1. Impacts of Indian Ocean circulation on biological activity Jay McCreary, Raghu Murtugudde, D. Shankar, Satish Shetye, Jerome Vialard, P. N. Vinayachandran, Jerry Wiggert, and Raleigh Hood Impacts of IO mixed layer thickness on biological activity A short course on: Modeling IO processes and phenomena INCOIS Hyderabad, India November 16−27, 2015

2. References 1)McCreary, J.P., R. Murtugudde, J. Vialard, P.N. Vinayachandran, J.D. Wiggert, R.R. Hood, D. Shankar, and S.R. Shetye, 2009: Biophysical processes in the Indian Ocean, In: Indian Ocean Biogeochemical Processes and Ecological Variability, American Geophysical Union, Washington DC. 2)McCreary, J.P., K.E. Kohler, R.R. Hood, and D.B. Olson, 1996: A four- component ecosystem model of biological activity in the Arabian Sea. Prog. Oceanogr., 37, 193–240. 3)McCreary, J.P., K.E. Kohler, R.R. Hood, S. Smith, J. Kindle, A. Fischer, and R.A. Weller, 2001: Influences of diurnal and intraseasonal forcing on mixed- layer and biological variability in the central Arabian Sea. J. Geophys. Res., 106, 7139–7155. 4)Hood, R.R., K.E. Kohler, J.P. McCreary, and S.L. Smith, 2003: A four- dimensional validation of a coupled physical-biological model of the Arabian Sea. Deep-Sea Research II, 50, 2917–2945. 5)McCreary, J.P., Z. Yu, R.R. Hood, P.N. Vinaychandran, R. Furue, A. Ishida, and K.J. Richards, 2013: Dynamics of the Indian-Ocean oxygen minimum zones. Prog. Oceanogr., 112–113, 15–37.

3. Overview Arabian-Sea mixed layer Biophysical interactions upwelling, entrainment, detrainment, advection Climatological processes Arabian Sea, Bay of Bengal, South Indian Ocean (Intraseasonal processes) MJOs, South IO Rossby waves (eddies) Interannual processes ENSO & IOD events AS & BoB oxygen minimum zones

4. Overview

5. Somali and Oman Central and northern AS Sri Lanka Western Bay Java/Sumatra South Indian Ocean band Vinayachandran (2006; priv. comm.) SeaWiFS annual chlorophyll composite (1999)

6. JanuaryJuly The wind field in the Indian Ocean is very different from that in the other oceans, accounting for the unique properties of Indian Ocean circulation and its phytoplankton distributions. There are no easterly winds (trades) on the equator, so that there is no equatorial upwelling. Instead, there are reversing cross-equatorial winds. There are seasonally reversing monsoon winds in the Arabian Sea, the Bay of Bengal, and extending to 10°S, with a stronger ( weaker) clockwise circulation during the summer (winter). South of 10°S, the Southeast Trades are relatively more steady, but they are stronger in the southern winter (July). Climatological wind forcing

7. JanuaryJuly McCreary, Kundu, and Molinari (1993) During the SWM, upwelling favorable winds lift the thermocline off Somalia and Oman, on the Indian coast, and around Sri Lanka. During the NEM, the mixed-layer in the central and northern Arabian Sea thickens to ~100 m. There is a thermocline ridge in a band from 5–10°S. It is driven by Ekman pumping associated with the northward weakening of the Southeast Trades, and is stronger in northern summer when the Trades are stronger. Thermocline response

8. July There is an obvious connection between physics and biology, with regions of high phytoplankton concentrations tending to occur where the top of the thermocline rises close to the surface. This is sensible since then the subsurface nutrient supply lies within the euphotic zone. On the other hand, blooms also occur in regions where the thermocline is NOT shallow. Phytoplankton/thermocline depth linkage

9. Arabian-Sea mixed layer

10. Mixed-layer variability (Arabian Sea) Arabian Sea biology and upper-ocean physics were intensively studied from 1994 to 1996. As part of that effort, a mooring was deployed in the central Arabian Sea at 15.5°N, 61.5°E by WHOI. Among other things, it measured near-surface temperatures, heat and buoyancy fluxes, and contained optical sensors from which phytoplankton biomass could be estimated.

11. Wind stress over the Arabian Sea varies strongly during the year, reversing from the winter to the summer. In addition, there is a strong surface cooling during the winter, when cool, dry air blows over the AS from the surrounding continent. These large changes in wind strength and Q lead to a prominent annual cycle in the AS mixed-layer thickness. Mixed-layer variability (Arabian Sea)

12. WHOI mooring At the mooring site, the mixed layer exhibited a prominent annual cycle. It deepened during the monsoon periods, most strongly during the NEM. It was thin during the intermonsoon periods. It also exhibited a striking diurnal cycle, gradually thickening during the night and rapidly thinning during the day.

13. KT mixed-layer model Turner and Kraus (1967) described the tank experiment of Rouse and Dodu (1955) as follows: “They expected that such stirring would smear out the interfacial gradients, but discovered to their surprise that the interface in fact became sharper, with a transfer of material always from the nonturbulent into the turbulent fluid, where it quickly became well mixed [i.e., entrainment].” Observations and tank models show that surface turbulence leads to the formation of a mixed layer.

14. KT mixed-layer model To model these processes with equations, Kraus and Turner (1967) parameterized surface turbulence P r by Observations and tank models show that surface turbulence leads to the formation of a mixed layer. where and τ > 0 is wind speed. Forcing u* (wind “friction velocity) measures the strength of mixing by wind stirring, and m is an arbitrary factor. Forcing Q (surface heat flux) causes mixing when Q < 0. KT argued that the factor ϕ ≈ 1.

15. KT mixed-layer model KT assumed that when P r > 0, so that turbulence is produced in the mixed layer, there is entrainment into the mixed layer at the rate Note that if Q > 0, P r can become negative, which is not physically sensible. So, KT assumed that if P r in (1) ever tried to become less than zero, the system immediately adjusts h m to a value that sets P r = 0, the “Monin-Obhukov” depth.

16. Mixed-layer variability (Arabian Sea) WHOI mooring

17. Mixed-layer variability (Arabian Sea) Model The Kraus-Turner (1967) mixed-layer model is able to simulate the seasonal and diurnal variability at the mooring site reasonably well, except for the thinning of h m due to the passage of two eddies during Nov/Dec 1994 and Aug 1995.

18. Mixed-layer variability (Arabian Sea) …but not well enough! In a later study, we found that, when our mixed- layer model used the parameters that give this MLT, our biophysical model was not able to simulate biological activity very well in the Arabian Sea. So, we modified parameter ϕ in Q to allowing the strength of convective mixing (Q < 0) to be varied. Then, we adjusted m and n until the h m represented throughout the AS (at the WHOI mooring site and elsewhere) as well as possible.

19. Biophysical interactions UpwellingEntrainmentDetrainmentAdvection

20. Upwelling is a powerful process for generating biological activity because it brings high- nutrient, thermocline water into a thin, surface mixed layer, where the depth-averaged light intensity is high. During upwelling (top), h m thins to its minimum thickness H m (profiles 1–4). Then, water from the seasonal thermocline (gray shading) entrains into h m and h f thins (profiles 4–6). When h f is eliminated, upwelling from the main thermocline begins (dark shading; profile 7). h m = mixed layer h f = seas. therm. h 2 = thermocline During entrainment (bottom), h m thickens due to turbulent mixing (from either strengthened winds or surface cooling). Fluid entrains into h m until h f vanishes (profiles 1–5). Thereafter, thermocline water entrains into the mixed layer (profile 5–7). Even though entrainment can bring considerable nutrients into the euphotic zone, entrainment blooms are not as productive as upwelling blooms because h m is thick and, hence, the depth- averaged light intensity is low. Detrainment blooms tend to be highly productive because the final h m is thin and, hence, the depth-averaged light intensity is high. They are also short-lived because detrainment does not provide a source of new nutrients (Sverdrup, 1933). During detrainment (bottom, reversed panels 5–1), h m thins due to a decrease in turbulent mixing (either when the wind weakens or there is surface heating). Initially (profile 5), there is a deep mixed layer and nutrients are high, as often occurs after wintertime cooling. SeaWiFS annual chlorophyll composite (1999)

21. An entrainment event can then produce an apparent surface bloom by entraining the subsurface bloom into the mixed layer (after profile 5). Subsurface blooms occur when the thermocline (nutricline) is shallow enough to extend into the euphotic zone. In that case, phytoplankton can tap into the subsurface nutrient supply after nutrients are depleted from the mixed layer. For example, a subsurface bloom may occur at the interface between the seasonal and main thermoclines. Subsurface phytoplankton maximum

22. Ekman Pumping Advection by SMC Coastal Upwelling IRS-P4 OCM image during July, 1999 Advection

23. Climatological processes Arabian Sea

24. JAN ND Wiggert et al. (2005) SWM (Jul): Upwelling, filaments, mixing and entrainment; nutrient replete, high production, eutrophic. NEM (Jan): Wind and buoyancy-driven mixing; nutrient replete, high production, but light limited. Intermonsoon (May, Oct): Stratified conditions, low nutrients, near oligotrophic. MAY JULOCT ND Chlorophyll from SeaWiFs

25. The physical component is a 4½-layer model of the Indian Ocean. Layer 1 represents the oceanic mixed layer, and its physics are based on the Kraus-Turner (1967) parameterization. McCreary et al. (2001) Hood et al. (2003) i i ii Coupled biophysical model The biological component is an NPZD model included in each layer of the physical model, which allows for advection within layers and transport across them.

26. The biological equations specify how nitrogen moves between compartments. Each is an advective/diffusive equation with source, sink, and vertical-mixing terms. For example, the layer-1 phytoplankton equation is where the source/sink term is with and and the vertical-mixing term is

27. Climatological forcing Under climatological forcing, there are unrealistically large detrainment blooms at the end of the monsoons when the mixed layer (ML) thins rapidly. There are weak entrainment blooms at the beginning of the monsoons when the ML begins to thicken and nutrients are entrained into the mixed layer. During the monsoons, the ML is so thick that phytoplankton growth is light limited. DB EB Response in central AS (WHOI mooring site)

28. 1994 + diurnal forcing Under forcing by actual winds (1994) and with the diurnal cycle, there are a number of detrainment and entrainment blooms, and phytoplankton growth is spread more realistically throughout both monsoons. Response in central AS (WHOI mooring site)

29. Hood et al. (2003) When compared with (US JGOFS Arabian Sea Process Study) data elsewhere in the basin, the model’s response was initially not good. Many model/data discrepancies were traceable to the solution’s mixed-layer thickness being too thick (purple curve). CONCLUSION: Relatively simple biogeochemical models can capture the first- order biological variability in the Arabian Sea, but solutions are very sensitive to how well the models represent the physical state, particularly mixed-layer thickness and vertical-exchange processes. Sensitivity to mixed-layer thickness

30. Climatological processes Bay of Bengal

31. SeaWiFS images for 1997–2002 Vinayachandran et al. (2004; GRL) This monthly climatology from SeaWiFS clearly shows that there is a biological response south of India during the SWM. As shown in the next slide, different physical processes account for the bloom in different locations. Southwest Monsoon

32. Ekman Pumping Advection by SMC Coastal Upwelling IRS-P4 OCM image during July, 1999 Southwest Monsoon

33. There is also usually a bloom in the western Bay during the NEM. In the above sequence, the only exception was during 1997 when there was a bloom in the eastern Bay, likely a result of the ongoing ENSO/IOD event. Northeast Monsoon

34. The physical component is a 4½-layer model of the Indian Ocean. Layer 1 represents the oceanic mixed layer, and its physics are based on the Kraus- Turner (1967) parameterization. The biological component is an NPZD model included in each layer of the physical model, which allows for advection within layers and transport across them. McCreary et al. (2001) Hood et al. (2003) i i ii Coupled biophysical model

35. Obs The model is able to reproduce the bloom at the right time and right place. Model Evolution of the 1996 bloom

36. An important part of the bloom’s dynamics is the presence of a subsurface (layer 3) phytoplankton maximum. As a result, the initial surface bloom is caused largely by entrainment of subsurface phytoplankton into the mixed layer (layer 1). Bloom dynamics

37. Mixed Layer Nutrient Rich, No Light Prior to an increase in the wind, the mixed layer of the Bay is thin. Thus, there is sufficient light at subsurface levels (layer 3) to allow a subsurface bloom to develop, where nutrients are also available. When the winds strengthen, both nutrients and chlorophyll are entrained (or upwelled) into layer 1. Layer 3 Bloom dynamics

38. Climatological processes South Indian Ocean

39. Jan Aug There is a weak surface bloom in the South Indian Ocean everywhere from about 5–15ºS where the thermocline is shallow. Models and a few observations show that there is a much more prominent subsurface bloom in the same region. South Indian Ocean blooms The weaker surface bloom is caused partly by entrainment of the subsurface bloom into the mixed layer. Recent modeling work suggests that the surface bloom also results from new production, that is, from nutrient entrainment. The surface chlorophyll band is more intense during the southern winter (August) when the local winds, and hence entrainment, are stronger.

40. Interannual processes ENSO & IOD events

41. There is not enough data to identify general biophysical interactions with statistical reliability. On the other hand, such biophysical interactions were clearly active during the intense 1997/98 ENSO/IOD event. In this event, there was upwelling in the eastern, equatorial ocean and along Sumatra/Java forced by anomalous southeasterly winds. In response, SST cooled and there was an upwelling phytoplankton bloom. Oct/Nov, 1997 1997/98 ENSO/IOD event

42. AS and BoB OMZs

43. OMZs occur in many regions of the world ocean underneath areas of high production. The high production also generates detritus. The detritus is remineralized by bacteria as it sinks, consuming oxygen and creating a subsurface OMZ. Arabian Sea Oxygen Minimum Zone (ASOMZ)

44. A major biological puzzle is that the ASOMZ is shifted away from the location of the highest production in the western Arabian Sea. Both biological (e.g., differential sinking rates) and physical (e.g., flow of oxygenated RSW and PGW into the western Arabian Sea) might be the cause. Arabian Sea Oxygen Minimum Zone (ASOMZ) Dissolved oxygen (μM) TN039 0 km 2500 km 0 2500

45. mixed layer diurnal thermocline seasonal thermocline main thermocline, upper OMZ Schematic diagram of the 6½-layer model used to study the OMZs in the Arabian Sea and Bay of Bengal. Variable-density, 6½-layer model lower OMZ sub-OMZ layer

46. Variable-density, 6½-layer model The modeled oxygen distributions (right panels) capture major observed features, including: 1) northward spreading of higher oxygen concentrations from the southern hemisphere (all layers); 2) eastward shift of the upper ASOMZ (layer 4); 3) northward intensification of the lower ASOMZ (layer 5); and 4) a BBOMZ that is weaker than the ASOMZ, a feature that is misrepresented in most coupled OGCMs (Oschlies et al., 2008; Gnanadesikan et al., 2012). The WOA05 fields lack an eastward shift and northward intensification of the upper and lower ASOMZ (top- and middle-left panels), likely owing to data scarcity and smoothing. In the model, the eastward shift of the ASOMZ is caused primarily by strong eastward advection. It shifts most small detritus to the central/eastern AS before it can sink and be remineralized to consume oxygen and generate an OMZ.

47. Summary

48. Mixed layer thickness: The Arabian-Sea mixed layer has a prominent annual cycle. A Kraus-Turner model is able to simulate the mixed-layer annual cycle in the Arabian Sea and elsewhere in the IO. Biophysical interactions: 1) Near the surface, physics impacts biology through upwelling, entrainment, detrainment, and advection. 2) Shallow overturning cells, the CEC and STC, provide the water that upwells in the northern IO and along 5–10ºS. 3) Deeper circulations impact OMZs. Arabian Sea: In the central Arabian Sea (away from upwelling regions), blooms are driven by mixed-layer entrainment and detrainment events. There, the response of an NPZD model is very sensitive to mixed-layer thickness, indicating that the precise simulation of the physical state is critical for the realistic simulation of biological activity. Bay of Bengal: In the southern Bay and south of Sri Lanka, summertime blooms are driven by upwelling and advection. In the western Bay, wintertime blooms are driven in part by entrainment of subsurface phytoplankton into the surface mixed layer. South Indian Ocean: The South Indian Ocean has a weak annual cycle of phytoplankton. The seasonal bloom appears to be driven by entrainment into the surface layer of subsurface phytoplankton as well as nutrients.

49. Interannual events: During ENSO/IOD events, easterly winds develop along the equator. They cause upwelling along Sumatra and Java, lowering SST and generating a bloom there. AS & BoB OMZs: The eastward shift of the ASOMZ is caused primarily by strong eastward advection. It shifts most small detritus to the central/eastern AS before it can sink and be remineralized to consume oxygen and generate an OMZ.

51. Intraseasonal variability MJOs

52. MJOs are eastward-propagating, convective disturbances, typically with periods of 30–60 days. Their impacts on rainfall, oceanic surface fluxes, and SST are well documented. Waliser, Murtugudde, Lucas (2003, 2004) 100°E 150°E 180° easterlies westerlies Madden-Julian oscillations (MJOs)

53. Maps of SeaWiFs chlorophyll data composited for 13 summer MJOs from 1998–2004. “Chlorophyll ratio” is the value relative to the seasonal mean, thus 1.20 means a 20% increase over the typical seasonal value. Chlorophyll from SeaWiFs (NH summer) Systematic changes associated with MJOs are observed over most of the tropical Indian and West Pacific Oceans.

54. Model-derived, mixed-layer- thickness anomalies associated with MJO forcing. Mixed-layer thickness (NH summer) Positive anomalies indicate a thicker mixed layer, and thus regions that might be expected to have enhanced nutrients and hence to higher phytoplankton concentrations. This relation- ship holds at some, but not all, locations.

55. Intraseasonal variability South Indian Ocean

56. The thermocline rises to be close to the surface in a band from 5º–10ºS in the western and central IO in response to Ekman suction associated with the Southeast Trades. The model shown at the left illustrates the thermocline ridge and its seasonal variability. January July McCreary, Kundu, and Molinari (1993) Thermocline ridge Since the thermocline is shallow in the ridge, strengthened intraseasonal winds can cause thermocline variables (P and N) to be entrained into the surface mixed layer.

57. Kawamiya and Oschlies (2001; GRL) Observed (left panel) and modeled (right panel) chlorophyll (mg/m 3 ) concentrations during September, 1998. Units are mg/m 3. Chl (obs) Chl (model) Summertime variability In the model, there is a band of high concentration from 10−12S. There are also distinct patches of intense blooms. What causes them?

58. Observed and modeled chlorophyll (top) and sea level (bottom) during summer and fall, 1998. Sea level (model) Sea level (obs) In both the model and observations, chlorophyll variations are associated with westward-propaga- ting disturbances. Chl (obs) Chl (model) Variability along 12ºS during 1998

59. 8/13 9/2 9/22 During a phase of high chlorophyll, there is upwelling, the mixed-layer thickens, and the subsurface, chlorophyll maximum is entrained to the surface. Biophysical processes

60. Intraseasonal variability: The strength of phytoplankton blooms is linked to the life cycle of MJOs, and some blooms appear to be driven by MJO-induced changes in mixed-layer thickness. ISV in the South Indian Ocean: During the summer, some surface blooms are associated with the passage of Rossby waves, which shallow the thermocline. The shallowing intensifies entrainment into the surface layer, and thereby bringing subsurface phytoplankton and nutrients into the surface layer. Interannual events: During ENSO/IOD events, easterly winds develop along the equator. They cause upwelling along Sumatra and Java, lowering SST and generating a bloom there. AS & BoB OMZs: The eastward shift of the ASOMZ is caused primarily by strong eastward advection. It shifts most small detritus to the central/eastern AS before it can sink and be remineralized to consume oxygen and generate an OMZ.