Article

# A Review of Severe Thunderstorms in Australia

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## Abstract

Severe thunderstorms are a common occurrence in Australia, and have been documented since the first European settlement in 1788. These events are characterized by large damaging hail in excess of 2cm, convective wind gusts greater than 90kmh-1 and tornadoes, and contribute a quarter of all natural hazard related losses in the country. This impact has lead to a growing body of research and insight into these events. In this article, the state of knowledge regarding their incidence, distribution, and the resulting hail, tornado, convective wind risk and lightning will be reviewed. Applying this assessment of knowledge, the implications for forecasting, the warning process and how these events may respond to climate change and variability will also be discussed. Based on this review, several potential avenues for future research and exploration are suggested, and ongoing work in the field outlined. Most notably, the need for improved observational or proxy climatologies, forecasting guidelines for tornadoes and a greater understanding of how severe thunderstorms respond to climate variability are highlighted.

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... Carlson (1980) showing the Cold Conveyor Belt (CCB), warm conveyor belt (WCB) and the dry conveyor belt (DCB). (The COMET Program, 2014) Allen and Allen (2016). (a) 167 tornadoes from 1950 to 1961, adapted from Clarke (1962). ...
... In Australia, the Severe Storm Archive (SSA; BOM, 2015) contains data on hail, tornadoes, and damaging convective winds as early as 1795 up to the present day. In this dataset there is a strong bias, and even an over reporting of events, towards urban areas and the coast or along road networks (Schuster et al., 2005b;Allen et al., 2011;Tippett et al., 2015;Allen, 2016). Similarly, due to the sparse population in regional areas, along with the relatively small scale of severe thunderstorms, there is an under reporting of events in these rural areas resulting in a lack of understating of severe thunderstorms (Kelly et al., 1985;Hales, 1993;Griffiths et al., 1993;Geerts and Noke-Raico, 1995;Mills and Colquhoun, 1998;. ...
... For example, prior to the Australian BOM establishing the severe weather section in 1987 there was no formal collection mechanism, which led to temporal in-consistencies (Hales, 1993;Griffiths et al., 1993). This resulted in noticeable increase in the number of hailstorms over this period producing an artificial positive trend and questionable spatial distributions of hail occurrence (Allen and Allen, 2016). Because of this, the SSA is a short and inconsistent dataset prior 1987 and it is therefore challenging to make report-based climatology periods longer than a couple of decades. ...
Thesis
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Severe convective wind storms are responsible for billions of dollars in damage to global infrastructure each year. This suggests there are systematic deficiencies in the way that structures are designed to withstand this type of event and that there is a need to better understand the hazard convective wind storms pose to infrastructure. In order to quantify this risk, it is necessary to have a reliable and spatially complete climatology of their occurrence. Given no such climatology exists for Australia, this research sought to develop such a climatology based on recent observational records, as well as examining how climate change may impact the severe convective wind storm climate into the future. Severe weather records (including wind gusts) in the Australian Bureau of Meteorology’s Severe Storm Archive are spatially and temporally incomplete and are therefore inadequate for developing a reliable climatology. In contrast, approximately 600 Automatic Weather Stations (AWS) around the country now produce 1-minute data records for several atmospheric variables (including wind speed and direction). These records offer a source of data that can be reliably analysed. However, analysis of these data presents challenges, primarily including, a) identifying the weather mode (e.g., convective, frontal, strong pressure gradients, pressure systems) responsible for each extreme gust, and b) overcoming the incomplete spatial coverage of the network. To overcome these challenges, this work utilises Self-Organizing Maps (SOM) as an automated method for classifying the mode of each observed gust, and then applies hierarchical Bayesian statistics to extend the analysis to regions where no AWS records exist. With the increasing use and acceptance of SOM algorithms for classifying atmospheric data, this machine learning technique was used to objectively identify severe wind storms from 1-minutre AWS data. The SOM algorithm was applied to a small subset of AWS stations so that the SOMs could be trained, and their performance verified. Given the large number of free parameters built into the SOM algorithm, it was first essential to conduct a proper sensitivity analysis to determine the set up for the SOM. Upon selecting the best combination of free parameters to run the SOMs, different combinations of atmospheric variables were explored, including: wind speed, change in wind direction, temperature, mean sea level pressure, precipitation and equivalent potential temperature. Various statistical tools were used to determine how well the SOM algorithm was able to identify convective events compared to a manual identification of events. It was found that by considering wind speed alone, the SOM was able to perform well compared to methods that combine other variables such as temperature, pressure, and change in wind direction. To extend this station-based analysis and facilitate the development of a spatially complete convective wind storm climatology across the Australian continent, observational and global reanalysis data are coupled to determine the probability of severe wind storms occurring in different parts of Australia, even where there is no observational data available. A Bayesian hierarchical framework was used to develop the relationship between the SOM identified AWS convective events and severe weather indices calculated from ERA-Interim reanalysis data, while minimizing the impact of the spatial and temporal biases inherit to the AWS data. Using this model, the expected number of severe wind storms occurring in all parts of Australia was estimated. The Bayesian model was run using data between 2005-2015 and showed that there are significantly more severe convective wind storms occurring in northern Western Australia, southern Northern Territory and western Queensland than observational datasets show. Resampling techniques minimised the effects of the short observational period and helped determine the index or indices that best relates the observational and reanalysis data. These relationships were then used to extend the length of the observed dataset over the entire ERA-Interim reanalysis period (1979-2015). The flexibility of the Bayesian Hierarchal model allows the ERA-Interim reanalysis data to be replaced by other global datasets, including global climate models. Here, the Bayesian model is run with CMIP5 data to estimate how the climatology of severe convective wind storms might change under different climate scenarios. The BOM-CSIRO ACCESS-CM 1.3 under the RCP8.5 scenario was used. Mean severe weather indices were calculated for the projection period of 2090-2100 and the historical period from 1990-2000. Using this global model input for the Bayesian model, the change in the severe convective wind storm event counts from 1990-2000 to 2090-2100 were examined. To understand potential changes to convective wind storm hazard under an Intergovernmental Panel on Climate Change (IPCC) climate change scenario, large-scale global climate model environmental parameters (i.e. CAPE, Wind Shear) used in the stochastic model to estimate convective wind storm frequency were studied. Running the stochastic model with these “changed” environments showed that an increase in the number of severe convective wind storms can be expected during the spring, summer, and autumn, especially over northern Western Australia, and Queensland. This resulting data can be used to generate hazard maps and stochastic event sets to inform wind-resistant design standards and facilitate risk-based decision making by government and industry.
... Grossversuch III showed that hailfall 813 increased after seeding, but at a very low level of significance, whereas Grossversuch IV 814 showed that the difference in hail kinetic energy was not significantly different (at the 5% with the sparse network of trained individuals who make the vast majority of these re- As for panel a, except greater than 5 cm hail reports. Adopted from [Allen and Allen, 2016], their Figure 7. ...
... Used with permission of the author and Elsevier. Walsh, 2005;Allen et al., 2011;Allen and Karoly, 2014;Allen and Allen, 2016]. The pri-831 mary factor driving expansion of hail observations has been the impacts of the 1999 Syd-832 ney hailstorm, and thus most analyses are regionally specific [Schuster et al., 2005a]. ...
... Property insurance underwriting for both the wind and hail perils in the US relies Allen and Tippett, 2015;Allen and Allen, 2016;Groen- 1647Groen- emeijer et al., 2017Allen et al., 2017]. The perils are also much smaller in spatial scale 1648 relative to other hazards considered by insurers. ...
Article
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The processes leading to the development of hail and the distribution of these events worldwide are reviewed. Microphysical and physical characteristics of hail development are described to provide context of the notable gaps in our understanding of what drives hail to grow large, or what determines how it falls to the ground. Distributional characteristics of hail are explored, utilizing both surface observations of hailstones and remotely sensed observational datasets to identify opportunities and needs for new observations. These observational deficiencies contribute to our limited capacity to both forecast hail or its expected size, and reduce the effectiveness of using favorable conditions for hail development as a proxy to frequency where observations are unavailable. Given the substantive influences of both climate variability and the changing Earth system on hail, the latest understanding of their contributions to risk are addressed. Applying this understanding of the distribution and physical characteristics of hail, the damage by hail of agriculture and insured property are assessed. Much remains unknown about the processes leading to hail growth and environmental controls on hail occurrence, size and magnitude, particularly outside of the United States and Europe. A better understanding of the global occurrence of hail is also needed to better anticipate the hazard and associated impacts.
... As the focus here is on characterizing tornadoes in subsequent thresholds based on both shear and a lifted index. Given the small body of available literature and case studies of tornadoes in Australia (Allen and Allen 2016), this suggests motivation to improve tornado forecasting parameters for Australian conditions. ...
... To avoid these problems, we extract latitude, longitude, date and time information, which are available in all cases and use this information to produce a comparative climatology. Data are gridded to an 80x80 km grid, following the approach of Allen and Allen (2016). ...
... No significant tornadoes impacted the major cities, however the human impact was anomalous, with 147 reported injuries and no fatalities for 2013 (Table A1), compared with 116 injuries and 28 fatalities for the remainder of the 1795-2014 STA record. However, the STA record does not always include injury information (for example, it contained no injuries or fatalities for 2013), and media reports document greater numbers of injuries for historical events (Allen and Allen 2016). Spatially, the tornadoes that occurred during 2013 reflect the distribution expected from the population distribution (Fig. 2a), with a greater frequency where density is higher. ...
Article
... The ESSL data has most records over Central Europe and shows a steep increase in extremes after its unification in 2006 . The BoM data is limited due to the sparse population density and the non-existence of a formal collection mechanism for severe storm reports before 1987 (Allen and Allen, 2016). ...
... Using satellite data Cecil and Blankenship (2012) and (Mroz et al., 2017) generally show high hail hazards in the tropics and subtropics including Northwestern Australia where freezing levels are high. Hail observations from Australia (Fig. 1b) do not confirm these high frequencies, which is supported by Allen and Allen (2016) and Bedka et al. (2018). However, due to a lack of ground observations, tropical and subtropical large hail hazards are not well understood. ...
Article
Full-text available
A single hailstorm can cause losses in the billion-dollar range if it occurs over a densely populated area. Property losses from hailstorms are rising with time mainly due to a combination of increases in population density and wealth. Report based observational hail data alone are highly inhomogeneous and unable to discriminate between climate and societal changes. Here we present a statistical approach that estimates hail hazard from large-scale environmental conditions. Using daily ERA-Interim reanalysis data and large hail observations (diameter larger than 2.5 cm) from the conterminous United States (CONUS) we show that four predictors enable skillful discrimination of large hail frequencies on a regional scale. The predictors include atmospheric instability, freezing level height, and 0–3 km wind shear and storm relative helicity. These variables are used to develop a hail algorithm, which provides the probabilities for large hail occurrence from regional to global scales and from daily to climate timescales. The algorithm skill is tested over the CONUS and with independent hail observations from Australia and Europe. It skillfully captures the frequency, annual cycle, spatial patterns, and interannual variability of observed large hail records in a large variety of climate regions. Deficiencies are found in regions with strong orographic forcing and low shear environments. The algorithm outperforms established severe convection indices in terms of more accurately predicting absolute hail frequencies and the annual cycles of large hail in all tested regions. The code is open-source and is applicable to a variety of tasks including daily to seasonal forecasting and assessing climate change influences on hail hazard.
... The tornadoes were not associated with classic supercell thunderstorms, and occurred at a climatologically unusual time of the diurnal cycle (see e.g. Allen and Allen, 2016;Grams et al., 2012). This paper looks at the synoptic and dynamical set-up that led to the tornado outbreak and puts the event in context of existing tornado and convective mode classification schemes. ...
... A recent review of severe thunderstorm research in Australia (Allen and Allen, 2016) found that tornadoes are a frequent but under-reported feature of the Australian environment, and that they can occur in a variety of environmental contexts. The distribution of tornadoes in the Australian Severe Thunderstorm Archive (STA) shows a seasonal peak in occurrence of tornadoes in NSW between November and February, as well as a strong diurnal peak in occurrence from mid-afternoon to early evening (Griffiths et al., 1993). ...
... The tornadoes were not associated with classic supercell thunderstorms, and occurred at a climatologically unusual time of the diurnal cycle (see e.g. Allen and Allen, 2016;Grams et al., 2012). This paper looks at the synoptic and dynamical set-up that led to the tornado outbreak and puts the event in context of existing tornado and convective mode classification schemes. ...
... A recent review of severe thunderstorm research in Australia (Allen and Allen, 2016) found that tornadoes are a frequent but under-reported feature of the Australian environment, and that they can occur in a variety of environmental contexts. The distribution of tornadoes in the Australian Severe Thunderstorm Archive (STA) shows a seasonal peak in occurrence of tornadoes in NSW between November and February, as well as a strong diurnal peak in occurrence from mid-afternoon to early evening (Griffiths et al., 1993). ...
Article
This paper documents the case of a nocturnal outbreak of tornadoes on the New South Wales (NSW) south coast on 23 February 2013, and provides an analysis of the conditions that led to the outbreak. These tornadoes were associated with the passage of a warm front which had developed on the eastern flank of a mature extratropical cyclone.The damage from the tornadoes is discussed, and an analysis of the synoptic and mesoscale conditions that led to the event is provided. An analysis of radar at the time of the event shows a series of vortices developing within a zone of horizontal shear just prior to the tornadoes developing. The tornadoes were difficult for operational forecasters to predict, partly due to the infrequent occurrence of nocturnal tornadoes of this type in NSW, and in part due to operational demands from the broader scale severe weather event that resulted from the low-pressure system. This paper presents an analysis of the event that may assist forecasters in identifying similar events in the future.
... There is a need for improved preparedness for convection-related hazards including through greater understanding of their meteorology, mean occurrence frequencies, and environmental factors influencing their spatiotemporal variability. In Australia, previous studies have investigated the mean occurrence frequency of hail through analysis of radar observations near Brisbane and Sydney Warren et al., 2020), satellite observations (Bedka et al., 2018;Cecil & Blankenship, 2012), as well as station observations and damage reports (Allen & Allen, 2016;Prein & Holland, 2018;Schuster et al., 2005Schuster et al., , 2006. The mean occurrence frequency of lightning over the Australian region has been examined based on satellite observations (Bednarczyk & Sousounis, 2014; ©2020. ...
... There is relatively little variation between the different locations in the timing of the maxima and minima. The hail and lightning events occur more frequently during the warmer months of the year, broadly similar to a range of previous studies(Allen & Allen, 2016;Bedka et al., 2018;Bednarczyk & Sousounis, 2014;Dowdy & Kuleshov, 2014;King & Kennedy, 2019;Schuster et al., 2005;Taszarek et al., 2017;Virts et al., 2013;Warren et al., 2020). The minimum values occur around the May to July period for the lightning and hail events. ...
Article
Full-text available
There is a growing need to better understand and quantify risks associated with extreme weather, including severe thunderstorm‐related hazards such as hail and lightning. Hail occurrence based on a long‐term archive of radar observations is presented for the first time in many temperate and subtropical regions of Australia, together with lightning observations from a ground‐based network of sensors. Mean monthly and hourly occurrence frequencies are examined for hail and lightning. Environmental conditions obtained from hourly reanalysis data indicate stronger wind shear on average for hail than lightning. The environmental conditions also indicate higher freezing levels on average for lightning than hail. These environmental differences provide plausible physical reasons for observed differences between hail and lightning climatology through the year. The study results are intended to help inform future planning and preparedness for thunderstorm‐related risks, including for severe weather forecasting and climate risk applications.
... Thunderstorm outflow and SCWs have been observed by previous studies in Australia (Richter et al., 2014;Romanic et al., 2020;Sherman, 1987) and systematically identified within anemometer records (Geerts, 2001;Holmes, 2002;Spassiani & Mason, 2021). However, producing a long-term spatially consistent climatology of these events, as well as identifying their associated large-scale environments, has proved challenging in Australia largely due to observational constraints (Allen & Allen, 2016). Subsequently, measurements of SCW gusts can be used in training methods based on environmental diagnostics, suitable for application in climate studies (Brown & Dowdy, 2019;Rädler et al., 2018;Spassiani, 2020). ...
Article
Full-text available
Thunderstorms can produce severe convective winds (SCWs) that damage buildings and other infrastructure such as electricity transmission towers. Understanding the climatology of SCWs is therefore important for planning and risk management. An archive of observed SCWs is used to examine a diverse set of diagnostics for indicating SCW environments based on reanalysis data. These diagnostics are then applied to climate model data to examine projections of future climate change for Australia. A diagnostic based on logistic regression is found to provide a better representation of observed SCW occurrences than other diagnostics. Projections for the future based on that diagnostic indicate increases and decreases between 16% and 34% in the occurrence frequency of regionally averaged SCW environments, based on the 10th and 90th percentile estimates of annual mean changes from a 12-member ensemble of global climate models. Projections based on other severe weather diagnostics indicate a wider range of future changes, including increases and decreases of up to 50% in magnitude, with regional and seasonal variations through Australia. Changes in the frequency of SCW environments appears to be largely driven by increased low level moisture concentrations which can lead to increased convective available potential energy, countered in some cases by a stabilization of the mid-troposphere temperature lapse rate. These results represent the most comprehensive estimate to date for constraining the range of uncertainty in projected future changes in convective environments for Australia, including severe thunderstorms and associated SCWs, noting that this has significant implications for risk management and climate adaptation purposes.
... Australia, hailstorm frequency and maximum hail size have been studied using data 94 from reports between 1791 and 2014 ( Schuster et al. 2005;Allen and Allen 2016). In 95 addition, in western Asia, the climatology of severe hail has been studied in Turkey 96 using data from meteorological stations, newspaper archives, and Internet sources 97 during 1925-2014(Kahraman et al. 2016). ...
Article
Full-text available
The hail day climatology from 1961 to 2005 was previously studied based on hundreds of surface stations in China. Recently, both hail occurrence and maximum hail diameter (MHD) data from more than 2000 surface stations were released by the National Meteorological Information Center of China. These data enable hail climatology to be explored using both hail frequency (HF), which is defined as annual mean hail occurrence, and MHD records from more stations over the entire country. Following quality control, hail data from 2254 stations were selected for the period of 1980–2015. In general, HF increased with station topography height, with a maximum of more than 30 events per year in the Tibetan Plateau and a minimum of less than 1 event per year in southern China, whereas the station mean MHD decreased with topography height. The highest peak of the 80th-percentile cumulative distribution function of the annual MHD cycle in southern China occurred in May but was delayed to July in the north. Severe hail (MHD ≥ 20 mm; 5.32% of all cases) mainly occurred along the edge of the plain, near the mountainsides, and was most likely to develop in the afternoon.
... Visually, they may be identified by the formation of Cumulonimbus clouds, presence of lightning and thunder, by the sudden drop of temperature as well as the sudden increase in wind speed and finally by the heavy precipitation. Severe thunderstorms may produce hail and floods as well as damaging winds and even tornados [1]. As such, damage produced by these storms are not only limited to wind- induced damage but also wind-related damage such as that produced by heavy rain or large hail which may affect both the built [2; 3] as well as the natural environment [4]. ...
Conference Paper
A recent storm which occurred on June 19 th 2016 in Romania caused the collapse of several overhead transmission towers next to the village Cuci of Mureș county: 6 towers of 400 kV, 4 towers of 220 kV, 18 towers of 110 kV and several LEA towers according to Energy for Romania. As a consequence of this event, 13599 consumers were left without power in 60 nearby localities. The national media emphasized the unusual nature of this event during which temperature dropped by 10 o C and the wind velocity reached over 100km/h. The total reported estimated damage was approximately 545000 euros. In Romania, information on wind-related damage is scarce and poorly documented. Although not completely reliable, due to the tendency of journalists to exaggerate facts, the main source of information is represented by mass-media reports published in the aftermath of the storm. Due to the lack of wind measurements which allow for identification of thunderstorms based on data analysis, in this paper, thunderstorm occurrence is studied considering mass-media damage reports. The aim of this paper is to investigate wind-related damage that has been produced in Romania by strong winds in order to identify best possible locations for installation of instrumentation to measure thunderstorms for future research. The main methodology of investigation involves performing an extensive review of damage reports that have been published in online newspapers in the past five years (2017-2013). Data related to affected counties, storm intensity, damage type as well as visual accounts of interviewed people are documented. Based on this, a database of wind storms as well as a wind damage prone map of Romania is elaborated.
... The influence of urban environment on the lightning activity remains a debatable topic, beginning with first publication of Westcott [1], followed by several studies in US, Europe, Asia, Brazil and Australia [2][3][4][5][6][7]. The change of LULC in urban areas leads to a change of surface characteristics. ...
Article
Full-text available
Land use and land cover (LULC) play a crucial role in the interaction between the land and atmosphere, influencing climate at local, regional, and global scales. LULC change due to urbanization has significant impacts on local weather and climate. Land-cover changes associated with urbanization create higher air temperatures compared to the surrounding rural area, known as the "urban heat island (UHI)" effect. Urban landscapes also affect formation of convective storms. In recent years, the effect of urbanization on local convections and lightning has been studied very extensively. In this paper a long-term study has been carried out taking cloud-to-ground (CG) lightning data (1998-2012) from Tai-Power Company, and particulate matter (PM10), sulfur dioxide (SO 2) data (2003-2012) from the Environmental Protection Administration (EPA) of Taiwan, in order to investigate the influence of LULC change through urbanization on CG lightning activity over Taipei taking into account in situ data of population growth, land use change and mean surface temperature (1965-2010). The thermal band of the Land-Sat 7 satellite was used to generate the apparent surface temperature of New Taipei City. It was observed that an enhancement of 60-70% in the flash density over the urban areas compared to their surroundings. The spatial distribution of the CG lightning flashes follows closely the shape of the Taipei city heat island, thereby supporting the thermal hypothesis. The PM10 and SO 2 concentrations showed a positive linear correlation with the number of cloud-to-ground flashes, supporting the aerosol hypothesis. These results indicate that both hypotheses should be considered to explain the CG lightning enhancements over the urban areas. The results obtained are significant and interesting and have been explained from the thermodynamic point of view. Keywords: Land use and land cover (LULC); cloud-to-ground (CG) lightning; particulate matter (PM10); sulfur dioxide (SO 2)
... Associating downbursts with severe thunderstorms, the highest frequency of occurrence of these events is observed along the broad region along the East Coast of the US (SPC, 2015). These differences among climatologies of tornadoes, thunderstorms and wind gusts for the US in 2015 are portrayed in Fig. 7. Similarly, other studies investigated climatologies of tornadoes, thunderstorms and synoptic winds over Europe (e.g., Burlando et al., 2018a,b;Romanic, 2018;Romanić et al., 2016a;Groenemeijer and Kühne, 2014;Brooks et al., 2003;Giaiotti et al., 2007), Australia (e.g., Soderholm et al., 2017;Allen and Allen, 2016;Allen et al., 2014), Asia (e.g., Chen et al., 2018;Zhang et al., 2017;Cecil and Blankenship, 2011), and South America (e.g., Montecinos et al., 2016;Rasmussen et al., 2014;Silva Dias, 2011). ...
Article
The traditional Davenport Chain method, which is at the base of current wind engineering practice, is founded on the assumption that engineering structures are subjected to loads resulting from their interaction with synoptic winds approximated by atmospheric boundary layer (ABL) flow fields. Herein, we introduce a new class of non-synoptic winds and bring forward the differences between the two wind systems in terms of climatology, microclimatology due to the surface layer characteristics, aerodynamic loading, and structural responses. We use a set of downburst and tornado simulations conducted during the last couple of years in the Wind Engineering, Energy and Environment (WindEEE) Dome at Western University, Canada to investigate and illustrate these differences. We show ways in which geometric, kinematic and dynamic scaling can be defined for the non-synoptic wind systems. In the process, we analyze the assumptions related to the quasi-steady theory, which is at the base of the Davenport Chain for ABL winds. We then interrogate the applicability of these assumptions to the non-synoptic – three-dimensional, non-stationary and non-Gaussian (3D-NS-NG) – wind systems, such as tornadoes and downburst, and their actions on buildings and structures.
... Designs for large structures, or networks, are likely to give a greater consideration to parameter uncertainty than small plot-level structures because of the higher associated costs of failure. However, the aggregated costs of multiple plot-level structures simultaneously failing can be substantial, such as when extreme events occur in urban areas [15][16][17]. ...
Article
The main design determinant for small catchment hydraulic structures is rainfall intensity. Localised relationships between rainfall intensity, frequency and duration (IFD) are used to design each structure to a specified level of performance. However, limitations in rainfall observations introduce uncertainty in IFD values. Further, this uncertainty is compounded by changes in climatic conditions via anthropogenic forcing. Whether this is a cause for concern depends on the structure's sensitivity to deviations away from design rainfall values. Here, we investigate the ability of roof drainage systems to accommodate deviations in design rainfall. We assess the sensitivity of box gutter overflow designs across Australia to spatial variability in IFD values, and projections of IFD values due to climatic change. Different overflow designs were found to have markedly variable responses to rainfall intensity increases, from 13% to 406% before failure. Potential increases in rainfall intensity from spatial variability uncertainty varied from 2 to 54%. While rainfall projections for the 2090 decade ranged from −15 to +59%. Rainfall intensity increases as high as 259% were noted when both sources of uncertainty were combined for a temperature rise scenario of 5 °C. At the majority of locations coupled increases in rainfall intensity were primarily driven by existing rather than future uncertainties for a 2 °C temperature rise scenario. Considering design rainfall uncertainties in terms of design sensitivity shows that adapting to present and future uncertainties can come at no additional cost for some design options while other options need to be altered to reduce the risk of failure.
... Climate change has already had a significant influence on weather phenomena in Australia and this influence is expected to continue throughout this century (IPCC 2013;Reisinger et al. 2014; CSIRO and Bureau of Meteorology 2015, Bureau of Meteorology and CSIRO 2018). Due to their small spatial and temporal scale, as well as infrequent occurrence, observed trends in severe thunderstorm characteristics are difficult to determine in general (IPCC 2013;Allen and Allen 2016;Walsh et al. 2016), while noting some indication of a downward trend in observed lightning flashes in southern Australia during the cooler months of the year ( Bates et al. 2015). Currently available climate models are not able to directly examine thunderstorm activity (including due to the small spatio-temporal scales required to model some convective processes), such that analysis methods typically assess changes in larger-scale indicators of atmospheric conditions favourable to thunderstorm occurrence (e.g., using parameters such as Convective Available Potential Energy: CAPE). ...
Book
The spatial and temporal characteristics of extreme convective wind gusts in South Australia are analysed over the period 1979 to 2017, using station data in combination with wind gust and environmental parameter data from atmospheric reanalyses. The reanalyses used are the European Center for Medium-range Weather Forecasts ERA-Interim, and the Bureau of Meteorology High-resolution Atmospheric Regional Reanalysis for Australia (BARRA). The wind gust data obtained from the reanalyses generally provide a good representation of the observed wind gusts, apart from extreme events above 30 m.s-1 which are a focus of this study. The use of previously established environmental parameters associated with thunderstorm activity is found to be better than using wind gust data from the reanalyses for indicating the occurrence of observed extreme wind gusts. A conditional parameter is also tested here, based on two different sets of environmental conditions, to account for extreme wind events that can sometimes occur in low/zero large scale CAPE environments. Results include a systematic analysis of extreme wind environments based on all days from 1979 to 2017 and an examination of two extreme wind events: November 1979, as well as September 2016 which included the occurrence of several tornadoes. Regional variations in extreme wind environments are indicated, including being more strongly associated with CAPE for inland locations than near-coastal locations where wind shear plays a more important role. Long-term changes in extreme wind environments are examined over the 1979-2017 period, indicating a potential area of decreased risk in the far north of South Australia in recent decades, and a potential area of increased risk around the southern Flinders Ranges and Yorke Peninsula region. Extreme convective wind gust environments are found to have a strong relationship with the Southern Annular Mode, particularly during winter and spring in some regions, but not with the El Niño-Southern Oscillation or Indian Ocean Dipole.
... The World Meteorological Organization has developed a definition of severe weather that acknowledges regional differences in types of (e.g., sand/snow storms, flash floods) as well as thresholds for severe weather events (e.g., intensity of wind or rain) but characterizes severe weather as "an extreme meteorological event or phenomenon, which represents a real hazard (to human life and property)"( [2], p. 2). Although severe weather is less intense and occurs less frequently in the European region than in other parts of the world, it still poses an increasing threat in Europe [3,4]: for instance, thunderstorms, or so-called convective storms, can arise with heavy winds or even tornadoes, rainfall, hail, and lightning [5][6][7][8][9]. ...
Article
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Background: Warning apps can provide personalized public warnings, but research on their appraisal and impact on compliance is scarce. This study introduces a virtual city framework to examine affective reactions when receiving an app-based warning, and subsequent behavioral intentions. Methods: In an online experiment, 276 participants (M = 41.07, SD = 16.44, 62.0% female) were randomly allocated to one of eight groups (warning vs. no warning, thunderstorm vs. no thunderstorm, video vs. vignette). Participants were guided through a virtual city by a mock-up touristic app (t1). Then, the app issued a warning about an impending thunderstorm (t2), followed by a virtual thunderstorm (t3). The virtual city tour was presented via vignettes or videos. ANCOVAs were used to investigate trajectories of momentary anxiety, hierarchical regressions analyzed the impact of momentary anxiety on information seeking. Results: Participants who received a warning message and were confronted with a thunderstorm showed the highest increase in momentary anxiety, which predicted information seeking intentions. Conclusions: The findings underscore the importance of affective appraisal in processing warning messages. The virtual city framework is able to differentiate the impact of warning versus event in an online context, and thus promising for future warning research in virtual settings.
... These threshold values are somewhat lower than those applied in Australia by Allen and Karoly (2014) (e.g., threshold values including 25,000 and 68,000) while noting that they were considering a somewhat different approach and application, including the use of reports of severe thunderstorm events (rather than based on all thunderstorm events as is the intention for this study). Fig. 2) indicate more thunderstorm activity for the warmer months of the year (i.e., around the austral summer period for DJF: Fig. 2a) than the cooler months (i.e., around the austral winter period for JJA: Fig. 2c), broadly similar to previous studies (Dowdy and Kuleshov 2014;Allen and Allen 2016). More thunderstorm activity is indicated during spring (SON: Fig. 2d) than autumn (MAM: Fig. 2b) in general throughout Australia, apart from near-coastal western regions of Australia. ...
Article
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... Thunderstorms are characterized with a short but intense spell of rain, enormous lightning and gust of strong winds associated with cumulonimbus clouds (Doswell, 1987). These weather events are essential to understand and predict due to their catastrophic nature and short life span (Allen and Allen, 2016). Accurate and timely prediction of thunderstorms requires analyzing in-situ observations, satellite and weather radar imagery analysis and running state of the art mesoscale weather prediction models over the region of interest (Brooks et al., 2019;Sills and Joe, 2019). ...
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Thermodynamic indices have been used as a tool for nowcasting thunderstorms for decades. The present study deals with understanding the variations in threshold values of various thermodynamic indices during pre-monsoon season at two north-eastern Indian stations: Agartala and Guwahati. The study utilises thirty years (1987–2016) of radiosonde data, surface information about thunderstorms, and TRMM daily rainfall data. The threshold values for five years period interval each has been determined for fourteen thermodynamic indices to the whole period. The indices related to latent, potential and convective instability responded differently at both the sites.
... Lightning location networks (Kaltenböck et al., 2009;Nastos et al., 2014;Czernecki et al., 2016) and geostationary satellites equipped with lightning detectors (e.g., the FengYun-4A Lightning Mapping Imager) provide continuous information on the "stroke" and "event," respectively. The detection of lightning is relatively objective (Poelman et al., 2016), so lightning is generally used as a proxy for estimating the occurrence and development of thunderstorms (Allen and Allen, 2016). A significant number of studies have analysed the characteristics of thunderstorm at regional, national, or continental scales using lightning signals (Poelman, 2014;Cecil et al., 2015;Czernecki et al., 2016;Zhang et al., 2018). ...
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... Studies on hail trends in Oceania have been limited to Australia. The Australian Bureau of Meteorology maintains an archive of severe-storm observations, and, although it is an imperfect record 13 , it has been used to examine hail trends. Analysis of collated hail reports for New South Wales show that hail frequency was lower in 1989-2002 than in 1953-1988 (reF. ...
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... Supercell tornadoes have been studied extensively in U.S. through two dedicated field campaigns (VORTEX1; Rasmussen et al. 1994;VORTEX2;Wurman et al. 2012) and many observational and numerical studies. In Australia, some tornado case studies have been published (e.g., Hanstrum et al. 2002;Richter 2007), but the composition of a meaningful tornado climatology is still a work in progress, as it involves the painstaking collection and evaluation of disparate information sources such as newspaper articles (Allen and Allen 2016). ...
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Current and potential future storm-related wind and hail hazard in Australia is reviewed. Confidence in the current incidence of wind hazard depends upon the type of storm producing the hazard. Current hail hazard is poorly quantified in most regions of Australia. Future projections of wind hazard indicate decreases in wind hazard in northern Australia, increases along the east coast and decreases in the south, although such projections are considerably uncertain and are more uncertain for small-scale storms than for larger storms. A number of research gaps are identified and recommendations made.
... The impact of thunderstorms upon the Brisbane Metropolitan Area (BMA) and the encompassing South East Queensland (SEQ) region of Australia is recognised through both climatological (Allen and Karoly 2014;Peter et al. 2015;Soderholm et al. 2017a;Allen and Allen 2016) and event-based studies (Richter et al. 2014;Soderholm et al. 2016Soderholm et al. , 2017b. Although most thunderstorms have a limited impact on the BMA, the region experiences more reports of large hail (.2 cm) and damaging wind gusts (.25 m s À1 ) than any other Australian capital city (Allen and Karoly 2014). ...
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Synthesis of previous work indicates that the four high-impact cases occurred during a south-easterly change with strengthening winds ahead of the change, suggesting commonalities may exist that can be exploited for forecasting. This paper provides a detailed observational analysis of the environment and convective storms from the four BMA events to explore discriminating characteristics that may improve the skill of nowcasting. For the four BMA events, significant deep convection was observed along the change for the hours prior to the change’s arrival at the Brisbane Airport, potentially acting as an early indicator of favourable conditions for high-impact thunderstorms. It was found that the timing of the south-easterly change through Brisbane was also highly correlated for all events, occurring within a 90-min window during the mid-afternoon convective heating maximum. Despite the destructive severe weather, upper air conditions were marginal for supporting organised thunderstorms, highlighting the importance of capturing mesoscale processes, such as the south-easterly change. To further understand possible discriminators of the four high-impact BMA cases, a 10-year climatology of the mesoscale and synoptic environment associated with south-easterly change events was developed for the warm season months of November to January. It is shown that although only a small number of events are associated with high-impact BMA thunderstorms, these events share a set of conditions relating to the prechange wind shift, timing of the south-easterly change and radar signatures. ... The thunderstorm cells are mainly originating from the vertically developed cumulonimbus clouds, with moisture, triggering mechanism (lifting) and atmospheric instability as a basic requirement for the formation (Doswell 1987). The study of thunderstorms and associated atmospheric changes is a prime area of research worldwide due to the need of accurate prediction of these events (Kunz et al. 2009;Saha et al. 2012;Wu et al. 2013;Diffenbaugh et al. 2013;Madala et al. 2013Madala et al. , 2016Brooks et al. 2014;Seeley and Romps 2015;Allen and Allen 2016;Tippett et al. 2016;Osuri et al. 2017;James et al. 2018). To improve the predictability of thunderstorm, among various techniques, the stability indices and skill score techniques are one of the widely accepted and popular methods helpful in the nowcasting of thunderstorms and associated precipitation events for many years (Normand 1921;Srinivasan et al. 1973;Peppier 1988;Schultz 1989;Sadhukhan et al. 2000;Mukhopadhyay et al. 2005;Ghosh et al. 2008;Madhulatha et al. 2013;Santhi et al. 2014;Viceto et al. 2017). ... Article Full-text available The present study analyses thermodynamic indices variation over three sites of eastern Indian region: Bhubaneswar, Kolkata and Ranchi, associated with pre-monsoon thunderstorms for 20-year period (1987–2006) for Bhubaneswar and Kolkata and 15 years (1996–2010) for Ranchi. All three sites are showing a rise in humidity over the period, unveiling the climate change over the region. We evaluated the threshold values of various thermodynamic indices for periods of 5-year intervals at each site based on skill score analysis. The indices associated with potential, convective, latent instability and moisture are showing varying threshold values over all the sites, and some of the indices are showing a definite increase/decrease in these threshold values. All three sites are showing a decrease in thunderstorm frequency over the study period. The work identifies the thermodynamic indices, which tend to capture the global warming impact in the threshold values by either showing an increase or decrease with the time at each site. The results advocate that for a long-term analysis of thermodynamic indices, the threshold values may change from one period to another. ... The impact of thunderstorms upon the Brisbane Metropolitan Area (BMA) and the encompassing South East Queensland (SEQ) region of Australia is recognised through both climatological Allen and Karoly (2014); Peter et al. (2015); Soderholm et al. (2017a); Allen and Allen (2016)and event-based studies Richter et al. (2014); Soderholm et al. (2016Soderholm et al. ( , 2017b. While most thunderstorms have a limited impact on the BMA, the region experiences more reports of large hail (> 2 cm) and damaging wind gusts (> 25 ms -1 ) than any other Australian capital city Allen and Karoly (2014). ... Article Full-text available Accurate thunderstorm warnings in the hours to minutes preceding impact are often limited by the complex evolution of the mesoscale atmospheric environment. To accurately capture these complexities, analysis of observations remains central to operational short term nowcasting predictions of thunderstorms. Over the past 40 years, multiple high-impact thunderstorm events have impacted the Brisbane Metropolitan Area (BMA) of South East Queensland (SEQ) resulting significant insured losses. Four of these high-impact events are the focus of the following work. These cases include three events that resulted in the greatest insured losses for the BMA, exceeding$4 billion AUD (2017) () and a fourth significant event (24 December 1989). Synthesis of previous work indicates that the four high-impact cases occurred during a southeasterly change with strengthening winds ahead of the change, suggesting commonalities may exist that can be exploited for forecasting. This paper provides a detailed observational analysis of the environment and convective storms from the four BMA events to explore discriminating characteristics that may improve the skill of nowcasting. For the four BMA events, significant deep convection was observed along the change for the hours prior to the change's arrival at the Brisbane Airport , potentially acting as an early indicator of favourable conditions for high-impact thunderstorms. It was found that the timing of the south-easterly change through Brisbane was also highly correlated for all events, occurring within a 90 minute window during the mid-afternoon convective heating maximum. Despite the destructive severe weather, upper air conditions were marginal for supporting organised thunderstorms, highlighting the importance of capturing mesoscale processes, such as the southeasterly change. To further understand possible discriminators of the four high-impact BMA cases, a 10 year climatology of the mesoscale and synoptic environment associated with southeasterly change events was developed for the warm season months of November to January. It is shown that while only a small number of events are associated with high-impact BMA thunderstorms , these events share a set of conditions relating to the pre-change wind shift, timing of the southeasterly change and radar signatures.
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This study presents a concept for coupling remote sensing data and environmental variables with machine learning techniques for the prediction of large hail events. In particular, we want to address the following question: How would one improve the performance of large hail warnings / forecasts if thermodynamic and kinematic parameters derived from a numerical weather prediction model are combined with real-time remote sensing data? For this purpose, POLRAD radar reflectivity, EUCLID lightning detection data, and convective indices calculated from the ERA5 reanalysis are combined and then compared with large hail reports from Poland (2008–2017). The data fusion of multiple sources, coupled with the machine learning approach, makes it possible to greatly improve the robustness of large hail prediction compared to any single product commonly used in operational forecasting. This is especially noticeable with the reduced number of false alarms. Although the created machine learning models are mainly driven by radar reflectivity, composite thermodynamic and kinematic indices such as Hail Size Index (HSI), Significant Hail Parameter (SHIP), Large Hail Parameter (LGHAIL), and WMAXSHEAR provide an added value to a model's performance. The accuracy achieved by a random forest model brings with it encouraging prospects for future research with respect to operational forecasters (who may fill in the gaps within NWP-derived data with remotely sensed measurement) and climatological studies that aim to investigate past and future changes in severe weather occurrences.
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In this study we investigate convective environments and their corresponding climatological features over Europe and the United States. For this purpose, NLDN and ATDnet lightning data, ERA5 hybrid-sigma levels, and severe weather reports from ESWD and SPC Storm Data were combined on a common grid of 0.25° and 1-hour steps over a period 1979–2018. Severity of convective hazards increases with increasing instability and wind shear (WMAXSHEAR), but climatological aspects of these features differ over both domains. Environments over the United States are characterized by higher moisture, CAPE, CIN, wind shear and mid-tropospheric lapse rates. Conversely, 0–3 km CAPE and low-level lapse rates are higher over Europe. From the climatological perspective severe thunderstorm environments (hours) are around 3–4 times more frequent over the United States with peaks across Great Plains, Midwest and Southeast. Over Europe severe environments are the most common over the south with local maxima in northern Italy. Despite having lower CAPE (tail distribution of 3000–4000 J kg-1 compared to 6000–8000 J kg-1 over the United States), thunderstorms over Europe have higher probability for convective initiation given favorable environment. Conversely, the lowest probability for initiation is observed over the Great Plains, but, once a thunderstorm develops, the probability that it will become severe is much higher compared to Europe. Prime conditions for severe thunderstorms over the United States are between April and June, typically from 1200 to 2200 CST, while across Europe favorable environments are observed from June to August, usually between 1400 and 2100 UTC.
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The production of electrical energy from solar energy is increasing vastly from last decade because it gives an environment clean and limitless source of energy. There are numerous factors such as solar radiation, wind, dust, temperature, humidity, and hailstorm that influence the performance of PV module. Because of the increasing demand for solar energy, the safety of solar modules is more important than ever. The heavy hailstorm may damage the front glass surface and breakage solar cell. When cracks appear in front glass surface, it they reduces the sun-oriented radiation to enter specific on the solar cell. When cracks appear in a solar cell, the cell is fully isolated as a result current decreases. Hailstorm not only reduces the total power generation but also reduces the life of PV Module. There are few researches on the impact of a hailstorm on the performance of PV module. The hailstorm reduces the output power and the life of the PV module, since the safety of the solar panel from the hailstorm is very necessary. This paper discusses in detail the formation of hailstorm and the impact of a hailstorm on the performance of PV module.
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On 16 December 2015 a severe thunderstorm and associated tornado affected Sydney causing widespread damage and insured losses of $206 million. Severe impacts occurred in Kurnell, requiring repairs to Sydney's desalination plant which supplies up to 15% of Sydney water during drought, with repairs only completed at the end of 2018. Climatologically, this storm was unusual as it occurred during the morning and had developed over the ocean, rather than developing inland during the afternoon as is the case for many severe storms impacting the Sydney region. Simulations of the Kurnell storm were conducted using the Weather Research and Forecasting (WRF) model on a double nested domain using the Morrison microphysics scheme and the NSSL 2-moment 4-ice microphysics scheme. Both simulations produced severe storms that followed paths similar to the observed storm. However, the storm produced under the Morrison scheme did not have the same morphology as the observed storm. Meanwhile, the storm simulated with the NSSL scheme displayed cyclical low- and mid-level mesocyclone development, which was observed in the Kurnell storm, highlighting that the atmosphere supported the development of severe rotating thunderstorms with the potential for tornadogenesis. The NSSL storm also produced severe hail and surface winds, similar to observations. The ability of WRF to simulate general convective characteristics and a storm similar to that observed displays the applicability of this model to study the causes of severe high-impact Australian thunderstorms. References J. T. Allen and E. R. Allen. A review of severe thunderstorms in Australia. Atmos. Res., 178:347–366, 2016. doi:10.1016/j.atmosres.2016.03.011. Bureau of Meteorology. Severe Storms Archive, 2020. URL http://www.bom.gov.au/australia/stormarchive/. D. T. Dawson II, M. Xue, J. A. Milbrandt, and M. K. Yau. Comparison of evaporation and cold pool development between single-moment and multimoment bulk microphysics schemes in idealized simulations of tornadic thunderstorms. Month. Wea. Rev., 138:1152–1171, 2010. doi:10.1175/2009MWR2956.1. H. Hersbach, B. Bell, P. Berrisford, S. Hirahara, A. Horanyi, J. Munoz-Sabater, J. Nicolas, C. Peubey, R. Radu, D. Schepers, et al. The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146:1999–2049, 2020. doi:10.1002/qj.3803. Insurance Council of Australia. Victorian bushfire losses push summer catastrophe bill past$550m, 2016. E. R. Mansell, C. L. Ziegler, and E. C. Bruning. Simulated electrification of a small thunderstorm with two-moment bulk microphysics. J. Atmos. Sci., 67:171–194, 2010. doi:10.1175/2009JAS2965.1. R. C. Miller. Notes on analysis and severe-storm forecasting procedures of the Air Force Global Weather Central, volume 200. Air Weather Service, 1972. URL https://apps.dtic.mil/sti/citations/AD0744042. H. Morrison, J. A. Curry, and V. I. Khvorostyanov. A new double-moment microphysics parameterization for application in cloud and climate models. Part I: Description. J. Atmos. Sci., 62:1665–1677, 2005. doi:10.1175/JAS3446.1. H. Morrison, G. Thompson, and V. Tatarskii. Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Month. Wea. Rev., 137:991–1007, 2009. doi:10.1175/2008MWR2556.1. J. G. Powers, J. B. Klemp, W. C. Skamarock, C. A. Davis, J. Dudhia, D. O. Gill, J. L. Coen, D. J. Gochis, R. Ahmadov, S. E. Peckham, et al. The Weather Research and Forecasting Model: Overview, system efforts, and future directions. Bull. Am. Meteor. Soc., 98:1717–1737, 2017. doi:10.1175/BAMS-D-15-00308.1. H. Richter, A. Protat, J. Taylor, and J. Soderholm. Doppler radar and storm environment observations of a maritime tornadic supercell in Sydney, Australia. In Preprints, 28th Conf. on Severe Local Storms, Portland OR, Amer. Meteor. Soc. P, 2016. W. C. Skamarock, J. B. Klemp, J. Dudhia, D. O. Gill, Z. Liu, J. Berner, W. Wang, J. G. Powers, M. G. Duda, D. Barker, and X.-Y. Huang. A description of the advanced research WRF Model version 4. Technical report, 2019. Storm Prediction Center. The Enhanced Fujita Scale (EF Scale), 2014. URL https://www.spc.noaa.gov/efscale/. R. A. Warren, H. A. Ramsay, S. T. Siems, M. J. Manton, J. R. Peter, A. Protat, and A. Pillalamarri. Radar-based climatology of damaging hailstorms in Brisbane and Sydney, Australia. Quart. J. Roy. Meteor. Soc., 146:505–530, 2020. doi:10.1002/qj.3693.
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A review of thunderstorm and lightning observations in Australia, with emphasis on studies of their spatial distribution and frequency over the Australian continent, is presented. Long-term thunderday records, lightning data obtained by ground-based lightning detection instruments CIGRE-500 and CGR3 and by NASA satellite-based instruments OTD and LIS have been analyzed to develop maps of total lightning flash density, Nt, (i.e. cloud-to-ground and intracloud) and of ground flash density, Ng. The peak lightning occurrence is in the north-western part of the Australian continent with N t values up to about 35 km-2yr-1. Ground flash density (Ng) values vary from over 6 km-2yr-1 in the northern parts of Australia to about 1 km-2 yr-1 and below in the southern parts. There are significant seasonal and yearly variations in the frequency of thunderdays. Some aspects of the hazards from thunderstorms and lightning appear to be special to Australia, including lightning initiated wildfires, lightning injuries to telephone users and faults on power lines caused by high wind gust speeds.
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A recently updated Average Annual Thunder-Day Map for Australia is presented. On the basis of this map, the distribution of thunderstorms over Australia is analysed in terms of the factors required for storm development. Thunderstorms are most frequent over the northern half of the country, and generally decrease southward, with lowest frequencies in southeast Tasmania. A secondary maximum is also apparent in southeast Queensland and over central and eastern New South Wales, extending into the northeastern Victorian highlands. Thunderstorm frequency does not, in general, appear to vary in any consistent way with rainfall. There appears to be no evidence of any widespread temporal trend in thunderstorm frequency.
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The spatial distribution of deep convection in the greater Sydney area is examined. The primary source of data is the incoherent, broadbeam 10 cm radar at Sydney's Mascot Airport. For 25 years significant storm cells on the radar screen were manually logged. A composite storm cell density map is produced. Under certain assumptions, this map can be converted to a storm probability distribution. Such distribution can be produced for any subset of the entire database (e.g. a given time of the day), and the anomalous storm probability under the conditions of the subset can be examined. We focus on anomaly maps for a set of six synoptic situations in which thunderstorms occur most commonly. These synoptic classes are defined solely on the basis of mean sea-level pressure (MSLP) patterns, because MSLP charts are available at the highest time and space resolution, and because MSLP, via its relation to the low-level flow, is an important synoptic-scale discriminant for local storm distribution. We find that in some areas the low-level flow has a significant impact on storm distribution. These anomaly maps directly link the local storm predictability to the regional weather predictability. The results are compared to data from much more recent, more objective but climatologically inadequate alternative data sources: automatically recorded significant radar echoes, a lightning network, and a storm spotters network. While the comparison is difficult, some basic patterns are verified.
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In previous studies published in the open literature, a strong relationship between the occurrence of hail and the microwave brightness temperatures (primarily at 37 and 85 GHz) was documented. These studies were performed with the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and most recently, the Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sensor. This led to climatologies of hail frequency from TMI and AMSR-E, however, limitations included geographical domain of the TMI sensor (35 S to 35 N) and the overpass time of the Aqua satellite (130 am/pm local time), both of which reduce an accurate mapping of hail events over the global domain and the full diurnal cycle. Nonetheless, these studies presented exciting, new applications for passive microwave sensors.
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The El Niño/Southern Oscillation (ENSO) is characterized by changes in sea surface temperature (SST) and atmospheric convection in the tropical Pacific, and modulates global weather and climate. The phase of ENSO influences United States (US) temperature and precipitation and has long been hypothesized to influence severe thunderstorm occurrence over the US. However, limitations of the severe thunderstorm observational record, combined with large year-to-year variability, have made it difficult to demonstrate an ENSO influence during the peak spring season. Here we use environmental indices that are correlated with tornado and hail activity, and show that ENSO modulates tornado and hail occurrence during the winter and spring by altering the large-scale environment. We show that fewer tornadoes and hail events occur over the central US during El Niño and conversely more occur during La Niña conditions. Moreover, winter ENSO conditions often persist into early spring, and consequently the winter ENSO state can be used to predict changes in tornado and hail frequency during the following spring. Combined with our current ability to predict ENSO several months in advance, our findings provide a basis for long-range seasonal prediction of severe thunderstorm activity.
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High-resolution dynamical downscaling is used to explore 2080-2090 peak-season hazardous convective weather as simulated from the Community Climate System Model version 3. Downscaling to 4 km grid spacing is performed using the Weather Research and Forecasting model. Tornadoes, damaging wind gusts, and large hail are simulated using a model proxy at hourly intervals for locations east of the U.S. Continental Divide. Future period results are placed into context using 1980-1990 output. While a limited sample size exists, a statistically significant increase in synthetic severe weather activity is noted in March, whereas event frequency is shown to slightly increase in April, and stay the same in May. These increases are primarily found in the Mississippi, Tennessee, and Ohio River valleys. Diurnally, most of the increase in hazardous convective weather activity is shown to be in the hours surrounding local sunset. Peak-season severe weather is also shown to be more variable in the future with a skewed potential toward larger counts. Finally, modeled proxy events are compared to environmental parameters known to generate hazardous convective weather activity. These environmental conditions explain over 80 % of the variance associated with modeled reports during March-May and show an increasing future tendency. Finally, challenges associated with dynamical downscaling for purposes of resolving severe local storms are discussed.
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From data gathered on twenty hailstorms which severely damaged pine plantations in various parts of Australia during the past decade, and from a review of the literature, an analysis is presented of the nature and effects of hail damage on Pinus radiata and Pinus elliottii.Meterorological data from Australia indicate that plantations in this country are likely to experience about two physically damaging hailstorms per 35-year rotation, and scars left by the impact of hailstones tend to confirm this.Hailstones knocked needle fascicles and thin shoots off the trees and thus caused up to 70% defoliation. They also killed 1–4 cm wide patches of bark and cambium where the bark was thin, i.e. on limbs, and the top 6–12 m of the stem. More serious damage resulted when these physical injuries were followed by shoot dieback associated with infection by Diplodia pinea. Except for vigorous young (<6 yr) plants, all classes of trees were susceptible to the dieback, largely irrespective of dominance, vigour, site quality, stand density and drought stress. Many trees died, but most recovered in about 2 to 4 years. Those that had lost several metres of their leader developed badly deformed stems.During 1971–80, dieback necessitated the salvage of about 100 000 m−1 of stem wood per year, i.e. about 3.6% of the total harvests.
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A brief discussion is presented of five aspects which must be considered when planning an aerial photographic mission to map mechanical hail damage of pine plantations per se or the subsequent dieback due to infection by Diplodea pinea. These are the timing of photography, the film, scale and format to be used and the likely costs. A number of recommendations are made which will enable forest managers to prescribe a suitable aerial survey of any particular damage event.
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From Australia-wide surveys, forestry records and studies of major events of storm damage, a first comprehensive assessment is presented of the nature and incidence of damage caused by wind, snow and hail storms in Australian plantations of pines, mainly Pinus radiata. The main types of damage by wind and snow are the uprooting of trees, the tilting of saplings and trees and the bending or breakage of stems and branches. Wind may also abrade and strip the foliage or desiccate the crowns. The physical impact of hailstones damages the bark and cambium on limbs and the upper trunk, and detaches foliage and foliar shoots. This is sometimes followed by dieback of the crown and even death of trees, usually associated with infection by Diplodia pinea.