Spectral Content of Temperature Variability

To reveal the spatial characteristics of temperature variability along IX1 and PX2, total variance was binned into four broad spectral bands: for periods less than 0.4 years (intraseasonal/mesoscale); periods between 0.4 and 1.1 years (seasonal); periods between 1.1 and 3.2 years (quasi-biennial

(QB) band); and for periods greater than 3.2 years (ENSO band). The model data were detrended prior to calculating the variances. The variance in each spectral band is shown as a percentage of the total mapped variance in Figs. 8 and 9.

Eddy energy is only partially suppressed by the mapping scales used to average the XBT data, and we find that observed intraseasonal energy accounts for typically 10-20% of the total mapped observed temperature variance in two regions along IX1 (Fig. 8a): off the coast of western Australia where the IX1 line intersects the eddy field associated with the Leeuwin Current and between 13°S and 8°S along the axis of the South Equatorial Current, where strong intraseasonal eddies develop as a result of an instability of the current at its seasonal maximum (Feng and Wijffels, 2001). Intraseasonal variability in the model along the Australian coast (Fig. 8e) is less than 10% along most of IX1 with a maximum of about 20% along the coast of Java, which is still significantly weaker than in the observations (up to 40%).

The observed seasonal band (Fig. 8b), which includes both the annual and semiannual frequencies, dominates SST and variability in the seasonal thermocline. The depth penetration of the seasonal thermocline clearly increases to the south along with the strength of the seasonal heating/cooling cycle. This feature is quite accurately reproduced by the model (Fig. 8f). Dominant seasonal variation is also evident in the observations throughout the water column between 12°S and 20°S (Fig. 8b); this is the forced annual Rossby wave described by Masumoto and Meyers (1998), which is primarily driven by local wind-stress curls, and associated Ekman pumping and Rossby wave propagation. Although the model also shows increased seasonal variability between 12°S and 20°S (Fig. 8f), it lacks the coherent signal across the whole latitude band between 12°S and 20°S in the observations.

Off the coast of Java, the relative importance of the observed and simulated seasonal cycle in temperature variability is largest in a narrow region trapped at the coast below 100 m and extending to 750 m (Fig. 8b, f). This signal is in response to the semiannual Kelvin waves excited in the equatorial Indian Ocean. Interestingly, both observed and simulated coastal SST and temperature variability above 100 m off Java largely occur in the QB and ENSO bands (Fig. 8c, d, g, h). Variance in the QB band occurs in the Java mixed layer and upper thermocline and extends further offshore at depth than the seasonal variability (Fig. 8c, g). Off Australia, the simulated and observed ENSO band accounts for 30-40% of the total variability in the upper thermocline.

Along PX2, the observed intraseasonal band has little energy due to the longer averaging times (e-folding scale of 30 days) needed to grid this more sparsely sampled and noisy section (Fig. 9a). Similar to IX1, the model shows weaker than observed intraseasonal variability along this section (Fig. 9d). Seasonal variations dominate observed and, to a lesser extent,

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Figure 8: The percentage of mapped temperature variance in four spectral bands along IX1 for observations (upper half) and model (lower half) for 1992—2000 period: (a, e) intraseasonal (periods >0.4 years), (b, f) seasonal (periods between 0.4 and 1.1 years), (c, g) biennial band (periods between 1.1 and 3.2 years), and (d, h) interannual (periods longer than 3.2 years).

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4 Variance T > 3.2 years

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120 125 130 Longitude

120 125 130 Longitude

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Variance T > 3.2 years

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120 125 130 Longitude

120 125 130 Longitude

simulated temperature variability above and below the main thermocline and at the Arafura shelf break (Fig. 9b, f). Both observations and model show a decrease in strength of the seasonal signal in SST from the Arafura to the Java shelf break. Within the thermocline, QB and ENSO band variability dominate (Fig. 9c, d, g, h). The QB variability also contributes significantly below the thermocline. For seasonal and longer timescales the model simulates the observed structures with reasonable accuracy, though the responses occur at deeper depths than observed.

Ray theory explains the results shown in Figs. 5 and 8 where annual and semiannual energy dominates subthermocline depths off Sunda Strait, while ENSO-band variability is confined to the upper thermocline. Simple ray-tracing theory (following Kessler and McCreary, 1993) along the equatorial and coastal wave guides, starting at the thermocline depth of 100 m at 60°E (mid-Indian basin), suggests semiannual energy will dive to below 300 m off Sunda, only to 200 m depth for annual frequencies and barely to 120 m for the ENSO band (5 years). Waves originating at 170°W in the equatorial Pacific can dive to well below 1,000 m for the semiannual, to 300 m for the annual and barely to 130 m for the ENSO band. Thus the upward propagating annual wave seen off the Arafura shelf break (Fig. 7) is remotely forced in the central Pacific. However, a discrepancy in the linear ray theory is the thermocline response off the western Australian coastline, which extends to 300 m depth (Fig. 4), and therefore much deeper than the ray paths suggest was possible. Likely, the energy is following the thermocline as it deepens poleward (Wijffels and Meyers, 2004).

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