contact: Gaël Aloryphone: (03) 6232 5399email: gael.alory@csiro.au

Temperature trends in the Indian Ocean: observations vs. modelsObservations show a warming of the Sea Surface Temperature (SST) in the tropical Indian Ocean over 1960-1999, of more than 0.5°C along the equator (fig. 1a). All climate models with radiative forcing, including enhanced greenhouse gases concentration, reproduce a surface warming. It is particularly realistic in the CNRM simulation. Despite a mean cold bias, this model has an equatorial SST trend near the upper range of observations (fig. 1b). A similar trend is found when the simulated temperature is averaged over the upper 50 m or in the mixed layer.

In subsurface, the Indian Ocean Thermal Archive (IOTA) –a new compilation of temperature profiles– shows a cooling trend in the thermocline, located around the 20°C isotherm (fig. 2a). This cooling corresponds to a shallowing of the thermocline, already observed in the western Pacific and related to a decrease in Pacific trade winds, probably transmitted to the Indian Ocean through

the Indonesian Throughflow [1, 2]. Only half of the models reproduce a subsurface cooling, among them the CNRM model. Horizontally averaged over the equatorial band and compared to observations, the temperature trends in this model are characterised by a shallower subsurface cooling and larger surface warming, but a similar upper heat content warming, so the model could be a useful tool to understand the observed changes (fig. 2b).

Heat fluxes and mixed layer depth influence on SSTThe net atmospheric heat flux is maximum along the equator (fig. 3a) and mostly acts over the oceanic mixed layer, around 40 m deep in this region (fig. 3b). Both NCEP and ERA40 atmospheric reanalyses suggest a decrease in the heat fluxes of the equatorial Indian Ocean over the last 40 years, also found in some models including CNRM (fig. 3c). Heat fluxes are thus unlikely to explain the SST warming, which points at an oceanic mechanism. A shallowing mixed layer could contribute to warming by trapping heat fluxes in a thinner layer. The mixed layer slightly shallows in CNRM but a simple ratio suggests the effect is too weak to counteract the heat flux trend (fig. 3d).

Acknowledgements

We thank the modeling groups for providing their data and the PCMDI for archiving and making them available, and especially Davis Salas at CNRM for providing the model original outputs. Thanks to Susan Wijffels for preprocessing the IOTA data. NCEP and ERA40 reanalysis data were retrieved from the NOAA/CDC and ECMWF data center respectively. HADISST data were retrieved from the UK Met Office, Hadley Centre.

Gaël Alory, Gary Meyers

CSIRO Marine and Atmospheric Research •Wealth from Oceans National Research Flagship •

Western Australian Marine Science Institution •

References

1 Vecchi, G. A., B. J. Soden, A. T. Wittenberg, I. M. Held, A. Leetmaa, and M. J. Harrison (2006), Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing, Nature, 441, 73-76.

2 Alory, G., S. Wijffels, and G. Meyers (2007), Observed temperature trends in the Indian Ocean over 1960-1999 and associated mechanisms, Geophys. Res. Lett., 34, L02606.

3 Liu, Z., and B. Huang (2000), Cause of tropical Pacific warming trend, Geophys. Res. Lett., 27 (13), 1935-1938.

Figure 1: (a) Linear trend (colour scale) and mean (contours) in SST from observations (first row) and climate models, (b) SST time series and trend values averaged over the equatorial Indian Ocean (9°S-6°N) for observations and CNRM model.

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Figure 2: (a) Linear trend (colour scale) and mean (contours) in equatorial Indian Ocean temperature from IOTA observations and climate models in longitude-depth coordinates, (b) Linear trend in equatorial Indian Ocean temperature from observations and CNRM model as a function of depth.

What we did

A set of 12 climate model simulations of ocean temperature is compared to the observed surface warming in the equatorial Indian Ocean. The most realistic model is selected to investigate the mechanisms responsible for the changes, through a tentative heat budget.

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Figure 3: Mean (a) net heat flux and (b) mixed layer depth for CNRM model (1960-1999), (c) Mean and trend of net heat flux over the equatorial Indian Ocean for NCEP/ERA 40 atmospheric reanalyses and climate models, (d) Surface heat flux (left), mixed layer depth (middle) and heat term due to penetration of heat flux in the mixed layer (left) in the equatorial Indian Ocean in CNRM model.

Figure 4: (a) Year-to-year variations of 0-50 m equatorial Indian Ocean temperature and contributing heat terms in CNRM model, (b) Integration from SST annual variations as expressed in the heat budget equation (left) to SST (right).

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What we found

Climate models generally reproduce the surface warming of the equatorial Indian Ocean. The CNRM model furthermore reproduces the observed subsurface cooling and decrease in surface heat fluxes. Decreasing heat fluxes suggest an oceanic origin to the SST warming, but the thinning of the mixed layer is too small to play a role. The heat budget analysis cautions against a direct linkage between the long-term trend of heat terms and the SST warming. The exact closure of the heat budget is a preliminary condition which cannot be met with monthly model outputs, and requires online computation of heat terms during the simulation.

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Heat budget in the upper (0-50 m) equatorial Indian OceanThe heat budget in CNRM in a 9°S to 6°N, 0 to h=50 m box is formulated as:

which respectively includes heat fluxes, meridional/vertical advection and a residual term. The mean value of the different heat terms shows that the warming due to heat fluxes is partly balanced by cooling through vertical advection, while meridional advection has only a slight warming effect (fig. 4a). The sum of these 3 terms reproduces the interannual temperature variations very well. However the heat budget is not closed with a residual term of about 1°C.yr-1, preventing further study of the mechanisms responsible for the SST trend.

This heat budget has been computed from the monthly-averaged simulated variables, the only outputs generally available from climate change models. The residual term includes diffusion, whose explicit calculation (Kz∂T/∂z) needs to be done at each model time step, especially near the mixed layer depth. Advection being also a product, its calculation at monthly timescale is an approximation. To close the multidecadal heat budget, it is thus necessary to compute the different heat terms at each model time step. It is all the more important as the heat budget equation reveals that the long-term average of the different heat terms, rather than their trend, is the main contributor to SST trend (fig. 4b). Hence an interpretation based on trends only is incorrect [3].

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