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The Positive Indian Ocean Dipole-like Response in the Tropical Indian Ocean to Global Warming

doi: 10.1007/s00376-015-5027-5

  • Climate models project a positive Indian Ocean Dipole (pIOD)-like SST response in the tropical Indian Ocean to global warming. By employing the Community Earth System Model and applying an overriding technique to its ocean component (version 2 of the Parallel Ocean Program), this study investigates the similarities and differences of the formation mechanisms for the changes in the tropical Indian Ocean during the pIOD versus global warming. Results show that their formation processes and related seasonality are quite similar; in particular, wind-thermocline-SST feedback is the leading mechanism in producing the anomalous cooling over the eastern tropics in both cases. Some differences are also found, including the fact that the cooling effect of the vertical advection over the eastern tropical Indian Ocean is dominated by the anomalous vertical velocity during the pIOD but by the anomalous upper-ocean stratification under global warming. These findings are further examined through an analysis of the mixed layer heat budget.
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  • Alory G., G. Meyers, 2009: Warming of the upper equatorial Indian Ocean and changes in the heat budget (1960-99). J. Climate, 22, 93- 113.10.1175/ In the equatorial Indian Ocean, sea surface has warmed by 0.5°–1°C over the 1960–99 period, while waters have cooled at thermocline depth and the net atmospheric heat flux has decreased. Among a set of twentieth-century climate simulations from 12 coupled models, the Centre National de Recherches Météorologiques Coupled Global Climate Model version 3 (CNRM-CM3) reproduces key observed features of these changes. It is used to investigate changes in the heat budget of the upper equatorial Indian Ocean and identify mechanisms responsible for the warming. By comparing twentieth-century and control simulations, significant shifts in the mean balance of the heat budget between the preindustrial and the 1960–99 periods can be identified. The main cause of the surface warming is a decrease in the upwelling-related oceanic cooling. It occurs in the thermocline dome region because of a slowdown of the wind-driven Ekman pumping. The observed decrease in net heat flux is a negative feedback driven by evaporation, which is enhanced by the equatorial warming and associated strengthening of trade winds.
    Baquero-Bernal A., M. Latif, and S. Legutke, 2002: On dipolelike variability of sea surface temperature in the tropical Indian Ocean. J. Climate, 15, 1358- 1368.10.1175/1520-0442(2002)015<1358:ODVOSS>2.0.CO; aim of this study is to investigate the differences on ultrastructure of the cochleae caused by different classic musical opuses with different intonations. Guinea pigs were grouped into 3, one of which was the control and the other two were the experimental groups. While the first group, which was the control, was not exposed to any music, the second group was exposed to classic musical opuses with extensive intervals (40 decibel) and third group was exposed to classical music opuses with strained intonations (60 decibel) for 6 h a day with 15 min-intervals for totally 10 days. Cochleae tissue samples were taken from the guinea pigs at the end of the tenth day. They were examined at the electron microscopic level. In addition to compansatris processes on the cochleae, thickening on the stereocilias of hair cells and basal membranes and proliferation on the synaptic terminalles of afferent nerves caused by extensive intonations were observed. Extremely obvious degenerative differences such as damage in neuroepitelial cells, nerves and synaptic terminalles as well as componsatris processes caused by strained intonations were determined. As a result of all these observations it was concluded that continuously listening to the strained intonations used in musical opuses has a very harmful effect on the auditory system.
    Behera S. K., J. J. Luo, S. Masson, S. A. Rao, H. Sakuma, and T. Yamagata, 2006: A CGCM study on the interaction between IOD and ENSO. J. Climate, 19, 1688- 1705.10.1175/ An atmosphere–ocean coupled general circulation model known as the Scale Interaction Experiment Frontier version 1 (SINTEX-F1) model is used to understand the intrinsic variability of the Indian Ocean dipole (IOD). In addition to a globally coupled control experiment, a Pacific decoupled noENSO experiment has been conducted. In the latter, the El Ni09o–Southern Oscillation (ENSO) variability is suppressed by decoupling the tropical Pacific Ocean from the atmosphere. The ocean–atmosphere conditions related to the IOD are realistically simulated by both experiments including the characteristic east–west dipole in SST anomalies. This demonstrates that the dipole mode in the Indian Ocean is mainly determined by intrinsic processes within the basin. In the EOF analysis of SST anomalies from the noENSO experiment, the IOD takes the dominant seat instead of the basinwide monopole mode. Even the coupled feedback among anomalies of upper-ocean heat content, SST, wind, and Walker circulation over the Indian Ocean is reproduced. As in the observation, IOD peaks in boreal fall for both model experiments. In the absence of ENSO variability the interannual IOD variability is dominantly biennial. The ENSO variability is found to affect the periodicity, strength, and formation processes of the IOD in years of co-occurrences. The amplitudes of SST anomalies in the western pole of co-occurring IODs are aided by dynamical and thermodynamical modifications related to the ENSO-induced wind variability. Anomalous latent heat flux and vertical heat convergence associated with the modified Walker circulation contribute to the alteration of western anomalies. It is found that 42% of IOD events affected by changes in the Walker circulation are related to the tropical Pacific variabilities including ENSO. The formation is delayed until boreal summer for those IODs, which otherwise form in boreal spring as in the noENSO experiment.
    Bjerknes J., 1969: Atmospheric teleconnections from the equatorial Pacific. Mon. Wea. Rev., 97, 163- 172.10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO; The “high index” response of the northeast Pacific westerlies to big positive anomalies of equatorial sea temperature, observed in the winter of 1957–58, has been found to repeat during the major equatorial sea temperature maxima in the winters of 1963–64 and 1965–66. The 1963 positive temperature anomaly started early enough to exert the analogous effect on the atmosphere of the south Indian Ocean during its winter season. The maxima of the sea temperature in the eastern and central equatorial Pacific occur as a result of anomalous weakening of the trade winds of the Southern Hemisphere with inherent weakening of the equatorial upwelling. These anomalies are shown to be closely tied to the “Southern Oscillation” of Sir Gilbert Walker.
    Cai W., X. T. Zheng, E. Weller, M. Collins, T. Cowan, M. Lengaigne, W. D. Yu, and T. Yamagata, 2013: Projected response of the Indian Ocean Dipole to greenhouse warming. Nature Geoscience, 6, 999- 1007.10.1038/ modes of variability centred in the tropics, such as the El Nino/Southern Oscillation and the Indian Ocean Dipole, are a significant source of interannual climate variability across the globe. Future climate warming could alter these modes of variability. For example, with the warming projected for the end of the twenty-first century, the mean climate of the tropical Indian Ocean is expected to change considerably. These changes have the potential to affect the Indian Ocean Dipole, currently characterized by an alternation of anomalous cooling in the eastern tropical Indian Ocean and warming in the west in a positive dipole event, and the reverse pattern for negative events. The amplitude of positive events is generally greater than that of negative events. Mean climate warming in austral spring is expected to lead to stronger easterly winds just south of the Equator, faster warming of sea surface temperatures in the western Indian Ocean compared with the eastern basin, and a shoaling equatorial thermocline. The mean climate conditions that result from these changes more closely resemble a positive dipole state. However, defined relative to the mean state at any given time, the overall frequency of events is not projected to change - but we expect a reduction in the difference in amplitude between positive and negative dipole events.
    Cai W., A. Santoso, G. J. Wang, E. Weller, X. L. Wu, K. Ashok, Y. Masumoto, and T. Yamagata, 2014: Increased frequency of extreme Indian Ocean Dipole events due to greenhouse warming. Nature, 510, 254- 258.10.1038/ Indian Ocean dipole is a prominent mode of coupled ocean-atmosphere variability, affecting the lives of millions of people in Indian Ocean rim countries. In its positive phase, sea surface temperatures are lower than normal off the Sumatra-Java coast, but higher in the western tropical Indian Ocean. During the extreme positive-IOD (pIOD) events of 1961, 1994 and 1997, the eastern cooling strengthened and extended westward along the equatorial Indian Ocean through strong reversal of both the mean westerly winds and the associated eastward-flowing upper ocean currents. This created anomalously dry conditions from the eastern to the central Indian Ocean along the Equator and atmospheric convergence farther west, leading to catastrophic floods in eastern tropical African countries but devastating droughts in eastern Indian Ocean rim countries. Despite these serious consequences, the response of pIOD events to greenhouse warming is unknown. Here, using an ensemble of climate models forced by a scenario of high greenhouse gas emissions (Representative Concentration Pathway 8.5), we project that the frequency of extreme pIOD events will increase by almost a factor of three, from one event every 17.3-墆ears over the twentieth century to one event every 6.3 ears over the twenty-first century. We find that a mean state change--with weakening of both equatorial westerly winds and eastward oceanic currents in association with a faster warming in the western than the eastern equatorial Indian Ocean--facilitates more frequent occurrences of wind and oceanic current reversal. This leads to more frequent extreme pIOD events, suggesting an increasing frequency of extreme climate and weather events in regions affected by the pIOD.
    Clement A., P. DiNezio, and C. Deser, 2011: Rethinking the Ocean's role in the Southern Oscillation. J. Climate, 24, 4056-4072, doi: 10.1175/2011JCLI3973.1.10.1175/ The Southern Oscillation (SO) is usually described as the atmospheric component of the dynamically coupled El Ni09o–Southern Oscillation phenomenon. The contention in this work, however, is that dynamical coupling is not required to produce the SO. Simulations with atmospheric general circulation models that have varying degrees of coupling to the ocean are used to show that the SO emerges as a dominant mode of variability if the atmosphere and ocean are coupled only through heat and moisture fluxes. Herein this mode of variability is called the thermally coupled Walker (TCW) mode. It is a robust feature of simulations with atmospheric general circulation models (GCMs) coupled to simple ocean mixed layers. Despite the absence of interactive ocean dynamics in these simulations, the spatial patterns of sea level pressure, surface temperature, and precipitation variability associated with the TCW are remarkably realistic. This mode has a red spectrum indicating persistence on interannual to decadal time scales that appears to arise through an off-equatorial trade wind–evaporation–surface temperature feedback and cloud shortwave radiative effects in the central Pacific. When dynamically coupled to the ocean (in fully coupled ocean–atmosphere GCMs), the main change to this mode is increased interannual variability in the eastern equatorial Pacific sea surface temperature and teleconnections in the North Pacific and equatorial Atlantic, though not all coupled GCMs simulate this effect. Despite the oversimplification due to the lack of interactive ocean dynamics, the physical mechanisms leading to the TCW should be active in the actual climate system. Moreover, the robustness and realism of the spatial patterns of this mode suggest that the physics of the TCW can explain some of the primary features of observed interannual and decadal variability in the Pacific and the associated global teleconnections.
    DiNezio P. N., A. C. Clement, and G. A. Vecchi, 2010: Reconciling differing views of tropical Pacific climate change. Eos, Trans. Amer. Geophys.Union, 91, 141- 142.10.1029/ analyses of global warming projections simulated with global climate models (GCMs) suggest that the tropical Pacific does not become El Ni&ntilde;o- or La Ni&ntilde;a-like in response to increased greenhouse gases (GHGs). Rather, the physical mechanisms that drive tropical Pacific climate change depart substantially from the El Ni&ntilde;o-Southern Oscillation (ENSO) analogy often invoked for interpreting future climate changes [e.g., Knutson and Manabe, 1995; Meehl and Washington, 1996; Cane et al., 1997; Collins et al., 2005; Meehl et al., 2007; Lu et al., 2008; Cox et al., 2004] and past climate changes [e.g. Lea et al., 2001; Koutavas et al., 2002]. This presents an opportunity for reconciling theory, models, and observations. An ENSO analogy typically is invoked for interpreting tropical Pacific climate change because if an external forcing introduces some east-west asymmetry, this asymmetry can be amplified in the same way as interannual perturbations are, through the positive ocean-atmosphere Bjerknes feedback. This then would lead to an altered mean state of the tropical Pacific resembling El Ni&ntilde;o or La Ni&ntilde;a [ Dijkstra and Neelin, 1995]. For instance, the model projections used for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) anticipate tropical Pacific climate change in response to increased GHGs that has been described as El Ni&ntilde;o&mdash;like [ Meehl et al., 2007]. These models project robust enhanced equatorial warming [ Liu et al., 2006; DiNezio et al., 2009] and a weakening of the overturning atmosphere circulation across the tropical Pacific, i.e., the Walker circulation [ Vecchi and Soden, 2007], both of which occur during El Ni&ntilde;o events. However, these experiments also show a shoaling and sharpening of the equatorial thermocline [ Vecchi and Soden, 2007; DiNezio et al., 2009] (Figure 1a). This is in contrast to El Ni&ntilde;o events, when the thermocline response is heavily dominated by a relaxed tilt (Figure 1b).
    Huang P. Y., Y. Xue, H. Wang, W. Q. Wang, and A. Kumar, 2012: Mixed layer heat budget of the El Niño in NCEP climate forecast system. Climate Dyn., 39, 365- 381.10.1007/ mechanisms controlling the El Ni01±o have been studied by analyzing mixed layer heat budget of daily outputs from a free coupled simulation with the Climate Forecast System (CFS). The CFS is operational at National Centers for Environmental Prediction, and is used by Climate Prediction Center for seasonal-to-interannual prediction, particularly for the prediction of the El Ni01±o and Southern Oscillation (ENSO) in the tropical Pacific. Our analysis shows that the development and decay of El Ni01±o can be attributed to ocean advection in which all three components contribute. Temperature advection associated with anomalous zonal current and mean vertical upwelling contributes to the El Ni01±o during its entire evolutionary cycle in accordance with many observational, theoretical, and modeling studies. The impact of anomalous vertical current is found to be comparable to that of mean upwelling. Temperature advection associated with mean (anomalous) meridional current in the CFS also contributes to the El Ni01±o cycle due to strong meridional gradient of anomalous (mean) temperature. The surface heat flux, non-linearity of temperature advection, and eddies associated with tropical instabilities waves (TIW) have the tendency to damp the El Ni01±o. Possible degradation in the analysis and closure of the heat budget based on the monthly mean (instead of daily) data is also quantified.
    Iskand ar, I., W. Mardiansyah, D. Setiabudidaya, A. K. Affand i, F. Syamsuddin, 2014: Surface and subsurface oceanic variability observed in the eastern equatorial Indian Ocean during three consecutive Indian Ocean dipole events: 2006-2008. AIP Conference Proceedings 1617,48, doi: 10.1063/1.4897101.
    Lau N. C., M. J. Nath, 2004: Coupled GCM simulation of atmosphere-ocean variability associated with zonally asymmetric SST changes in the tropical Indian Ocean. J. Climate, 17, 245-
    Li T., Y. S. Zhang, E. Lu, and D. L. Wang, 2002: Relative role of dynamic and thermodynamic processes in the development of the Indian Ocean dipole: An OGCM diagnosis. Geophys. Res. Lett., 29,2110, doi: 10.1029/2002GL015789.10.1029/[1] The relative role of oceanic dynamics and surface heat fluxes in the initiation and development of the Indian Ocean dipole was investigated by analyzing results from an oceanic general circulation model. The model was forced by observed surface wind stress and heat flux fields for 1958-1997. The results show that it was capable of reproducing observed dipole events over the tropical Indian Ocean. The diagnosis of the mixed-layer heat budget indicates that the SST anomaly (SSTA) in the east pole is primarily induced by anomalous surface latent heat flux and vertical temperature advection, whereas in the west pole it is mainly caused by meridional and vertical temperature advection anomalies. In both regions shortwave radiation anomalies tend to damp the SSTA. The ocean Rossby waves are essential in linking the anomalous wind and SST off Sumatra and subsurface temperature variations in southwest Indian Ocean.
    Li T., B. Wang, C. P. Chang, and Y. S. Zhang, 2003: A theory for the Indian Ocean dipole-zonal mode. J. Atmos. Sci., 60, 2119- 2135.10.1175/1520-0469(2003)060<2119:ATFTIO>2.0.CO; Four fundamental differences of air-sea interactions between the tropical Pacific and Indian Oceans are identified based on observational analyses and physical reasoning. The first difference is represented by the strong contrast of a zonal cloud-SST phase relationship between the warm and cool oceans. The in-phase cloud- SST relationship in the warm oceans leads to a strong negative feedback, while a significant phase difference in the cold tongue leads to a much weaker thermodynamic damping. The second difference arises from the reversal of the basic-state zonal wind and the tilting of the ocean thermocline, which leads to distinctive effects of ocean waves. The third difference lies in the existence of the Asian monsoon and its interaction with the adjacent oceans. The fourth difference is that the southeast Indian Ocean is a region where a positive atmosphere- ocean thermodynamic feedback exists in boreal summer. A conceptual coupled atmosphere-ocean model was constructed aimed to understand the origin of the Indian Ocean dipole-zonal mode (IODM). In the model, various positive and negative air-sea feedback processes were considered. Among them were the cloud-radiation-SST feedback, the evaporation-SST-wind feedback, the thermocline-SST feedback, and the monsoon-ocean feedback. Numerical results indicate that the IODM is a dynamically coupled atmosphere-ocean mode whose instability depends on the annual cycle of the basic state. It tends to develop rapidly in boreal summer but decay in boreal winter. As a result, the IODM has a distinctive evolution characteristic compared to the El Nino. Sensitivity experiments suggest that the IODM is a weakly damped oscillator in the absence of external forcing, owing to a strong negative cloud-SST feedback and a deep mean thermocline in the equatorial Indian Ocean. A thermodynamic air-sea (TAS) feedback arises from the interaction between an anomalous atmospheric anticyclone and a cold SST anomaly (SSTA) off Sumatra. Because of its dependence on the basic-state wind, the nature of this TAS feedback is season dependent. A positive feedback occurs only in northern summer when the southeasterly flow is pronounced. It becomes a negative feedback in northern winter when the northwesterly wind is pronounced. The phase locking of the IODM can be, to a large extent, explained by this seasonal- dependent TAS feedback. The biennial tendency of the IODM is attributed to the monsoon-ocean feedback and the remote El Nino forcing that has a quasi-biennial component. In the presence of realistic Nino-3 SSTA forcing, the model is capable of simulating IODM events during the last 50 yr that are associated with the El Nino, indicating that ENSO is one of triggering mechanisms. The failure of simulation of the 1961 and 1994 events suggests that other types of climate forcings in addition to the ENSO must play a role in triggering an IODM event.
    Lu J., B. Zhao, 2012: The role of oceanic feedback in the climate response to doubling CO2. J. Climate, 25, 7544- 7563.10.1175/ Two suites of partial coupling experiments are devised with the upper-ocean dynamics version (UOM) of the CCSM3 to isolate the effects of the feedbacks from the change of the wind-driven ocean circulation and air–sea heat flux in the global climate response to the forcing of doubling CO 2 . The partial coupling is achieved by implementing a so-called overriding technique, which helps quantitatively partition the total response in the fully coupled model to the feedback component in question and the response to external forcing in the absence of the former. By overriding the wind stress seen by the ocean and the wind speed through the bulk formula for evaporation, the experiments help to reveal that (i) the wind–evaporation–SST (WES) feedback is the main formation mechanism for the tropical SST pattern under the CO 2 forcing, verifying the hypothesis proposed by Xie et al.; (ii) the weakened tropical Pacific wind is shown in this UOM model not to be the cause for the enhanced equatorial Pacific warming, as one might expect from the thermocline and Bjerknes feedbacks; (iii) WES is also the leading mechanism for shaping the tropical precipitation response in the ocean; and (iv) both the wind-driven ocean dynamical feedback and the WES feedback act to increase the persistence of the southern annular mode (SAM) and the increased time scale of the SAM due to these feedbacks manifests itself in the response of the jet shift to an identical CO 2 forcing, in a manner conforming to the fluctuation–dissipation theorem.
    Luo Y. Y., Q. Y. Liu, and L. M. Rothstein, 2009: Simulated response of North Pacific Mode Waters to global warming. Geophys. Res. Lett., 36,L23609, doi: 10.1029/2009GL040906.10.1029/[1] This study investigates the response of the Mode Waters in the North Pacific to global warming based on a set of Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) models. Solutions between a present-day climate and a future, warmer climate are compared. Under the warmer climate scenario, the Mode Waters are produced on lighter isopycnal surfaces and are significantly weakened in terms of their formation and evolution. These changes are due to a more stratified upper ocean and thus a shoaling of the winter mixing depth resulting mainly from a reduction of the ocean-to-atmosphere heat loss over the subtropical region. The basin-wide wind stress may adjust the Mode Waters indirectly through its impact on the surface heat flux and subduction process.
    Luo Y. Y., J. Lu, F. K. Liu, and W. Liu, 2014: Understanding the El Niño-like oceanic response in the tropical Pacific to global warming. Climate Dyn., doi: 10.1007/s00382-014-2448-2.10.1007/ enhanced central and eastern Pacific SST warming and the associated ocean processes under global warming are investigated using the ocean component of the Community Earth System Model (CESM), Parallel Ocean Program version 2 (POP2). The tropical SST warming pattern in the coupled CESM can be faithfully reproduced by the POP2 forced with surface fluxes computed using the aerodynamic bulk formula. By prescribing the wind stress and/or wind speed through the bulk formula, the effects of wind stress change and/or the wind-evaporation-SST (WES) feedback are isolated and their linearity is evaluated in this ocean-alone setting. Result shows that, although the weakening of the equatorial easterlies contributes positively to the El Nino-like SST warming, 80% of which can be simulated by the POP2 without considering the effects of wind change in both mechanical and thermodynamic fluxes. This result points to the importance of the air-sea thermal interaction and the relative feebleness of the ocean dynamical process in the El Nino-like equatorial Pacific SST response to global warming. On the other hand, the wind stress change is found to play a dominant role in the oceanic response in the tropical Pacific, accounting for most of the changes in the equatorial ocean current more&raquo; system and thermal structures, including the weakening of the surface westward currents, the enhancement of the near-surface stratification and the shoaling of the equatorial thermocline. Interestingly, greenhouse gas warming in the absence of wind stress change and WES feedback also contributes substantially to the changes at the subsurface equatorial Pacific. Further, this warming impact can be largely replicated by an idealized ocean experiment forced by a uniform surface heat flux, whereby, arguably, a purest form of oceanic dynamical thermostat is revealed. 芦less
    Murtugudde R., J. P. McCreary, and A. J. Busalacchi, 2000: Oceanic processes associated with anomalous events in the Indian Ocean with relevance to 1997-1998. J. Geophys. Res., 105, 3295- 3306.10.1029/ An anomalous climatic event occurred in the Indian Ocean (IO) region during 1997-1998, which coincided with a severe drought in Indonesia and floods in parts of eastern Africa. Cool sea surface temperature anomalies (SSTAs) were present in the eastern IO along and south of the equator. Beginning in July 1997, warm SSTAs appeared in the western IO, and they peaked in February 1998. An ocean general circulation model is employed to investigate the dynamic and thermodynamic processes that caused the SSTAs associated with this and other similar IO events. The eastern cooling resulted from unusually strong upwelling along the equator and Sumatra. The Sumatran upwelling was forced both locally by the stronger alongshore winds and remotely by equatorial and coastal Kelvin waves. By the end of 1997, weakening of the winds and the associated reduction in latent heat loss led to the elimination of the cold SST anomalies in the east. The western warming was initiated by weaker Southwest Monsoon winds and maintained by enhanced precipitation forcing, which resulted in a barrier layer structure. Analysis of the mixed layer temperature equation indicates that a downwelling Rossby wave contribution was crucial for sustaining the warming into February 1998. It is tempting to suppose that the 1997 event was related to the El Ni&ntilde;o-Southern Oscillation (ENSO) event that took place in the Pacific at the same time. Indeed, weaker IO events occur quite regularly in the control run that evolve similarly to the 1997 event, and they are often but not always related to ENSO. We speculate that these events represent a natural mode of oscillation in the IO, which is externally forced by ENSO but also excited by ocean-atmosphere interactions internal to the IO.
    Pacanowski R. C., S. G. H. Philander, 1981: Parameterization of vertical mixing in numerical models of tropical oceans. J. Phys. Oceanogr., 11, 1443-
    Saji N. H., T. Yamagata, 2003: Structure of SST and surface wind variability during Indian Ocean dipole mode events: COADS observations. J. Climate, 16, 2735- 2751.10.1175/1520-0442(2003)016<2735:SOSASW>2.0.CO; A study of the detailed spatiotemporal characteristics of the Indian Ocean dipole (IOD) mode in SST and surface winds using available observations from 1958 till 1997 is reported. The analysis is used to address several of the controversial issues regarding the IOD.One key finding of this study is that interdecadal fluctuations contribute strongly to tropical Indian Ocean (TIO) SST variability; in SST anomalies (SSTA) interdecadal variance is as strong as interannual variance. Over both the western and eastern TIO, an accelerated warming of SST after the mid-1970s is apparent. The lack of anticorrelation between western and eastern TIO SSTA occurs only in this latter half of the analysis period.In order to examine the hypothesis that the IOD is a part of ENSO evolution in the TIO, the temporal characteristics of IOD indices have been compared with Ni&ntilde;o-3. On the basis of several quantitative comparisons that include wavelet and cross-wavelet analysis, several important differences between the two phenomena are reported. These differences are highlighted to argue that the IOD is not a part of ENSO evolution in the TIO. On the other hand, a striking similarity is found in the temporal structure of atmospheric and oceanic variability within the TIO that is suggestive of IOD arising from inherent coupled air-sea interactions in the TIO.ENSO events that do not co-occur with IOD have been isolated and their impacts on TIO SSTA and winds described. Similarly, the characteristics of IOD events that occur independently of ENSO are described. Based on the characteristics of these two groups a hypothesis is suggested through which both phenomena may interact. It is noted that ENSO events co-occurring with IOD events are much stronger compared to non-co-occurring events. On the other hand, IOD events that are independent of ENSO as well as those that co-occur with it appear to have the same strength.
    Saji N. H., B. N. Goswami, P. N. Vinayachand ran, and T. Yamagata, 1999: A dipole mode in the tropical Indian Ocean. Nature, 401, 360- 363.10.1038/ the tropical Pacific and Atlantic oceans, internal modes of variability that lead to climatic oscillations have been recognized, but in the Indian Ocean region a similar ocean-atmosphere interaction causing interannual climate variability has not yet been found. Here we report an analysis of observational data over the past 40 years, showing a dipole mode in the Indian Ocean: a pattern of internal variability with anomalously low sea surface temperatures off Sumatra and high sea surface temperatures in the western Indian Ocean, with accompanying wind and precipitation anomalies. The spatio-temporal links between sea surface temperatures and winds reveal a strong coupling through the precipitation field and ocean dynamics. This air-sea interaction process is unique and inherent in the Indian Ocean, and is shown to be independent of the El Nino/Southern Oscillation. The discovery of this dipole mode that accounts for about 12% of the sea surface temperature variability in the Indian Ocean--and, in its active years, also causes severe rainfall in eastern Africa and droughts in Indonesia--brightens the prospects for a long-term forecast of rainfall anomalies in the affected countries.
    Vecchi G. A., B. J. Soden, 2007: Global Warming and the Weakening of the Tropical Circulation. J. Climate, 20, 4316- 4340.10.1175/ This study examines the response of the tropical atmospheric and oceanic circulation to increasing greenhouse gases using a coordinated set of twenty-first-century climate model experiments performed for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The strength of the atmospheric overturning circulation decreases as the climate warms in all IPCC AR4 models, in a manner consistent with the thermodynamic scaling arguments of Held and Soden. The weakening occurs preferentially in the zonally asymmetric (i.e., Walker) rather than zonal-mean (i.e., Hadley) component of the tropical circulation and is shown to induce substantial changes to the thermal structure and circulation of the tropical oceans. Evidence suggests that the overall circulation weakens by decreasing the frequency of strong updrafts and increasing the frequency of weak updrafts, although the robustness of this behavior across all models cannot be confirmed because of the lack of data. As the climate warms, changes in both the atmospheric and ocean circulation over the tropical Pacific Ocean resemble “El Ni09o–like” conditions; however, the mechanisms are shown to be distinct from those of El Ni09o and are reproduced in both mixed layer and full ocean dynamics coupled climate models. The character of the Indian Ocean response to global warming resembles that of Indian Ocean dipole mode events. The consensus of model results presented here is also consistent with recently detected changes in sea level pressure since the mid–nineteenth century.
    Vinayachand ran, P. N., S. Iizuka, T. Yamagata, 2002: Indian Ocean dipole mode events in an ocean general circulation model. Deep-Sea Res., 49, 1573- 1596.10.1016/S0967-0645(01) evolution of the dipole mode (DM) events in the Indian Ocean is examined using an ocean model that is driven by the NCEP fluxes for the period 1975-1998. The positive DM events during 1997, 1994 and 1982 and negative DM events during 1996 and 1984-1985 are captured by the model and it reproduces both the surface and subsurface features associated with these events. In its positive phase, the DM is characterized by warmer than normal SST in the western Indian Ocean and cooler than normal SST in the eastern Indian Ocean. The DM events are accompanied by easterly wind anomalies along the equatorial Indian Ocean and upwelling-favorable alongshore wind anomalies along the coast of Sumatra. The Wyrtki jets are weak during positive DM events, and the thermocline is shallower than normal in the eastern Indian Ocean and deeper in the west. This anomaly pattern reverses during negative DM events.During the positive phase of the DM easterly wind anomalies excite an upwelling equatorial Kelvin wave. This Kelvin wave reflects from the eastern boundary as an upwelling Rossby wave which propagates westward across the equatorial Indian Ocean. The anomalies in the eastern Indian Ocean weaken after the Rossby wave passes. A similar process excites a downwelling Rossby wave during the negative phase. This Rossby wave is much weaker but wind forcing in the central equatorial Indian Ocean amplifies the downwelling and increases its westward phase speed. This Rossby wave initiates the deepening of the thermocline in the western Indian Ocean during the following positive phase of the DM. Rossby wave generated in the southern tropical Indian Ocean by Ekman pumping contributes to this warming. Concurrently, the temperature equation of the model shows upwelling and downwelling to be the most important mechanism during both positive events of 1994 and 1997.
    Yang H. J., F. Y. Wang, and A. D. Sun, 2009: Understanding the ocean temperature change in global warming: The tropical Pacific. Tellus A, 61, 371- 380.10.1111/ synthesized a mixed crystal of lanthanum-neodymium oxychloride (La Nd OCl) by the liquid pahse method. The change of the crystal structure with the Nd content was investigated by X-ray diffraction, Raman scattering and infrared absorption. We also studied the optical emission and the excitation spectra of the doped Ce and Nd ions in this material. Additional emission peaks from Nd ions in the visible region were observed.
    Yu J. Y., K. M. Lau, 2004: Contrasting Indian Ocean SST variability with and without ENSO influence: A coupled atmosphere-ocean study. Meteor. Atmos. Phys.,90, 179-191, doi: 10.1007/s00703-004-0094-7.10.1007/ this study, we perform experiments with a coupled atmosphere-ocean general circulation model (CGCM) to examine ENSO’s influence on the interannual sea-surface temperature (SST) variability of the tropical Indian Ocean. The control experiment includes both the Indian and Pacific Oceans in the ocean model component of the CGCM (the Indo-Pacific Run). The anomaly experiment excludes ENSO’s influence by including only the Indian Ocean while prescribing monthly-varying climatological SSTs for the Pacific Ocean (the Indian-Ocean Run). In the Indo-Pacific Run, an oscillatory mode of the Indian Ocean SST variability is identified by a multi-channel singular spectral analysis (MSSA). The oscillatory mode comprises two patterns that can be identified with the Indian Ocean Zonal Mode (IOZM) and a basin-wide warming/cooling mode respectively. In the model, the IOZM peaks about 3–5 months after ENSO reaches its maximum intensity. The basin mode peaks 8 months after the IOZM. The timing and associated SST patterns suggests that the IOZM is related to ENSO, and the basin-wide warming/cooling develops as a result of the decay of the IOZM spreading SST anomalies from western Indian Ocean to the eastern Indian Ocean. In contrast, in the Indian-Ocean Run, no oscillatory modes can be identified by the MSSA, even though the Indian Ocean SST variability is characterized by east–west SST contrast patterns similar to the IOZM. In both control and anomaly runs, IOZM-like SST variability appears to be associated with forcings from fluctuations of the Indian monsoon. Our modeling results suggest that the oscillatory feature of the IOZM is primarily forced by ENSO.
    Zheng X. T., S. P. Xie, G. A. Vecchi, Q. Y. Liu, and J. Hafner, 2010: Indian Ocean dipole response to global warming: Analysis of ocean-atmospheric feedbacks in a coupled model. J. Climate, 23, 1240- 1253.10.1175/ modulation and change under global warming of the Indian Ocean dipole (IOD) mode are investigated with a pair of multicentury integrations of a coupled ocean09 tmosphere general circulation model: one under constant climate forcing and one forced by increasing greenhouse gas concentrations. In the unforced simulation, there is significant decadal and multidecadal modulation of the IOD variance. The mean thermocline depth in the eastern equatorial Indian Ocean (EEIO) is important for the slow modulation, skewness, and ENSO correlation of the IOD. With a shoaling (deepening) of the EEIO thermocline, the thermocline feedback strengthens, and this leads to an increase in IOD variance, a reduction of the negative skewness of the IOD, and a weakening of the IOD09 NSO correlation. In response to increasing greenhouse gases, a weakening of the Walker circulation leads to easterly wind anomalies in the equatorial Indian Ocean; the oceanic response to weakened circulation is a thermocline shoaling in the EEIO. Under greenhouse forcing, the thermocline feedback intensifies, but surprisingly IOD variance does not. The zonal wind anomalies associated with IOD are found to weaken, likely due to increased static stability of the troposphere from global warming. Linear model experiments confirm this stability effect to reduce circulation response to a sea surface temperature dipole. The opposing changes in thermocline and atmospheric feedbacks result in little change in IOD variance, but the shoaling thermocline weakens IOD skewness. Little change under global warming in IOD variance in the model suggests that the apparent intensification of IOD activity during recent decades is likely part of natural, chaotic modulation of the ocean09 tmosphere system or the response to nongreenhouse gas radiative changes.
    Zheng X. T., S. P. Xie, Y. Du, L. Liu, G. Huang, and Q. Y. Liu, 2013: Indian Ocean dipole response to global warming in the CMIP5 multimodel ensemble. J. Climate, 26, 6067- 6080.10.1175/ The response of the Indian Ocean dipole (IOD) mode to global warming is investigated based on simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). In response to increased greenhouse gases, an IOD-like warming pattern appears in the equatorial Indian Ocean, with reduced (enhanced) warming in the east (west), an easterly wind trend, and thermocline shoaling in the east. Despite a shoaling thermocline and strengthened thermocline feedback in the eastern equatorial Indian Ocean, the interannual variance of the IOD mode remains largely unchanged in sea surface temperature (SST) as atmospheric feedback and zonal wind variance weaken under global warming. The negative skewness in eastern Indian Ocean SST is reduced as a result of the shoaling thermocline. The change in interannual IOD variance exhibits some variability among models, and this intermodel variability is correlated with the change in thermocline feedback. The results herein illustrate that mean state changes modulate interannual modes, and suggest that recent changes in the IOD mode are likely due to natural variations.
    Zhong A. H., H. H. Hendon, and O. Alves, 2005: Indian Ocean variability and its association with ENSO in a global coupled model. J. Climate, 18, 3634- 3649.
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Manuscript received: 25 January 2015
Manuscript revised: 03 June 2015
Manuscript accepted: 09 July 2015
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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The Positive Indian Ocean Dipole-like Response in the Tropical Indian Ocean to Global Warming

  • 1. Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100
  • 2. Atmospheric Sciences & Global Change Division, Pacific Northwest National Laboratory, WA 99352, USA

Abstract: Climate models project a positive Indian Ocean Dipole (pIOD)-like SST response in the tropical Indian Ocean to global warming. By employing the Community Earth System Model and applying an overriding technique to its ocean component (version 2 of the Parallel Ocean Program), this study investigates the similarities and differences of the formation mechanisms for the changes in the tropical Indian Ocean during the pIOD versus global warming. Results show that their formation processes and related seasonality are quite similar; in particular, wind-thermocline-SST feedback is the leading mechanism in producing the anomalous cooling over the eastern tropics in both cases. Some differences are also found, including the fact that the cooling effect of the vertical advection over the eastern tropical Indian Ocean is dominated by the anomalous vertical velocity during the pIOD but by the anomalous upper-ocean stratification under global warming. These findings are further examined through an analysis of the mixed layer heat budget.

1. Introduction
  • The Indian Ocean Dipole (IOD) is the dominant mode of interannual variability over the tropical Indian Ocean (e.g., Saji et al., 1999; Murtugudde et al., 2000). The IOD usually peaks in austral spring, and its positive phase (pIOD) event is characterized by a decrease of SST and rainfall in the eastern tropical Indian Ocean (ETIO) but an increase of SST and rainfall in the western tropical Indian Ocean (WTIO), accompanying easterly anomalies of surface winds along the equatorial Indian Ocean where weak westerlies prevail in a normal spring season. The IOD is an air-sea coupled mode and can develop with or without the presence of El Niño-Southern Oscillation (ENSO) (e.g., Baquero-Bernal et al., 2002; Li et al., 2002, 2003; Saji and Yamagata, 2003; Lau and Nath, 2004; Yu and Lau, 2004; Zhong et al., 2005; Behera et al., 2006). Among the many feedbacks associated with the IOD, the positive wind-thermocline-SST feedback is believed to be the most important (Bjerknes, 1969).

    Recent studies have shown that mean climate conditions in the tropical Indian Ocean shift towards a pIOD-like state under global warming (GW), with features such as anomalous easterlies along the equator, stronger warming in the WTIO, and weaker warming in the ETIO accompanied by thermocline shoaling (Zheng et al., 2010, 2013; Cai et al., 2013). These oceanic changes are generally interpreted as a direct response to a weakening of easterly wind anomalies in the equatorial Indian Ocean associated with the slowdown of the Walker circulation, a robust signature of the atmospheric response to GW (e.g., Vecchi and Soden, 2007). The mean state changes will have profound impacts on the future climate variability in the tropical Indian Ocean. For example, the thermocline-SST feedback (i.e., the Bjerknes feedback) intensifies because of the shallower thermocline in the ETIO, resulting in a reduction of the negative skewness in the ETIO SST (Zheng et al., 2010, 2013). The future pIOD event will develop and terminate earlier than the canonical pIOD due to an earlier onset of the Asian summer monsoon associated with the weakened Indian Ocean Walker circulation (Cai et al., 2013). The frequency of extreme pIOD events will also increase significantly due to climatologically stronger west-minus-east SST gradients and easterly winds along the equatorial Indian Ocean (Cai et al., 2014).

    To date, there has been no reporting, in terms of formation processes, of the similarities and differences with respect to the changes in the tropical Indian Ocean between a pIOD event and the pIOD-like mean state under GW. For its counterpart in the Pacific where GW induces an El Niño-like condition, it was found that the physical mechanisms that drive tropical Pacific climate change depart substantially from the ENSO analogy that is often invoked for interpreting future climate change (e.g., DiNezio et al., 2010); while being a major player in the positive feedback loop during El Niño, the weakening of the equatorial easterlies contribute only marginally to the El Niño-like SST pattern formation under GW (Luo et al., 2014). In addition, our recent model experiments also revealed distinct mechanisms for the El Niño-like Pacific warming under greenhouse gas forcing from El Niño (Luo et al., 2014).

    The central goal of this study is to examine the similarities and differences of the formation mechanisms for the changes in the tropical Indian Ocean between the pIOD and GW. Our main finding is that, quite similar to the situation during the pIOD, the wind-thermocline-SST feedback plays the leading role in decreasing the warming in the ETIO under GW. This result is in stark contrast to what happens in the tropical Pacific where the wind stress change plays only a secondary role in the El Niño-like warming pattern. In addition, a heat budget analysis is performed to diagnose the mechanisms of the pattern formation under pIOD versus GW and to further confirm the above finding.

    The rest of the paper is structured as follows: Section 2 describes the model and numerical experiments. Section 3 introduces the methodology. Section 4 compares the oceanic and atmospheric changes between pIOD and GW. Section 5 analyzes the heat budget. A summary and discussion of our findings is then presented in section 6.

2. Model and simulations
  • The main modeling tool for this study is CESM1.1, which is comprised of the Community Atmospheric Model version 5 (CAM5), the Community Land Model version 4 (CLM4) and the POP2 ocean component.

    From the end of the historical experiment that is available at NCAR, a 94-year projection run under the Representative Concentration Pathway 8.5 scenario (RCP8.5) from 2006 to 2099 is first performed with CESM1.1, and its daily outputs of various oceanic and atmospheric variables are saved. This experiment is labeled "CPL85" (Table 1). Using this experiment, GW-induced trends are derived from least-squares linear fitting towards a straight line. In addition, the data from the CPL85 simulation are also used to construct a pIOD composite, the process of which is explained in detail in section3.

    Applying the daily surface atmospheric forcing fields from CPL85, the ocean model (POP2) is then integrated for 94 years from 2006 to 2099, and this experiment is called "FULL" (Table 1). Note that in POP2 bulk formulae are used to calculate evaporation as well as latent and sensible heat fluxes. A comparison of the SST trend in the tropics between the coupled and ocean-alone model runs reveals that the signature of the SST response is reproduced well by the ocean-alone model, including an El Niño-like response over the tropical Pacific Ocean and a pIOD-like warming pattern over the tropical Indian Ocean.

    In order to isolate the effect of changing wind stress (wind speed), experiment STRS (SPED) is performed with the wind stress (wind speed) fixed at repeating annual cycle of year 2006 while all other fields being the same as FULL.The wind stress contribution to the oceanic changes can be derived by subtracting STRS from FULL, and the wind speed contribution by subtracting SPED from FULL. The former reflects the effect of wind stress change on the ocean circulation and then the thermal structure (referred to as the effect of wind stress change on SST through the Bjerknes feedback). The latter reflects the effect of wind speed change on the latent heat flux through evaporation (referred to as Wind-Evaporation-SST or WES effect hereafter). It should be stressed that this WES effect only accounts for the direct thermal effect on ocean of the changing wind speed, not including the indirect feedbacks through the atmospheric processes as the WES in the fully coupled model (Lu and Zhao, 2012). The experiment WIND with both wind stress and wind speed fixed at year 2006 values is conducted to assess the linearity of the oceanic response to the two aspects to wind forcing, which turns out to hold accurately. In addition, another experiment is performed with POP2 driven repeatedly by the same atmospheric fields from 2006 for 94 years to serve as the control run for the overriding experiments, and this experiment is referred to as CTRL (Table 1).

    Figure 1.  Interannual variations of temperature simulated ($T_t$; black) and reconstituted ($ReT_t$; gray) from the heat budget, defined as the sum of net surface heat flux ($H$; green), zonal ($-uT_x$; red), meridional ($-vT_y$; yellow), and vertical ($-wT_z$; blue) advection heat terms, as well as the difference between the temperature simulated and reconstituted from this heat budget ($T_diff$; purple), for the top 55 m of (a) the WTIO and (b) the ETIO.

    In brief, the wind stress effect (WS) can be deduced from FULL-STRS, the wind speed effect (WES) from FULL-SPED, and the effect in the absence of wind stress and wind speed changes (w/o WS & WES) from WIND-CTRL, respectively. FULL-CTRL mimics the full response in the coupled CESM1.1, encompassing all the effects above. It should be noted that all these effects gleaned from the ocean-alone experiments could differ from those found in coupled model simulations.

3. Methods
  • A temperature budget analysis is performed to diagnose the leading maintenance mechanism for the SST anomalies revealed by the experiments. Since the 0-55 m layer temperature, mixed layer temperature, and SST have very similar interannual variability (not shown), a fixed bottom at 55 m is chosen for the heat budget to avoid entrainment terms. Reducing the number of terms eases interpretation but also reduces potential error sources in the computation (Alory and Meyers, 2009). The temperature budget equation is expressed as: \begin{equation} T_{t}=H-uT_x-vT_y-wT_z+T_{diff} , (1)\end{equation} where T t represents the tendency of the mixed layer temperature (MLT); H=(Q0-Q h)/(ρ0cph) is the net surface heat flux, in which Q0 and Q h are the heat fluxes at the surface and heat penetration through 55 m, respectively, and ρ and cp are the density and specific heat of sea water; -uTx, -vTy, and -wTz are the zonal, meridional, and vertical advection of temperature, respectively; and T diff represents the sum of contributions from the horizontal and vertical diffusion, and the convergence of heat by the transient eddies. For brevity, it is referred to as the diffusion term hereafter. Since the diffusion and eddy terms are not stored as part of the model's outputs, we can only infer the values of T diff as the residual of Eq. (1). A positive (negative) T diff indicates a heating (cooling) effect by diffusion.

    Figure 2.  Difference in the MLT anomaly between the WTIO (10$^\circ$S-10$^\circ$N, 50$^\circ$-70$^\circ$E) and the ETIO (10$^\circ$S-0$^\circ$, 90$^\circ$-110$^\circ$E). The horizontal dashed line at 2.2$^\circ$C is used as the criterion to define the IOD events, and 17 pIOD events are identified during the 94-year simulation period.

  • In this section we evaluate the MLT change from one year to the next and assess which mechanisms, by the terms in Eq. (1), control the change. The annual values of heat budget terms (Fig. 1) are computed from the outputs from CPL85, depicting the mean balance as well as the interannual variability. It is found that all heat budget terms are important, with the residual term (i.e., diffusion) being positive and working to warm the mixed layer in the tropical Indian Ocean. On average over the ETIO (WTIO), the warming from the net surface heat flux of 2.0°C yr-1 (2.0°C yr-1), meridional advection of 1.7°C yr-1 (1.9°C yr-1) and diffusion of 2.1°C yr-1 (0.6°C yr-1) is balanced by cooling from the vertical advection of -5.4°C yr-1 (-3.4°C yr-1) and zonal advection of -0.4°C yr-1 (-1.1°C yr-1).

    The annual temperature change simulated by the model (dT; expressed as black lines in Fig. 1) and the annual change reconstituted from the sum of the atmospheric and advective heat terms [d(H-uTx-vTy-wTz); expressed as gray lines in Fig. 1] are highly correlated (r≈ 0.70 in the ETIO and r≈ 0.93 in the WTIO), suggesting that this heat budget formulation without resolving explicitly the diffusion term can account for considerable interannual variability of the MLT in the tropical Indian Ocean. The difference between the simulated and reconstituted temperature change (Fig. 1) is an estimate of the importance of the total diffusion-eddy processes. It warms the tropical Indian Ocean, with a larger contribution in the east than west (average warming of 2.1°C yr-1 for the ETIO but only 0.6°C yr-1 for the WTIO). At the interannual scale, its variation is comparable to the net surface heat flux for the ETIO but is much less for the WTIO, suggesting that the diffusion and subgrid-scale mixing processes due to unresolved processes are more important for the closure of the interannual heat budget in the ETIO than in the WTIO.

  • We construct the pIOD composite following the procedure of (Huang et al., 2012), who constructed an El Niño composite based upon 60-year daily outputs from a coupled simulation with the Climate Forecast System. To formulate the pIOD composite, the simulated time series from 2006-99 in CPL85 are first detrended to remove the GW signal. Then, we obtain the difference in the MLT anomaly between the WTIO (10°S-10°N, 50°-70°E) and the ETIO (10°S-0°, 90°-110°E) in Fig. 2. In this analysis, a criterion of 2.2°C of the difference is chosen to define a pIOD event, and 17 pIOD events are identified during the 94-year simulation period. As in the observations, the peak amplitudes for these events are all phase-locked with austral spring. The year in which the pIOD events develop and mature are referred to as year 0. As such, we refer to May-July of year 0, August-October of year 0, November of year 0 to January of year 1, and February-April of year 1 as the development, peak, decay, and demise phases of pIOD, respectively. As we show in section 4, the composite pIOD captures the major characteristics of an observed pIOD event well.

    As the experiment FULL-CTRL successfully reproduces the interannual variability of CPL8.5, we use the same times of occurrence of the 17 events as in CPL85 for the pIOD composite for the overriding experiments. We find that the evolution of the pIOD composite in CPL85 (Fig. 3a) is reproduced well by FULL-CTRL (Fig. 3b), but with slightly larger amplitude, likely due to the lack of higher-than-daily-frequency air-sea fluxes in the ocean-alone experiments. The wind stress change plays a dominant role for the pIOD evolution (Fig. 3c), while the contribution from the wind speed change is negligible (Fig. 3d). Interestingly, in the absence of the wind stress and wind speed changes, WIND-CTRL can also produce weak pIOD events (Fig. 3e), hinting at possible formation mechanisms for IOD other than Bjerknes feedback (e.g., Clement et al., 2011).

    The analysis in the following sections is based primarily on the CPL85 simulation, and the overriding experiments are used to further isolate the role of individual feedbacks in the formation of pIOD and GW. Due to the high similarities between CPL85 and FULL-CTRL, all discussion related to the CPL85 run can be carried over to FULL-CTRL. Besides, since the magnitude of the modeled WES-induced oceanic change is negligible (Fig. 3d), we do not show the results of FULL-SPED (WES feedback) in the rest of the paper.

    In addition, to facilitate the comparison of the MLT patterns between pIOD and GW, the basin mean (averaged over 20°S-20°N in the Indian Ocean) of its response to GW has been removed.

4. Oceanic and atmospheric changes in the tropical Indian Ocean
  • Various features of the pIOD composite during the peak season are shown in Fig. 4. In comparison with observations (e.g., Murtugudde et al., 2000; Vinayachandran et al., 2002), CESM does a decent job in simulating the pIOD spatial distributions over the tropical Indian Ocean. Cold MLT anomalies appear in the ETIO, with the maximum cooling exceeding 3° centered at (100°E, 5°S) (Fig. 4a), accompanying lower sea surface height (not shown) and reduced rainfall in the ETIO (not shown) as well as easterly wind anomalies along the equator (Fig. 5c). The oceanic changes also include a reverse of the eastward flow (not shown) and upwelling into the mixed layer (Fig. 4e) along the equator. In addition, over the ETIO, the stratification below the mixed layer appears to be increased (Fig. 4g) due to a shallower thermocline there.

    GW-induced changes are also shown in Fig. 4. The MLT exhibits a clear pIOD-like pattern in the tropical Indian Ocean (Fig. 4b), with a cooling (i.e., reduced warming) over the ETIO and a warming (i.e., enhanced warming) over the WTIO. Despite sharing a number of similarities, a distinction from what happens during the pIOD appears in the southeast tropics around (95°E, 15°S), in which an anomalous cooling is found under GW (Fig. 4b). A comparison of the surface heat flux suggests that this is likely because the regional large positive anomalous atmospheric heat flux, which warms the surface ocean during the pIOD (Fig. 4i), is significantly reduced under GW (Fig. 4j).

    It is also clear that under a warming climate there is a remarkable westward shift of the anomalous easterlies compared to the situation during the pIOD (compare Fig. 4d to Fig. 4c). In response to this shift, both the eastward flow (not shown) and upwelling (Fig. 4f) along the equator are weaker compared to those associated with the pIOD (Figs. 4e). However, it is important to note that the upper-layer stratification under GW (Fig. 4h) is more intensified around the equator, especially over the ETIO, in spite of the wind shift. This is due mainly to the GW-induced warming generally decreasing with depth, leading to an increased temperature gradient of the upper ocean (e.g., Luo et al., 2009).

  • The seasonal evolution of the variables along 5°S during the pIOD and GW is shown in Fig. 5. As in the observations (e.g., Saji et al., 1999), cold MLT anomalies first appear in the ETIO in May-June (Fig. 5a), accompanied by moderate southeasterly wind anomalies (Figs. 5c and e). In the following months, the cold anomalies intensify while the WTIO begins to warm up, and zonal wind anomalies around the equator intensify together with the temperature dipole. A dramatically rapid peak of these features occurs in September, followed by a quick decay. Previous studies have shown the importance of wind stress change during a pIOD event, which is confirmed by the results of our overriding experiments (Fig. 6a), i.e., the wind stress effect contributes to the magnitude as well as seasonal evolution over both the ETIO and WTIO, while the effect in the absence of wind stress and wind speed changes merely contributes a small part to the anomalous warming and does not have much influence on the evolution of pIOD.

    The GW-induced seasonal evolution of MLT and wind anomalies in the tropical Indian Ocean is very similar to that during the pIOD. However, a striking difference is found in the seasonal evolution of the upper-layer stratification over the ETIO. For the pIOD, the local stratification is weakest during July-September (Fig. 5i) when the cooling there reaches a peak (Fig. 5a), suggesting that the vertical cooling is dominated by the change in the vertical velocity rather than stratification. Further, the overriding experiments reveal that the weak stratification is due to the effect of the absence of wind stress and wind speed changes (Fig. 6c). Without the WS & WES effect, the stratification is significantly reduced during austral winter, which partially offsets the enhanced stratification induced by the wind stress change (Fig. 6c). On the other hand, under a warming climate, the stratification over the ETIO (Fig. 5j) appears strongest during the peak cooling season (Fig. 5b), suggesting that the vertical cooling is dominated by the change in the stratification rather than upwelling. In addition, it is found from the overriding experiments that the GW-induced strong stratification during austral winter is due to a superposition of positive changes from both the wind stress effect and the w/o WS & WES effect (Fig. 6d), in contrast to what happens during the pIOD. Furthermore, the seasonal evolution of MLT under GW is controlled by the wind stress effect (Fig. 6b).

    It is interesting to note that there is an increase in the amplitude of the seasonal cycle of MLT under both pIOD and GW, expressed as greater cooling in low temperature months for the ETIO but more warming in high temperature months for the WTIO (Figs. 5a and b). For example, the maximum anomalous cooling in the ETIO is found in September when the climatological temperature there is lowest, while the warming in the WTIO is highest around January-February when it is the warmest season there. The increase of the seasonal cycle can also be found for the upwelling over the ETIO under both pIOD and GW (Figs. 5g and h), i.e., the induced upwelling reaches a maximum during July-August (about 1-2 months earlier than the cooling peak there) when the climatological vertical velocity happens to be largest in the upward direction.

    Figure 3.  Seasonal evolution of the pIOD composite in the (a) CPL85 simulation, (b) full response (FULL-CTRL), (c) wind stress effect (FULL-STRS), (d) wind speed effect (FULL-SPED), and (e) the effect in the absence of wind stress and wind speed changes (WIND-CTRL). The pink area denotes the upper and lower limits of the 17 composite members. Superscripts 0 and 1 in Jan, May and Sep denote year 0 and year 1, respectively.

    Figure 4.  The pIOD- (left) and GW-induced (right) changes during August-October: (a, b) MLT; (c, d) wind stress and its magnitude; (e, f) vertical velocity at a depth of 55 m; (g, h) stratification at a depth of 75 m; (i, j) surface heat flux. The GW-induced changes are their trends over 2006-99, normalized by multiplying 100 years, and the MLT in (b) is further normalized by subtracting the mean value of the field over 20$^\circ$S-20$^\circ$N in the Indian Ocean. Superimposed are their climatological fields of the corresponding variables in CPL85.

    Figure 5.  Seasonal evolution of anomalies during the pIOD composite (left) and GW (right) along 5$^\circ$S (between 6.5$^\circ$S and 3.5$^\circ$S): (a, b) MLT; (c, d) zonal wind stress; (e, f) meridional wind stress; (g, h) vertical velocity at a depth of 55 m; (i, j) stratification at a depth of 75 m. The anomalies under GW are their trends over 2006-99, normalized by multiplying 100 years, and the MLT in (b) is further normalized by subtracting the mean value of the field over 20$^\circ$S-20$^\circ$N in the Indian Ocean. Superimposed are their climatological fields of the corresponding variables in CPL85.

    Figure 6.  The pIOD- (left) and GW-induced (right) changes in (a, b) MLT, (c, d) stratification at a depth of 75 m, and (e, f) vertical velocity at a depth of 55 m over the ETIO (10$^\circ$S-0$^\circ$, 90$^\circ$-110$^\circ$E) (solid lines) and the WTIO (10$^\circ$S-10$^\circ$N, 50$^\circ$-70$^\circ$E) (dashed lines) in the CPL85 simulation (black), wind stress effect (FULL-STRS) (blue), and the effect in the absence of wind stress and wind speed changes (WIND-CTRL) (red).

  • Figure 7 shows the subsurface changes in temperature and thermocline depth along 5°S for both the pIOD and GW cases. The model reproduces well the major features of the thermocline changes in the tropical Indian Ocean during the pIOD (e.g., Vinayachandran et al., 2002; Iskandar et al., 2014). The subsurface temperature anomalies caused by the vertical movement of the isotherms are much larger than their surface counterpart, and the dipole pattern is present down to a depth of about 200 m, verifying the importance of ocean dynamics during the pIOD. The subsurface temperature anomalies are largest during November-January, a delay of one season compared to the surface dipole peak. Corresponding to the subsurface temperature changes, the thermocline shoals in the east but deepens in the west. The overriding experiments confirm that the wind stress change is responsible for the subsurface changes discussed above (not shown). Under GW, similar to what happens during the pIOD, the subsurface temperatures changes are much more significant than the surface changes, and reach a maximum during November-January. Also, it is found from the overriding experiments that the changes in the thermocline and the associated temperature are due mainly to the wind stress effect (not shown).

    Figure 7.  Seasonal evolution of temperature anomalies along 5$^\circ$S (averaged between 6.5$^\circ$S and 3.5$^\circ$S) during the pIOD composite (left) and GW (right). Superimposed are the thermocline depth (thick purple lines from an average of 2006-25; thick yellow lines in the left-hand side panels from an average of the 17 pIOD composite members; and thick yellow lines in the right-hand side panels from an average of 2080-99) and the climatological temperature in CPL85 (black contours). The thermocline depth is identified as the location of the maximum vertical gradient of temperature.

    Figure 8.  The pIOD- (left) and GW-induced (right) changes in the heat budget terms during August-October: (a, b) vertical advection; (c, d) zonal advection; (e, f) meridional advection; (g, h) net surface heat flux; (i, j) diffusion. Superimposed are their climatological fields of the corresponding variables in CPL85.

    Figure 9.  The pIOD- (left) and GW-induced (right) changes in (a, b) vertical advection, (c, d) zonal advection, (e, f) meridional advection, (g, h) net surface heat flux, and (i, j) diffusion over the ETIO (10$^\circ$S-0$^\circ$, 90$^\circ$-110$^\circ$E) (solid lines) and the WTIO (10$^\circ$S-10$^\circ$N, 50$^\circ$-70$^\circ$E) (dashed lines) in the CPL85 simulation (black), wind stress effect (FULL-STRS) (blue), and the effect in the absence of wind stress and wind speed changes (WIND-CTRL) (red).

5. Analysis of the mixed layer heat budget
  • In this section we focus on analyzing each term of the temperature heat budget and examining their response to pIOD and GW, separately. It turns out from our analysis that their response to both scenarios are very close, though not exactly the same.

  • The vertical advection is the major cooling term over the ETIO region (Figs. 8a), resulting from both wind-induced strong upwelling (Fig. 4e) and large vertical temperature gradients (Fig. 4g). Under both the pIOD and GW cases, the cold vertical advection is significantly enhanced (Figs. 9a and b), due to increased vertical velocity (Figs. 6e and f) and intensified stratification (Figs. 6c and d) resulting from anomalous easterlies along the equator. The anomalous cooling reaches a maximum in July for both pIOD and GW (Figs. 9a and b), about two months earlier than the cooling peak of the MLT. In spite of the above similarities, the overriding experiments reveal a distinction between the two scenarios: the effect in the absence of wind stress and wind speed changes produces a warming anomaly during the pIOD (Fig. 9a) but brings a cooling anomaly under GW (Fig. 9b). This distinction is caused by the opposite response of the stratification to pIOD and GW without the wind-related changes: the upper ocean is less stratified in the former (Fig. 6c) but more stratified in the latter (Fig. 6d).

    On the contrary, over the WTIO region, the cold vertical advection is weakened and the warming anomaly reaches a maximum in November for both pIOD and GW (Figs. 9a and b). However, the overriding experiments reveal that the w/o WS & WES effect acts to cool the surface layer, with the cooling being more significant in the case of GW than pIOD (Figs. 9a and b).

  • The zonal advection is a cooling resource to the surface layer around the equator, but not the far eastern and western tropical regions where it is a warming term (Fig. 8c). Under the pIOD, the change in the zonal advection tends to have a pattern of cold-getting-colder and warm-getting-warmer (Fig. 8c), i.e., its contribution is to further cool the central equator and further warm both the far eastern and western tropical regions. The GW-induced zonal advection bears a similar pattern of change, although the cooling around the central equator is not so significant as for the case of pIOD (Fig. 8d) because of weaker anomalous easterlies under GW (compare Fig. 4d to Fig. 4c). For the ETIO as a whole, the response of the zonal advection to pIOD is a cooling during its peak season and then a warming afterwards (Fig. 9c), while the response to GW tends to warm the region during September-December (Fig. 9d). Over the WTIO, the change in the zonal advection is similar between the pIOD and GW, i.e., a warming anomaly during May-November and cooling afterwards (Figs. 9c and d). The overriding experiments indicate that the above changes for both cases are due to the wind stress effect (Figs. 9c and d).

  • The meridional advection overall is a warming term in the tropical Indian Ocean (Fig. 8e). Under both the pIOD and GW, its warming effect is enhanced north of the equator but reduced south of the equator (Figs. 8e and f). Over the ETIO, the reduction appears to be most significant during the pIOD peak season, due to the wind stress change for both pIOD and GW (Figs. 9e and f). Over the WTIO, the change in the meridional advection appears to be secondary in both cases (Figs. 9e and f).

  • The net surface heat flux H is the major heating term for the tropical Indian Ocean (Fig. 8g). During the pIOD, the heating increases over the ETIO but decreases over the WTIO, i.e., its change tends to damp the formation of pIOD (Figs. 8g and 9g). Under GW (Fig. 8h and 9h), its changing pattern is similar to that during the pIOD, except the weaker heating anomaly over the ETIO. In addition, the overriding experiments reveal that it is the wind stress effect that plays a dominant role for its seasonal evolution (Figs. 9g and h), verifying that the Bjerknes feedback is at work in both the pIOD and GW cases.

  • Derived as the residual of the thermodynamic equation, the diffusion term is a heating effect at the equatorial Indian Ocean, with a maximum over the ETIO (Fig. 8i). In both the pIOD and GW cases, the diffusive heating is enhanced in the ETIO, compensating the vertical advective cooling there (Figs. 9i and j). This change may be explained as follows: The pattern of temperature change indicates that the ocean stability in the upper layer of the ETIO is increased (Fig. 7). This suppresses the vertical diffusivity through a Richardson number-dependent parameterization of the vertical diffusivity (Pacanowski and Philander, 1981) and, in turn, the cold diffusive flux and entrainment, resulting in an anomalous diffusive warming (e.g., Yang et al., 2009). Seasonally, the diffusive heating reaches a maximum during July and this variation is due mainly to the wind stress effect for both pIOD and GW (Figs. 9i and j).

6. Conclusions and discussion
  • It has been reported that GW induces a pIOD-like response in the tropical Indian Ocean, with features such as reduction in the strength of equatorial winds, increased warming in the WTIO, and decreased warming in the ETIO accompanied by a shoaling of the thermocline. By employing the coupled CESM and the ocean-alone POP2, this study investigates the similarity and difference of the formation mechanisms for the changes in the tropical Indian Ocean during the pIOD versus GW. In addition, an overriding technique is employed as a diagnostic tool to isolate and evaluate the role of wind changes in the robust features of the tropical Indian Ocean. The overriding technique enables an isolation of individual feedbacks (e.g., the wind-thermocline-SST feedback) from other factors (Lu and Zhao, 2012; Luo et al., 2014).

    Results show that the formation processes and the related seasonality are quite similar between the internal pIOD and GW. In particular, the wind-thermocline-SST feedback is the leading mechanism in producing the anomalous cooling over the ETIO in both cases. Nevertheless, some differences are found between them and are summarized as follows:

    • Although the total effect of vertical advection is a cooling over the ETIO during both pIOD and GW, the cooling in the pIOD is dominated by the vertical velocity change while the cooling in the GW is dominated by the stratification change.

    • The overriding experiments reveal that, over the ETIO, the contribution from the effect without the wind changes to the stratification is opposite: the upper ocean is less stratified and thus has a warming effect during the pIOD, but it is more stratified and thus has a cooling effect under GW.

    • GW induces a regional surface cooling (i.e., a minimum warming) over the southeast tropics. This is because the anomalous atmospheric heat flux, which warms the surface ocean during the pIOD, is significantly reduced under GW.

    To validate the robustness of the results presented from our local CESM run (i.e., CPL85), three members of RCP8.5 simulations with CESM are obtained from NCAR. A comparison of the surface and subsurface maps of various variables (not shown) reveals that GW-induced features over the tropical Indian Ocean from the ensemble simulations are reproduced well by the local run, suggesting that our modeling approach is reliable for examining the oceanic response in the tropical Indian Ocean to GW.

    The result that the WES feedback on the changes in the tropical Indian Ocean is negligible should be taken with caution, since prescribing the atmospheric conditions in the ocean-alone model compromises the full WES effect, which can in turn feed back to the atmosphere. Further experiments with CESM in partially coupled settings are underway to tease out the specific effects of WES in the SST response of the tropical Indian Ocean to GW.




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