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The South Pacific Convergence Zone: A Real "Swinger" Under the Influence of CO2?

Cai, W., Langaigne, M., Borlace, S., Collins, M., Cowan, T., McPhadden, M.J., Timmermann, A., Power, S., Brown, J., Menkes, C., Ngari, A., Vincent, E.M. and Widlansky, M.J. 2012. More extreme swings of the South Pacific Convergence Zone due to greenhouse warming. Nature 488: 365-369.
The South Pacific Convergence Zone (SPCZ) is a permanent feature in the general circulation that stretches southeastward from the equatorial region of the west Pacific into the central mid-latitude Pacific near Polynesia. This band of precipitation has drawn the interest of the climatological community because it behaves like the Intertropical Convergence Zone (ITCZ) in the tropics, but is driven by jet-stream dynamics in the mid-latitudes. Like the ITCZ, it is a locus for the occurrence of precipitation in the regions it impacts. Additionally, there is little consensus in the literature on the future strength and frequency of El Niño occurrences.

Previous research has demonstrated that the observed behavior and location of the SPCZ varies in relation to the phase of El Niño. During an El Niño year, the SPCZ is located further equatorward and can be oriented in a more zonal fashion, and such changes are more robust during stronger El Niño events. Then, Indonesia, Australia, and southwest Pacific nations are subject to drought during such years, and of course these conditions impact the regional ecology.

In a letter to Nature, Cai et al. (2012) compared the larger-scale components of the SPCZ rainfall anomalies derived from observations during the period 1979-2008 to rainfall anomalies generated by 17 CMIP3 General Circulation Model (GCM) simulations. The model simulations covered the period 1891-2000. These simulations included both known natural and anthropogenic forcings. The authors generated 90-year simulations using the A2 greenhouse emission scenarios, which assume business as usual or accelerating greenhouse gas emissions. Cai et al. (2012) also applied the same strategy with a later version of CMIP(5) under the scenario that levels out at 850 ppm during 200 years assuming 1% increases per year until stabilization. This is similar to the A2 scenario.

The work of Cai et al. (2012) demonstrates that stronger SPCZ events will occur with greater frequency in the future under the increased greenhouse gas scenarios in both models (doubled in CMIP3 and tripled in CMIP5). This implies increased frequency of drought for the regions of the southwest Pacific. Both models also imply that stronger El Niño events occur more frequently in the future scenario, but not as great as the increased SPCZ occurrences. Curiously, these results also imply that SPCZ behavior decouples from that of El Niño.

The conclusion that stronger SPCZ events will occur in the future was based on a greenhouse gas emission scenario that is considered quite extreme. Additionally, while there may be a physical reason for future decoupling in the model for the relationship between SPCZ strength and location and the strength of El Niño, it should be noted that the modeled SPCZ orientation seems to be more zonal than observed even before the future scenarios are generated (compare Fig. 1 and Fig 2).

Figure 1. Adapted from Fig. 1 in Cai et al. (2012). The variability of observed rainfall for the a) spatial pattern of the largest-scale component of the observed precipitation anomalies that was filtered out, and b) second-largest component of the observed anomalies extracted from the satellite-era rainfall anomaly data (mm d-1) (Global Precipitation Climatology Project version 225) focusing on the western South Pacific during the austral summer (December to February). The first (second) principal patterns account for 47% (16%) of the total variance. The SPCZ position (max rainfall greater than 6mm d-1) for El Niño (green line), La Niña (blue line) and neutral (black line) states is superimposed in a, and the position for zonal SPCZ events (red line) in b. Cold (warm) contours indicate increased (decreased) rainfall per one standard deviation (s.d.) change.

Figure 2. As in Fig. 1, except for the CMIP model runs.

Additionally, the authors admit to some uncertainty in the observed SPCZ position, stating that "although the simulated frequency in the control period is comparable to the observed frequency, the latter is based on observations over some three decades and may carry a large uncertainty." Like many modeling studies, therefore, the outcome of Cai et al. (2012) is simply just a scenario based on a specific set of assumptions, and with limitations on the ability to capture the phenomenon in question precisely. Thus, their results have only limited scientific value.

Archived 21 August 2012