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Lance M. Leslie, Bruce W. Buckley, and Mark Leplastrier


The preparation of accurate operational weather forecasts and the timely issuance of severe marine weather and ocean warnings and advisories for major oceanic weather systems impacting both coastal areas and the open ocean are major forecasting problems facing the Australian Bureau of Meteorology’s Regional Forecast Centre (RFC) and its collocated Tropical Cyclone Warning Centre (TCWC) in Perth, Western Australia. The region of responsibility for the Perth RFC is vast, covering a large portion of the southeast Indian and Southern Oceans, both of which are extremely data sparse, especially for near-surface marine wind data. Given that these coastline and open-ocean areas are subject to some of the world’s most intense tropical cyclones, rapidly intensifying midlatitude cyclones, and powerful cold fronts, there is now a heavy reliance upon NASA Quick Scatterometer (QuikSCAT) data for both routine and severe weather warning forecasts.

The focus of this note is on the role of QuikSCAT data in the Perth RFC for the accurate and early detection of maritime severe weather systems, both tropical and extratropical. First, the role of QuikSCAT data is described, and then three cases are presented in which the QuikSCAT data were pivotal in providing forecast guidance. The cases are a severe tropical cyclone in its development phase off the northwest coast of Australia, a strong southeast Indian Ocean cold front, and an explosively developing midlatitude Southern Ocean cyclone. In each case, the Perth RFC would have been unable to provide early and high-quality operational forecast and warning guidance without the timely availability of the QuikSCAT surface wind data.

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Hamish A. Ramsay, Lance M. Leslie, Peter J. Lamb, Michael B. Richman, and Mark Leplastrier


This study investigates the role of large-scale environmental factors, notably sea surface temperature (SST), low-level relative vorticity, and deep-tropospheric vertical wind shear, in the interannual variability of November–April tropical cyclone (TC) activity in the Australian region. Extensive correlation analyses were carried out between TC frequency and intensity and the aforementioned large-scale parameters, using TC data for 1970–2006 from the official Australian TC dataset. Large correlations were found between the seasonal number of TCs and SST in the Niño-3.4 and Niño-4 regions. These correlations were greatest (−0.73) during August–October, immediately preceding the Australian TC season. The correlations remain almost unchanged for the July–September period and therefore can be viewed as potential seasonal predictors of the forthcoming TC season. In contrast, only weak correlations (<+0.37) were found with the local SST in the region north of Australia where many TCs originate; these were reduced almost to zero when the ENSO component of the SST was removed by partial correlation analysis. The annual frequency of TCs was found to be strongly correlated with 850-hPa relative vorticity and vertical shear of the zonal wind over the main genesis areas of the Australian region. Furthermore, correlations between the Niño SST and these two atmospheric parameters exhibited a strong link between the Australian region and the Niño-3.4 SST. A principal component analysis of the SST dataset revealed two main modes of Pacific Ocean SST variability that match very closely with the basinwide patterns of correlations between SST and TC frequencies. Finally, it is shown that the correlations can be increased markedly (e.g., from −0.73 to −0.80 for the August–October period) by a weighted combination of SST time series from weakly correlated regions.

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