10 Influences of large scale climate modes and agulhas system variability on the BCLME region

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Summary This chapter has reviewed the major large scale modes that exist in the South Atlantic as well as those external to the region such as ENSO and the Antarctic Oscillation that may influence the BCLME region. Most attention has been paid to the Benguela Nino which is the most well known and dominant mode in the South East Atlantic. In addition to these large scale modes, the highly variable southern Agulhas Current also influences at least the southern part of the BCLME region. Some of the Agulhas Current variability develops locally due to instability processes but at least part may be linked to that evolving in the tropical Indian Ocean. Although the most recognizable feature of the BCLME region is its upwelling, the strength and timing of this process and its related SST expression is modulated by ENSO and likely also by other large-scale modes of variability. In the north of the BCLME region, the Benguela Nino impacts on the Angola—Benguela frontal zone and on SST to as far south as about 25°S. The proximity of the BCLME region to the Southern Ocean and the South West Indian Ocean, due to the termination of Africa in the sub-tropics, means that the Benguela upwelling system tends to display greater variability than do the Humboldt, Canary or California Current upwelling systems. Better understanding of this variability is fundamental for assessing its potential predictability and for developing appropriate management strategies of its rich ecosystems. A concern is the relative sparseness of in situ observations in the region. These include not only ocean data but also land surface and atmospheric data which, amoungst other applications, are needed to improve the reliability of the NCEP re-analyses often used to diagnose modes of variability over the region. In particular, prediction efforts for the region are significantly hindered by a lack of data with which to validate model outputs. Close collaboration between the observing system and modelling communities is therefore needed in order to make progress on better understanding the variability of the BCLME region and working towards prediction.