Australian Tropical Cyclone Research Articles

Coastal Inundation Hazard Assessment in Australian Tropical Cyclone Prone Regions

One of the hazards associated with tropical cyclones (TCs) is a storm surge, which leads to coastal inundation and often results in loss of life and damage to infrastructure. In this study, we used GIS-based bathtub models and tide-gauge-derived water levels to assess coastal inundation scenarios for the landfall region of TC Debbie. The three scenarios modelled what could have happened if the TC’s maximum storm surge had coincided with the maximum storm tide for that day, month, or TC season, where the water levels were determined through analysis of tide gauge data, using a new method called the variable enhanced Bathtub Model. Additionally, this study analysed the impact of excluding the correction of water levels with the Australian Height Datum. Our study found that between the least and most severe scenarios, with the input water-level difference for the model along the coastline being 0.43 m, the observed inundation depth of the analysed populated region increased from 0.25 m to 1 m. Ultimately, it was found that in the worst-case scenario, the study region could have experienced coastal inundation 0.63 m higher than it did, inundating 72.53 km2 of the coast. The results of this study support the consensus that coastal inundation is highly dependent on the characteristics of the terrain, and that coastal inundation modelling, such as that completed in this study, needs to be performed to better inform decision makers and communities of the potential impacts of TC-induced storm surges.

Sensitivity of northwest Australian tropical cyclone activity to ITCZ migration since 500 CE.

Tropical cyclones (TCs) regularly form in association with the intertropical convergence zone (ITCZ), and thus, its positioning has implications for global TC activity. While the poleward extent of the ITCZ has varied markedly over past centuries, the sensitivity with which TCs responded remains poorly understood from the proxy record, particularly in the Southern Hemisphere. Here, we present a high-resolution, composite stalagmite record of ITCZ migrations over tropical Australia for the past 1500 years. When integrated with a TC reconstruction from the Australian subtropics, this time series, along with downscaled climate model simulations, provides an unprecedented examination of the dependence of subtropical TC activity on meridional shifts in the ITCZ. TCs tracked the ITCZ at multidecadal to centennial scales, with a more southward position enhancing TC-derived rainfall in the subtropics. TCs may play an increasingly important role in Western Australia's moisture budgets as subtropical aridity increases due to anthropogenic warming.

Automated Analysis of Australian Tropical Cyclones with Regression, Clustering and Convolutional Neural Network

Tropical cyclones take precious lives, damage critical infrastructure, and cause economic losses worth billions of dollars in Australia. To reduce the detrimental effect of cyclones, a comprehensive understanding of cyclones using artificial intelligence (AI) is crucial. Although event records on Australian tropical cyclones have been documented over the last 4 decades, deep learning studies on these events have not been reported. This paper presents automated AI-based regression, anomaly detection, and clustering techniques on the largest available cyclone repository covering 28,713 records with almost 80 cyclone-related parameters from 17 January 1907 to 11 May 2022. Experimentation with both linear and logistic regression on this dataset resulted in 33 critical insights on factors influencing the central pressure of cyclones. Moreover, automated clustering determined four different clusters highlighting the conditions for low central pressure. Anomaly detection at 70% sensitivity identified 12 anomalies and explained the root causes of these anomalies. This study also projected parameterization and fine-tuning of AI-algorithms at different sensitivity levels. Most importantly, we mathematically evaluated robustness by supporting an enormous scenario space of 4.737 × 108234. A disaster strategist or researcher can use the deployed system in iOS, Android, or Windows platforms to make evidence-based policy decisions on Australian tropical cyclones.

Using historical tropical cyclone climate datasets to examine wind speed recurrence for coastal Australia

Likelihood estimates of extreme winds, including those from tropical cyclones (TCs) at certain locations are used to inform wind load standards for structural design. Here, wind speed average recurrence intervals (ARIs) determined from TC climate data dating back to the 1970s in two quantile–quantile adjusted reanalysis datasets (ERA5 and BARRA [1990]), and best-track observations for context, were compared with Standardized ARIs (AS/NZS) across seven tropical and two subtropical Australian inland coastal regions. The novelty of this work lies in determining TC-wind speed ARIs from a range of datasets that are not typically used to evaluate this metric. Inherent differences between the data used to determine the Standard ARIs (large sample size allow for larger extrapolations; GEV function) and TC data ARIs (smaller sample size and less certain data; the more asymptotic Lognormal/Weibull functions are used) led to the use of different extreme value functions. Results indicated that although these are two distinct ways of determining design wind speeds, when they are considered equivalent, there was a moderate reproduction of the ARI curves with respect to the Standard in both reanalysis datasets, suggesting that similar analyses using climate model products can provide useful information on these types of metrics with some caveats. Trends in TC wind strength affecting coastal Australia were also analyzed, indicating a potential slight downtrend in tropical West coast TC wind strength and slight uptrend for tropical East coast TC wind strength, noting considerable uncertainty given the short time period and limitations of data quality including over longer time periods. Such trends are not only limited to the relationship between TC intensity and anthropogenic warming, but also to regional changes in TC frequency and track direction. This could lead to significant trends emerging in regional Australian TC wind gust strength before several decades of warming have occurred. It is hoped that climate models can provide both longer-term and a more homogenous base for these types of evaluations and subsequent projections with respect to climate change simulations.

Revisions to the Australian tropical cyclone best track database

The Australian tropical cyclone (TC) best track database (BT) maintained by the Bureau of Meteorology has records since 1909 of varying quality and completeness. Since 2005 a series of efforts to improve the database have included: removing internal inconsistencies, adding fixes, and identifying errors using comparisons with other datasets; upgrading intensity information since 1973 including adding maximum winds (Vm) prior to 1984–85, rederiving Dvorak Current Intensity numbers from archived material and accounting for different wind–pressure relationships used; a partial reanalysis of satellite imagery including microwave imagery using the HURSAT dataset since 1987; and considering an objective intensity dataset. The BT homogeneity is reviewed in the context of improvements in satellite technology, observational coverage, scientific developments, BT procedures and the subjective variation between analysts across time and offices. The scale of these variances is greatest in the early stages prior to 1981 in the absence of geostationary satellite imagery until 1978, satellite calibration issues from 1978–80 and prior to the introduction of the enhanced infra-red Dvorak technique in 1981. The current era since 2003 is considered to be the most accurate, comprehensive and homogeneous corresponding to the expansion of the TC database to include the current suite of fields; the application of microwave and scatterometry imagery; greater standardisation of BT practices and slight changes in the application of the Dvorak technique. These improvements have generated a more consistent dataset that could be used for weather and climate research and other TC-related work.

Weather systems and extreme rainfall generation in the 2019 north Queensland floods compared with historical north Queensland record floods

Earlier papers have addressed floods from warm-air advection (WAA) in southeast Australia and around the globe, and extreme rainfall in US hurricanes and Australian tropical cyclones (TCs). This is the first paper to address the WAA phenomena in causing monsoon and TC floods and in TC-like systems which develop over the interior of northern Australia. The inland events help explain Australia’s worst tropical flooding disaster in 1916. A disastrous series of floods during late January and early February 2019 caused widespread damage in tropical north Queensland both in inland regions and along the coast. This occurred when some large-scale climate influences, including the sea surface temperatures suggested conditions would not lead to major flooding. Therefore, it is important to focus on the weather systems to understand the processes that resulted in the extreme rainfall responsible for the flooding. The structure of weather systems in most areas involved a pattern in which the winds turned in an anticyclonic sense as they ascended from the low to middle levels of the atmosphere (often referred to as WAA) which was maintained over large areas for 11 days. HYSPLIT air parcel trajectory observations were employed to confirm these ascent analyses. Examination of a period during which the heaviest rain was reported and compared with climatology showed a much stronger monsoon circulation, widespread WAA through tropical Queensland where normally its descending equivalent of cold-air advection is found, and higher mean sea level pressures along the south Queensland coast. The monsoon low was located between strong deep monsoon westerlies to the north and strong deep easterlies to the south which ensured its slow movement. This non-TC event produced heavy inland rainfall. Extreme inland rainfall is rare in this region. Dare et al. (2012), using data from 1969/70 to 2009/10, showed that over north Queensland non-TC events produced a large percentage of the total rainfall. The vertical structure associated with one of the earlier events that occurred in 2008 had sufficient data to detect strong and widespread WAA overlying an onshore moist tropical airstream. This appears to have played a crucial role in such extreme rainfall extending well inland and perhaps gives insight to the cause of a 1916 flooding disaster at Clermont which claimed around 70 lives. Several other events over the inland Tropics with strong WAA also help explain the 1916 disaster.

Solar forcing over the last 1500 years and Australian tropical cyclone activity

AbstractAccurate seasonal and decadal predictions of tropical cyclone activity are essential for the development of mitigation strategies for the 2.7 billion residents living within cyclone prone regions. The traditional indices (Southern Oscillation Index and various sea surface temperature indices) have fallen short in recent years as seasonal predictors within the Australian region. The short length of these records (i.e., <50 years) has meant that our current knowledge of larger‐scale drivers at interdecadal, centennial, and millennial scales is limited. The development of a new tropical cyclone activity index spanning the last 1500 years has enabled the examination of tropical cyclone climatology at higher temporal resolution than was previously possible. Here we show that in addition to other well‐known climate indices, solar forcing largely drives decadal, interdecadal, and centennial cycles within the tropical cyclone record.

Long‐term changes in Australian tropical cyclone numbers

AbstractTropical cyclone (TC) observations are used to examine changes in the TC climatology of the Australian region. The ability to investigate long‐term changes in TC numbers improves when the El Niño‐Southern Oscillation (ENSO) is considered. Removing variability in TC numbers associated with ENSO shows a significant decreasing trend in TC numbers at the 93–98% confidence level. Additionally, there is some indication of a temporal change in the relationship between ENSO and TC numbers, with ENSO accounting for about 35–50% of the variance in TC numbers during the first half of the study period, but only 10% during the second half.

Australian tropical cyclone activity lower than at any time over the past 550–1,500 years

The assessment of changes in tropical cyclone activity within the context of anthropogenically influenced climate change has been limited by the short temporal resolution of the instrumental tropical cyclone record (less than 50 years). Furthermore, controversy exists regarding the robustness of the observational record, especially before 1990. Here we show, on the basis of a new tropical cyclone activity index (CAI), that the present low levels of storm activity on the mid west and northeast coasts of Australia are unprecedented over the past 550 to 1,500 years. The CAI allows for a direct comparison between the modern instrumental record and long-term palaeotempest (prehistoric tropical cyclone) records derived from the (18)O/(16)O ratio of seasonally accreting carbonate layers of actively growing stalagmites. Our results reveal a repeated multicentennial cycle of tropical cyclone activity, the most recent of which commenced around AD 1700. The present cycle includes a sharp decrease in activity after 1960 in Western Australia. This is in contrast to the increasing frequency and destructiveness of Northern Hemisphere tropical cyclones since 1970 in the Atlantic Ocean and the western North Pacific Ocean. Other studies project a decrease in the frequency of tropical cyclones towards the end of the twenty-first century in the southwest Pacific, southern Indian and Australian regions. Our results, although based on a limited record, suggest that this may be occurring much earlier than expected.

The Different Impact of Positive-Neutral and Negative-Neutral ENSO Regimes on Australian Tropical Cyclones

Abstract The number of tropical cyclones (TCs) in the Australian region exhibits a large variation between different ENSO regimes. While the difference in TC numbers and spatial distribution of genesis locations between the canonical El Niño and La Niña regimes is well known, the authors demonstrate that a statistically significant difference in TC numbers also exists between the recently identified negative-neutral and positive-neutral regimes. Compared to the negative-neutral and La Niña regimes, significantly fewer TCs form in the Australian region during the positive-neutral regime, particularly in the eastern subregion. This difference is attributed to concomitant changes in various large-scale environmental conditions such as sea level pressure, relative vorticity, vertical motion, and sea surface temperature.

Interrelationship between Indian Ocean Dipole (IOD) and Australian Tropical Cyclones

Indian Ocean Dipole (IOD) index plays an important role in shaping the weather conditions in the Indian Ocean and surrounding areas. It has a strong correlation with Darwin pressure. This paper attempts to unfold its relationship with the occurrence of Tropical Cyclones (TCs) in the Australian basin. An analysis of 30 years' data (1976-2006) reveals that individual IOD pole (Western or Eastern) has peak negative correlation (-.5 and -.4, respectively) with the seasonal occurrences of TCs in Australia. Mainly the TC occurrences in Western and Eastern sub-regions are correlated with IOD index of both the poles. Northern sub-region is more or less free from the influence of IOD index. These findings provide further insight in understanding the genesis of tropical cyclones in the Australian region.

Surface pressure profiles, vortex structure and initialization for hurricane prediction. Part II: numerical simulations of track, structure and intensity

In part 1 of this study, an assessment of commonly used surface pressure profiles to represent TC structures was made. Using the Australian tropical cyclone model, the profiles are tested in case studies of high-resolution prediction of track, structure and intensity. We demonstrate that: (1) track forecasts are mostly insensitive to the imposed structure; (2) in some cases [here Katrina (2005)], specification of vortex structure can have a large impact on prediction of structure and intensity; (3) the forecast model mostly preserves the characteristics of the initial structure and so correct structure at t = 0 is a requirement for improved structure forecasting; and (4) skilful prediction of intensity does not guarantee skilful prediction of structure. It is shown that for Ivan (2004) the initial structure from each profile is preserved during the simulations, and that markedly different structures can have similar intensities. Evidence presented suggests that different initial profiles can sometimes change the timing of intensification. Thus, correct initial vortex structure is an essential ingredient for more accurate intensity and structure prediction.

Interannual Variability of Northwest Australian Tropical Cyclones

Abstract 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 dependent upon standard El Niño–Southern Oscillation (ENSO) variables than many other TC basins, including the rest of the Australian region basin. The largest correlations with TC frequency were geopotential heights for June–August at 925 hPa over the South Atlantic Ocean (r = −0.65) and for April–June at 700 hPa over North America (−0.64). For TC days the largest correlations are geopotential heights for July–September at 1000 hPa over the South Atlantic Ocean (−0.7) and for April–June at 850 hPa over North America (−0.58). Last, wavelet analyses of annual TC frequencies and TC days reveal periodicities at ENSO and decadal time scales. However, the TC dataset is too short for conclusive evidence of multidecadal periodicities. Given the large correlations revealed by this study, developing and testing of a multivariate seasonal TC prediction scheme has commenced, with lead times up to 6 months.

The active tropical cyclone season of 2005–2006 over Northwest Australia: Operational model performance and high resolution case studies

There are three main aims of this study. First, the main features of the active 2005–2006 Australian region tropical cyclone (TC) season are summarized, with particular emphasis on the northwest Australian region. Second, an assessment is made of the skill of the available operational global and regional numerical weather prediction (NWP) models for three of the most significant TCs (TCs Clare, Glenda and Hubert), each of which made landfall on the northwest coast of Australia. Third, high-resolution numerical modelling simulations of these same three TCs are described in detail. The numerical weather prediction (NWP) model used here was developed at the University of Oklahoma, and in this study it utilises initial and boundary conditions obtained from archived analyses and forecasts provided by the Australian Bureau of Meteorology, as well as a 4D-Var data assimilation scheme to ingest all available satellite data. The high-resolution numerical model is multiply two-way nested, with the innermost domain having a resolution of 5 km. It was found that unlike the operational models, which were restricted by relatively low resolution and less data, the high resolution model was able to capture most of the major features of all three TC lifecycles including development from initial tropical depressions, intensification, and their tracks, landfall, and associated rainfall and wind fields.

Discussion of “Synthetic Tropical Cyclone Database” by M. K. James and L. B. Mason

The authors present a Monte Carlo technique for generating a database of synthetic tropical cyclone tracks over the Great Barrier Reef Marine Park, situated off the coast of Queensland, Australia. They validate their synthetic tracks by comparing the marginal probability density functions PDFS of various track parameters against the Australian tropical cyclone best-track database Dare and Davidson 2004. They conclude that their synthetic database has statistical properties that are similar to the observational record and that can therefore be used confidently for simulating the climatological probability of occurrence of various aspects of tropical cyclone risk, such as storm surge, waves, and wind. The authors independently model the cyclone east-west x and north-south y components of motion and the intensity change. That is, they assume these variables to be uncorrelated. The discussers will show that this assumption is not supported by the data and that it causes a significant class of storms to be underrepresented in the authors’ synthetic database. The error was not detected by their statistical tests, since they were all tests of the marginal PDFS. The motion components are correlated, and so tests of the joint PDFS would have been more appropriate. The motion of storms within the paper’s three zones, over the same period 1969–2003 according to the Australian best-track database are summarized in Fig 1. It is apparent that the variation of the motion of individual storms about the all-storm mean has a systematic structure. This structure can be summarized by the covariance matrix, plotted in the diagram by an ellipse: here the coordinate rotation that diagonalizes the matrix has been found and the ellipse oriented in this direction, with semimajor and semiminor axes equal to twice the square root of the variances in the rotated covariance matrix. In the northern zone, the mean motion is slow and almost due southward, whereas the covariance ellipse is markedly elongated and oriented almost in the east-west direction, showing that most of the variability in storm motion is in the x-direction and that the x- and y-components of storm motion are not strongly correlated. In the central zone, the mean motion is slightly west of southward and a little faster than in the northern zone. The covariance ellipse is oriented in a northwest-southeast direction, with the ratio of axis lengths equal to 2. The x- and y-components of storm motion are strongly correlated correlation coefficient –0.47 and

The Impact of Observational Technology on Climate Database Quality: Tropical Cyclones in the Tasman Sea

Abstract The recorded climatology of tropical cyclones that affect the Tasman Sea spans the period from 1911 to the present. This climatology is a subset of the much larger Australian Tropical Cyclone database, which is the official record of all tropical cyclones in the Australian area of responsibility. Such a long, detailed record should provide an excellent dataset for regional climate research. However, a detailed analysis of the database has revealed that it must be used with caution over the Tasman Sea, where statistically significant discontinuities are present, greatly reducing its quality and length for climate and climate change studies. Problems with the complete Australian Tropical Cyclone database have been identified and discussed earlier by a number of authors. This study is concerned with two statistically significant discontinuities that occurred in the Tasman Sea portion of the database in the mid-1950s and in 1977. The first discontinuity almost trebled the recorded frequency of tropic...

Interdecadal variability in north-east Australian tropical cyclone formation

Interdecadal variability in north-east Australian regional tropical cyclone formation is investigated. It is found that mean tropical cyclone formation is significantly higher during positive phases of the Interdecadal Pacific Oscillation (IPO) than during negative phases. This is related to changes in vertical wind shear in the north-east Australian region.

A Real-Time System for Forecasting Tropical Cyclone Storm Surges

Abstract The depth-averaged, numerical storm-surge model developed by Hubbert et al. (1990) has been configured to provide a stand-alone system to forecast tropical cyclone storm surges. The atmospheric surface pressure and surface winds are derived from the analytical-empirical model of Holland (1980) and require only cyclone positions, central pressures, and radii of maximum winds. The model has been adapted to run on personal computers in a few minutes so that multiple forecast scenarios can be tested in a forecast office in real time. The storm surge model was tested in hindcast mode on four Australian tropical cyclones. For these case studies the model predicted the sea surface elevations and arrival times of surge peaks accurately, with typical elevation errors of 0.1 to 0.2 m and arrival time errors of no more than 1 h. Second order effects, such as coastally-trapped waves, were also well simulated. The model is now being used by the Australian Tropical Cyclone Warning Centres (TCWC's) for operatio...

Reduction of Tropical Cyclone Position Errors Using an Optimal Combination of Independent Forecasts

Abstract It is shown that an optimal linear combination of independent forecasts of tropical cyclone tracks significantly reduces the mean forecast-position errors. In this study the independent forecasts are provided by a statistical scheme (CLIPER) and a numerical weather prediction (NWP) model operating over the Australian tropics. A comparison is made between the optimal linear combination and four other forecast techniques, over the five Australian tropical cyclone seasons 1984/85–1987/88. The combination method gave a mean position error of 157 km at 24 h using independent “best track” data, an improvement of 15% over the next most accurate method. At 48 h, the mean position error of 312 km was 17% less than the next most accurate scheme. The combination method was assessed further in a real-time trial on operational data during the 1988/89 Australian tropical cyclone season. The results of this trial confirmed the superiority of the combination technique over the other methods. It will be used oper...

87:6159 The Australian tropical cyclone season 1985–1986: Kingston, G., 1986. Aust. met. Mag., 34(3):103–115

87:6159 The Australian tropical cyclone season 1985–1986: Kingston, G., 1986. Aust. met. Mag., 34(3):103–115