic heating that extends throughout the troposphere, to model deep convection.
SLP & sfc wind
The model is dry and has about 20 vertical levels. It is forced by diabatic heating with a prescribed vertical structure that extends throughout the troposphere, in order to model deep convection. There is also an interactive heating in the tropical WNP that depends on convergence driven by the TIO heating.
The model is linearized about the NCEP mean state for JJA. As a result, the response is asymmetric in the Indo-west Pacific but becomes increasingly symmetrical farther to the west (near the dateline).
The upper panel shows the response to a symmetric, basin-scale heating over the TIO. (The spatial structure for this "interactive" heating is given a priori, as depicted in the white contours.) The lower panel is the same, except that in the tropical WNP the magnitude and sign of diabatic heating are interactive with surface the wind convergence averaged in the blue area.
The two panels show that: a) TIO heating can lead to a convective response with a pronounced anticyclonic circulation b) if convective feedback is invoked in the tropical WNP.
Xie, S.-P., K. Hu, J. Hafner, H. Tokinaga, Y. Du, G. Huang, and T. Sampe, 2009: Indian Ocean capacitor effect on Indo-western Pacific climate during the summer following El Nino. J. Climate, 22, 730–747.
The figure shows the response to a symmetric, basin-scale heating over the TIO. As in the Gill model, a Kelvin wave radiates into the tropical WP. Northeasterlies develop on its northern flank, due to the background winds and to damping.
Xie et al. (2009, J. Climate)

19. ENSO
Summary
May
Second warming
JJA(1)
Feb
Kelvin wave
Rossby wave
ENSO wind curl
Ocean-atmosphere interaction in the SWIO is anchored by warming due to an oceanic Rossby wave. It is key to the persistence of the warming throughout the IO during JJA(1). The IO warming excites an atmospheric Kelvin wave, which causes low-level divergence in the tropical NWP, reducing rainfall and generating an anticyclone there.

20. Indian Ocean Dipole
An IO “La Nina” 20

21. IOD
Figure 18: IOD pattern during Sept-Nov. a) Regression of Z20 (shading in m) and surface wind velocity (m/s) on the first principal component of Z b) Correlation of precip (shading) and SST (contours at 0.3, 0.6 and 0.9 and negative dashed) with the first principal component of Z20. From Saji et al. (2006a).
The typical IOD develops from Sept–Nov, with dipole anomalies in SST, Z20, and precipitation and anomalous equatorial easterlies. These changes are all consistent with the occurrence of Bjerknes feedback.
An EOF is a spatial eigenfunction of a data set (like Z20). It is the eigenfunction of the “covariance matrix,” obtained by finding the covariance of each data point in the array with every other one. Then, the principal components for each EOF are the expansion coefficients (time series) obtained by expanding the data set into EOFs.
The typical IOD manifests itself through a zonal gradient of tropical SST, with cooling off Sumatra and warming in the western ocean (Figure 18) [Saji et al., 1999; Saji and Yamagata, 2003]. As the IOD develops (September–November), an east-west dipole of anomalous rainfall is established over the tropical IO, with precipitation increasing in the west because of the low-level convergence associated with the anomalous equatorial easterlies and vice versa in the east [Saji et al., 1999; Webster et al., 1999]. The rainfall dipole is an important element of the air-sea interaction (Bjerknes feedback) that sustains the IOD. Easterly wind anomalies blow from the cold/dry EEIO to the warm/rainy western IO, lifting the thermocline in the EEIO and amplifying SST cooling there (Figure 18).

22. IOD
Figure 21: b) Seasonal cycles of SST in the EEIO (heavy solid) with interannual variability (one standard deviation, shaded) and SST and wind during IOD years (light solid). c) Same as b), except for zonal wind on equator at 85ºE. (From Saji and Yamagata, 2003).
The panels plot SST (left) and zonal winds (right), showing the seasonal cycle (solid), the standard deviation of all interannual variability (shading), and SST during IOD years (thin dotted curve).
The anomalies associated with IOD events always occur in the fall and early winter.
Further, the IOD anomalies (thin/circled curve) are larger than anomalies of all interannual variability, that is, including both ENSO and IOD events (thick curve), lying outside the standard deviation (gray shading). This supports the idea that IOD is a climate event separate from ENSO.
Why does the IOD develop in the fall (Sept–Nov)? One reason is because the normal annual cycle of SST in the EEIO is coolest (and Z20 is shallowest) at that time. Thus, the monsoon forcing creates a “window” in which IOD events can develop.
The IOD-year curves lie outside the standard deviation of all interannual variability, supporting the idea that IOD is a climate event separate from ENSO.

23. Courtesy of Jerome Vialard
IOD
Sea-level is low (thermocline is shallow) from September–October, providing a window for the development of IOD events.
Courtesy of Jerome Vialard

24. IOD
Figure 20: a) SSTW and SSTE anomalies from 1981−99. b) SSTW–SSTE and Δτxeq. c) Δτxeq and inverted SOI. Light blue shading indicates El Nino events in the Pacific (from Feng and Meyers, 2003).
The correlation between the SSTE and SSTW is only 0.43 and is positive. It is negative only during IOD events.
Questions that have been asked: A) Is the IOD really a dipole? B) Is the IOD different from ENSO?
The correlation between the eastern and western poles of the IOD index is So, the two poles ARE related, but not highly.
In contrast, the correlation between the IOD index (SST difference) and equatorial zonal winds is VERY HIGH (0.86).
The correlation between SOI (which includes the IOD index) and equatorial zonal winds is not as high.
The conclusion from b) and c) is that the IO SST difference drives the IO equatorial winds, NOT SOI.
Show Irina Sakov’s movie band-passed filtered about a period of 3 years.
The τxeq anomaly is more closely related to ΔSST (0.86) than to SOI (0.67), supporting the independence of IOD from ENSO.

25. IOD
Figure 23: Variations of the intensity of submonthly (6–30 day) OLR variability for the area 2.5–12.5S, 87.5–102.5E (solid line) and an IOD index (dashed line) during SON.
Shinoda and Han ( 2005)
The region ( S, E) is the correlation maximum area between 6-30d OLR and DMI, shown as a box in their Fig. 3 (a correlation map between 6-30d OLR and DMI).
Submonthly OLR and the IOD are closely related, with the former being strongly reduced during IOD years (corr. coeff. 0.84). The likely cause of the linkage is that atmospheric convection is suppressed (enhanced) in the EEIO during a positive (negative) IOD phase, when SST is anomalously (cool) warm.

26. Summary Climatological background state El Nino Indian Ocean Dipole
Climatological thermocline depth, h, is shallow in the western Arabian Sea, southern tip of India, 5–10ºS thermocline ridge, and off Sumatra/Java.
These regions are climatically important because that is where ocean dynamics can impact SST.
El Nino
ENSO generates negative Ekman pumping in the southeastern tropical IO. It forces a Rossby wave that deepens h, warms SST, and strengthens convection in 5–10ºS thermocline ridge during the following spring,
This anomalous convection weakens the onset of the SWM in the following summer, and warms the northern IO. The second warming forces an atmospheric Kelvin wave that reduces convection in the western Pacific.
Indian Ocean Dipole
IOD events develop during the fall, when h off Sumatra/Java is at its climatological minimum. Bjerknes feedback appears to be active during large IOD events, so that IOD is dynamically similar to a Pacific “La Nina.”
During IOD events, submonthly atmospheric variability decreases significantly.

27. Longer-term variability and trends
IO warming and IOD decadal variability 27

28. Indian Ocean warming trend
Alory et al. (2007)
From 40–50º, there was a strong, near-surface, warming trend in the western subtropical IO, an increase of 1–2ºC over 40 years extending to 800 m (panel c). In addition, from 35ºS to 5ºN there were regions of cooling below 100 m. A similar subsurface cooling pattern occurs in an average of several IPCC models (panel e). The cooling regions must involve shifts the ocean’s response to changing dynamical forcing (e.g., winds and across-boundary transports) (panel d).
The warming is not spatially uniform.
In panel c), there is a particularly strong warming trend in the western, subtropical, IO from 40–50ºS, corresponding to an increase of 1–2ºC over 40 years and extending to 800 m; in contrast, the warming from 15ºS–5ºN tends to be trapped above the 20◦C isotherm with a subsurface, cooling trend from 100–200 m.
3) The surface warming is weaker when the mean IOTA temperature field is simply shifted southward by 0.5º but the subsurface warming is quite similar to the observations, suggesting that much of the deeper warming could be dynamically driven by wind-driven shifts in gyre structure.
Figure 24: c) Zonally averaged temperature trends 1960–99 (shading) from new IO temperature archive (IOTA). d) as b) but calculated after shifting mean temperature structure southward by 0.5º. e) trends from mean of 10 IPCC models. 28

29. Indian Ocean warming trend
The warming is not spatially uniform.
In panel c), there is a particularly strong warming trend in the western, subtropical, IO from 40–50ºS, corresponding to an increase of 1–2ºC over 40 years and extending to 800 m; in contrast, the warming from 15ºS–5ºN tends to be trapped above the 20◦C isotherm with a subsurface, cooling trend from 100–200 m.
3) The warming is much weaker when the mean IOTA temperature field is simply shifted southward by 0.5ºC, suggesting that much of the warming could be dynamically driven by wind-driven shifts in gyre structure.
The NIO heat storage has remained roughly constant in the upper 700 m over the past 50 years but has increased in the SIO. Barnett et al. (2005) suggested that stronger concentrations of aerosols over the northern IO weakened the climate-change signal there.
Figure 24: Time series of yearly heat content in the upper 700 m for a) the SIO and b) the NIO, with vertical bars for 1 std. dev. of the annual means, red line the respective trends and numbers explained variance by trend line (from Levitus et al., 2005). 29

30. IOD decadal variability
Figure 27: Thermocline-depth anomalies h in the EEIO (10ºS–0; 90–110ºE) in a) ocean GCM driven by NCEP winds. b) in the SODA reanalysis; vertical lines mark IOZM occurrences.
The occurrence of strong IOD events tends to vary decadally. This property holds true in the paleo-record: A fossil coral shows the occurrence of upwelling events off Sumatra that collect into decadal cycles.
This study suggests that the reason is that h in the EEIO varies decadally, and that IOD events are favored when h is shallowest.
Annamalai et al. (2005b)
IOD events tend to cluster in decades when the EEIO is preconditioned with a shallow thermocline, thereby favoring Bjerknes feedback in the IO. The preconditioning was driven by Pacific decadal variability, both by an atmospheric bridge and by changes in the ITF. 30

31. Summary IO warming IO decadal variability
The 50-year warming trend in the IO is due to surface heating. Regions of subsurface cooling must result from ocean dynamics (e.g., changes in wind or across-boundary transports).
The north IO has not shown significant warming for reasons that are not yet clearly understood.
IO decadal variability
IOD events tend to occur in decades when the EEIO thermocline is anomalously shallow, thereby favoring Bjerknes feedback.