Mean radiosonde soundings for the Australian monsoon/cyclone season (original) (raw)
Related papers
Simulations of observed interannual variability of tropical cyclone formation east of Australia
Atmospheric Science Letters, 2003
A modelling system comprising a regional climate model nested within a GCM is used to simulate the observed interannual variability of tropical cyclone formation off the east coast of Australia. The model's interannual variability of cyclone formation is weaker than that observed, with shortcomings in the model's simulation of vertical wind shear the likely cause.
Interannual Variability of Northwest Australian Tropical Cyclones
Journal of Climate, 2010
Tropical cyclone (TC) activity over the southeast Indian Ocean has been studied far less than other TC basins, such as the North Atlantic and northwest Pacific. The authors examine the interannual TC variability of the northwest Australian (NWAUS) subbasin (0°–35°S, 105°–135°E), using an Australian TC dataset for the 39-yr period of 1970–2008. Thirteen TC metrics are assessed, with emphasis on annual TC frequencies and total TC days. Major findings are that for the NWAUS subbasin, there are annual means of 5.6 TCs and 42.4 TC days, with corresponding small standard deviations of 2.3 storms and 20.0 days. For intense TCs (WMO category 3 and higher), the annual mean TC frequency is 3.0, with a standard deviation of 1.6, and the annual average intense TC days is 7.6 days, with a standard deviation of 4.5 days. There are no significant linear trends in either mean annual TC frequencies or TC days. Notably, all 13 variability metrics show no trends over the 39-yr period and are less depe...
Climate Dynamics, 2004
Fine-resolution regional climate simulations of tropical cyclones (TCs) are performed over the eastern Australian region. The horizontal resolution (30 km) is fine enough that a good climatological simulation of observed tropical cyclone formation is obtained using the observed tropical cyclone lower wind speed threshold (17 m s-1). This simulation is performed without the insertion of artificial vortices (''bogussing''). The simulated occurrence of cyclones, measured in numbers of days of cyclone activity, is slightly greater than observed. While the model-simulated distribution of central pressures resembles that observed, simulated wind speeds are generally rather lower, due to weaker than observed pressure gradients close to the centres of the simulated storms. Simulations of the effect of climate change are performed. Under enhanced greenhouse conditions, simulated numbers of TCs do not change very much compared with those simulated for the current climate, nor do regions of occurrence. There is a 56% increase in the number of simulated storms with maximum winds greater than 30 m s-1 (alternatively, a 26% increase in the number of storms with central pressures less than 970 hPa). In addition, there is an increase in the number of intense storms simulated south of 30°S. This increase in simulated maximum storm intensity is consistent with previous studies of the impact of climate change on tropical cyclone wind speeds.
Journal of Climate, 2008
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 ...
Northwest Australian tropical cyclones: Variability and seasonal prediction
2009
Global teleconnections, involving geopotential height, air temperature, and sea surface temperature, are found for the interannual variability of tropical cyclone (TC) activity in Northwest-Australian (NWAUS) basin of the Southeast Indian Ocean (105--135°E). The NWAUS basin averages 5.5 TCs per year, 42 TC days, and 3 TC landfalls. Additionally, a wavelet analysis yields wavelet power maximum in the 4--6 year and the decadal time periods for both yearly TC frequency and TC days. To identify significant correlates, the global atmospheric and oceanic parameters mentioned above were correlated with the TC frequency and TC days from the Woodside Petroleum Ltd. TC data set. Large correlations were obtained between the NWAUS TC frequency and the following variables: Apr--Jun 700-hPa geopotential heights over North America (r ˜ --0.64), May--Jul 850-hPa geopotential heights over the south Indian Ocean (r ˜ 0.60), May--Jul 850-hPa air temperature (r ˜ --0.63), Jun--Aug 925-hPa geopotential heights over the south Atlantic Ocean (r ˜ -0.65), and Jun--Aug 925-hPa geopotential heights over the Eastern Pacific Ocean (r ˜ --0.59). The collinearity among the five correlates are generally |r| < 0.4. Additionally, large correlations were obtained between the NWAUS TC days and the following variables: Jan--Mar 100-hPa v-component of the wind over the Southern Pacific Ocean (r ˜ 0.52), Apr-Jun 850-hPa geopotential heights over North America (r ˜ --0.58), and Jul--Sep 1000-hPa geopotential heights over the South Altanic Ocean (r ˜ --0.7). These variables can be utilized as seasonal predictors for the upcoming TC season in terms of frequency and days with a lead-time of at least three months for TC frequency and two months for TC days. This set of seasonal predictors includes, intra-basin, inter-basin, and cross-hemispheric regions, unlike previous Australian TC activity studies, which stress the primacy of ENSO. Here it is noted that the traditional Nino 3.4 and Nino 4 regions were not highly correlated with the NWAUS TC activity (| r| < 0.5). No local predictors based on SST, geopotential height, or air temperature resulted from the correlation analysis. The predictors are used in a multiple linear regression model for forecasting the coming seasons number of TCs and TC days. Finally, both prediction schemes are then compared to forecasts made using persistence, climatology, and random forecasts to determine if they perform better than these reference forecasts.
Tropical cyclone trends in the Australian region
Geochemistry, Geophysics, Geosystems, 2008
Tropical cyclone trends in the Australian region are examined using the Bureau of Meteorology best track data. Here the focus is on analyzing differences in trends between the eastern and western subregions of the Australian formation region, under the assumption that any spurious trends in the best track data due to changes in observational practices would be less noticeable in differences between two adjacent portions. Substantial differences in trends are found between the two subregions, with the number, average maximum intensity, and duration at the severe category intensities of tropical cyclones increasing since 1980 in the west but decreasing (in number) or exhibiting no trend (in intensity, severe category duration) in the east. Analyses of trends in atmospheric variables known to be related to tropical cyclone characteristics also indicate substantial differences between the two subregions.
Monthly Weather Review, 2010
This study investigates the impact of atmosphere–ocean coupling on predicted tropical cyclone (TC) intensity change and the ocean response in the Australian region. The coupled model comprises the Australian Bureau of Meteorology’s Tropical Cyclone Limited-Area Prediction System (TC-LAPS) and a regional version of the BLUElink ocean forecasting system. A series of case study forecasts are presented and the differences between coupled and uncoupled forecasts, operational forecasts, and posterior objective analyses are compared. A coupled model ensemble is also developed that uses different first-order approximations of the effects of surface waves on surface stress in an inertial coupling method. In each of the cases, the use of reanalyzed sea surface temperatures significantly improves the prediction of TC intensity change in the intensification phase. The results show that dynamic air–sea coupling has a modest impact on intensity in cases where SST cooling is significant and is lik...
Tropical cyclones in the Australian/southwest Pacific region
1983
Some results are presented from the completed first stage of a collaborative Colorado State University/Australian Bureau of Meteorology project to investigate various aspects of tropical cyclones in the Australian/southwest Pacific region. We begin with a brief description of ...