Time variation effects of weather conditions in rural MUSA-MIMO-OFDM channels

This paper presents channel measurements and weather data collection experiments conducted in a rural environment for an innovative Multi-User-Single-Antenna (MUSA) MIMO-OFDM technology, proposed for rural areas. MUSA MIMO-OFDM uplink channels are established by placing six user terminals (UT) around one access point (AP). Generated terrain profiles and relative received power plots are presented based on the experimental data. According to the relative received signal, MUSA-MIMO-OFDM uplink channels experience temporal fading. Moreover, the correlation between the relative received power and weather variables are presented. Results show that all weather variables exhibit a negative average correlation with received power. Wind speed records the highest average negative correlation coefficient of -0.35. Local maxima of negative correlation, ranging from 0.49 to 0.78, between the weather variables and relative received signals were registered between 5-6 a.m. The highest measured correlation (-0.78) of this time of the day was exhibited by wind speed. These results show the extend of time variation effects experienced by MUSA-MIMO-OFDM channels deployed in rural environments.

Motorcycle protective clothing : protection from injury or just the weather?

Background Apart from helmets, little is known about the effectiveness of motorcycle protective clothing in reducing injuries in crashes. The study aimed to quantify the association between usage of motorcycle clothing and injury in crashes. Methods and findings Cross-sectional analytic study. Crashed motorcyclists (n = 212, 71% of identified eligible cases) were recruited through hospitals and motorcycle repair services. Data was obtained through structured face-to-face interviews. The main outcome was hospitalization and motorcycle crash-related injury. Poisson regression was used to estimate relative risk (RR) and 95% confidence intervals for injury adjusting for potential confounders. Results Motorcyclists were significantly less likely to be admitted to hospital if they crashed wearing motorcycle jackets (RR = 0.79, 95% CI: 0.69–0.91), pants (RR = 0.49, 95% CI: 0.25–0.94), or gloves (RR = 0.41, 95% CI: 0.26–0.66). When garments included fitted body armour there was a significantly reduced risk of injury to the upper body (RR = 0.77, 95% CI: 0.66–0.89), hands and wrists (RR = 0.55, 95% CI: 0.38–0.81), legs (RR = 0.60, 95% CI: 0.40–0.90), feet and ankles (RR = 0.54, 95% CI: 0.35–0.83). Non-motorcycle boots were also associated with a reduced risk of injury compared to shoes or joggers (RR = 0.46, 95% CI: 0.28–0.75). No association between use of body armour and risk of fracture injuries was detected. A substantial proportion of motorcycle designed gloves (25.7%), jackets (29.7%) and pants (28.1%) were assessed to have failed due to material damage in the crash. Conclusions Motorcycle protective clothing is associated with reduced risk and severity of crash related injury and hospitalization, particularly when fitted with body armour. The proportion of clothing items that failed under crash conditions indicates a need for improved quality control. While mandating usage of protective clothing is not recommended, consideration could be given to providing incentives for usage of protective clothing, such as tax exemptions for safety gear, health insurance premium reductions and rebates.

Sensitivity of building cooling loads to future weather predictions

The interaction and relationship between the global warming and the thermal performance buildings are dynamic in nature. In order to model and understand this behavior, different approaches, including keeping weather variable unchanged, morphing approach and diurnal modelling method, have been used to project and generate future weather data. Among these approaches, various assumptions on the change of solar radiation, air humidity and/or wind characteristics may be adopted. In this paper, an example to illustrate the generation of future weather data for the different global warming scenarios in Australia is presented. The sensitivity of building cooling loads to the possible changes of assumed values used in the future weather data generation is investigated. It is shown that with ± 10% change of the proposed future values for solar radiation, air humidity or wind characteristics, the corresponding change in the cooling load of the modeled sample office building at different Australian capital cities would not exceed 6%, 4% and 1.5% respectively. It is also found that with ±10% changes on the proposed weather variables for both the 2070-high future scenario and the current weather scenario, the corresponding change in the cooling loads at different locations may be weaker (up to 2% difference in Hobart for ±10% change in global solar radiation), similar (less than 0.6%) difference in Hobart for ±10% change in wind speed), or stronger (up to 1.6% difference in Hobart for ±10% change in relative humidity) in the 2070-high future scenario than in the current weather scenario.

Profiling and characterisation of key weather variables and their implication on building design

Local climate is a critical element in the design of buildings. In this paper, ten years of historical weather data in Australia's all eight capital cities are analyzed to characterize the variation profiles of climatic variables. The method of descriptive statistics is employed. Either the pattern of cumulative distribution and/or the profile of percentage distribution are used to graphically illustrate the similarity and difference between different study locations. It is found that although the weather variables vary with different locations, except for the extreme parts, there is often a good, nearly linear relation between weather variable and its cumulative percentage for the majority of middle part. The implication of these extreme parts and the slopes of the middle parts on building design is also discussed.

Analysis of ten years historical weather data in Australia

Typical reference year (TRY) weather data is often used to represent the long term weather pattern for building simulation and design. Through the analysis of ten year historical hourly weather data for seven Australian major capital cities using the frequencies procedure of descriptive statistics analysis (by SPSS software), this paper investigates: • the closeness of the typical reference year (TRY) weather data in representing the long term weather pattern; • the variations and common features that may exist between relatively hot and cold years. It is found that for the given set of input data, in comparison with the other weather elements, the discrepancy between TRY and multiple years is much smaller for the dry bulb temperature, relative humidity and global solar irradiance. The overall distribution patterns of key weather elements are also generally similar between the hot and cold years, but with some shift and/or small distortion. There is little common tendency of change between the hot and the cold years for different weather variables at different study locations.

Considering weather in simulation traffic

The impact of weather on traffic and its behavior is not well studied in literature primarily due to lack of integrated traffic and weather data. Weather can significant effect the traffic and traffic management measures developed for fine weather might not be optimal for adverse weather. Simulation is an efficient tool for analyzing traffic management measures even before their actual implementation. Therefore, in order to develop and test traffic management measures for adverse weather condition we need to first analyze the effect of weather on fundamental traffic parameters and thereafter, calibrate the simulation model parameters in order to simulate the traffic under adverse weather conditions. In this paper we first, analyses the impact of weather on motorway traffic flow and drivers’ behaviour with traffic data from Swiss motorways and weather data from MeteoSuisse. Thereafter, we develop methodology to calibrate a microscopic simulation model with the aim to utilize the simulation model for simulating traffic under adverse weather conditions. Here, study is performed using AIMSUN, a microscopic traffic simulator.

Living through extreme weather events and natural disasters: How resilient are our high-rise high-density typologies?

The inner city Brisbane suburbs of the West End peninsula are poised for redevelopment. Located within walking distance to CBD workplaces, home to Queensland’s highest value cultural precinct, and high quality riverside parklands, there is currently a once-in-a-lifetime opportunity to redevelop parts of the suburb to create a truly urban neighbourhood. According to a local community association, local residents agree and embrace the concept of high-density living, but are opposed to the high-rise urban form (12 storeys) advocated by the City’s planning authority (BCC, 2011) and would prefer to see medium-rise (5-8 storeys) medium-density built form. Brisbane experienced a major flood event which inundated the peninsula suburbs of West End in summer January 2011. The vulnerability of taller buildings to the vagaries of climate and more extreme weather events and their reliance on main electricity was exposed when power outages immediately before, during and after the flood disaster seriously limited occupants’ access and egress when elevators were disabled. Not all buildings were flooded but dwellings quickly became unliveable due to disabled air-conditioning. Some tall buildings remained uninhabitable for several weeks after the event. This paper describes an innovative design research method applied to the complex problem of resilient, sustainable neighbourhood form in subtropical cities, in which a thorough comparative analysis of a range of multiple-dwelling types has revealed the impact that government policy regarding design of the physical environment has on a community’s resilience. The outcomes advocate the role of climate-responsive design in averting the rising human capital and financial costs of natural disasters and climate change.

Heavy Weather

Heavy Weather was a monumental sculptural work produced for the prestigious McClelland National Sculpture Survey in 2012. The work was a large cold-cast aluminium figure depicting the artist in athletic costume arching backwards across the top of massive boulder. The pose of the figure was derived from the ‘Fosbury flop’, the awkward backwards manoeuvre associated with high-jump event. The boulder was a portrait of a different kind - a remake of the Ian Fairweather memorial on Bribie Island but elongated to tower upwards. The work thus emphasised two contrasting impressions of movement – immense inertia and writhing agility. Heavy Weather sought to bring these two opposing forces together as a way of representing the tensions that shape our relationship with objects. In so doing, the work contributed to the artist’s ongoing exploration of sculpture, self-portraiture and the civic monument. The work was promoted nationally including the Art Guide and the Melbourne Review. It was also the subject of a article in the Australian Art Collector.

Non-contact ACL injuries : association with clegg soil impact test values for sports fields, soil moisture and prevailing weather

Introduction: There is a recognised relationship between dry weather conditions and increased risk of anterior cruciate ligament (ACL) injury. Previous studies have identified 28 day evaporation as an important weather-based predictor of non-contact ACL injuries in professional Australian Football League matches. The mechanism of non-contact injury to the ACL is believed to increased traction and impact forces between footwear and playing surface. Ground hardness and the amount and quality of grass are factors that would most likely influence this and are inturn, related to the soil moisture content and prevailing weather conditions. This paper explores the relationship between soil moisture content, preceding weather conditions and the Clegg Soil Impact Test (CSIT) which is an internationally recognised standard measure of ground hardness for sports fields. Methodology: The 2.25 kg Clegg Soil Impact Test and a pair of 12 cm soil moisture probes were used to measure ground hardness and percentage moisture content. Five football fields were surveyed at 13 prescribed sites just before seven football matches from October 2008 to January 2009 (an FC Women’s WLeague team). Weather conditions recorded at the nearest weather station were obtained from the Bureau of Meteorology website and total rainfall less evaporation was calculated for 7 and 28 days prior to each match. All non-contact injuries occurring during match play and their location on the field were recorded. Results/conclusions: Ground hardness varied between CSIT 5 and 17 (x10G) (8 is considered a good value for sports fields). Variations within fields were typically greatest in the centre and goal areas. Soil moisture ranged from 3 to 40% with some fields requiring twice the moisture content of others to maintain similar CSIT values. There was a non-linear, negative relationship for ground hardness versus moisture content and a linear relationship with weather (R2, of 0.30 and 0.34, respectively). Three non-contact ACL injuries occurred during the season. Two of these were associated with hard and variable ground conditions.

A closed-form approximation for pricing temperature-based weather derivatives

This paper develops analytical distributions of temperature indices on which temperature derivatives are written. If the deviations of daily temperatures from their expected values are modelled as an Ornstein-Uhlenbeck process with timevarying variance, then the distributions of the temperature index on which the derivative is written is the sum of truncated, correlated Gaussian deviates. The key result of this paper is to provide an analytical approximation to the distribution of this sum, thus allowing the accurate computation of payoffs without the need for any simulation. A data set comprising average daily temperature spanning over a hundred years for four Australian cities is used to demonstrate the efficacy of this approach for estimating the payoffs to temperature derivatives. It is demonstrated that expected payoffs computed directly from historical records are a particularly poor approach to the problem when there are trends in underlying average daily temperature. It is shown that the proposed analytical approach is superior to historical pricing.

Diffusion of extreme weather-proofing technology in the built environment

This study addresses the research question: ‘What are the diffusion determinants for extreme weather-proofing technology in the Australian built environment?’ In order to effectively identify diffusion determinants, a synthesis of literature in both technical and management fields was conducted from a system-wide perspective. Review results where then interpreted through an innovation system framework, drawn from innovation systems literature, in order to map the current state of extreme weather-proofing technology diffusion in the Australian built environment industry. Drivers and obstacles to optimal diffusion are presented. Results show the important role to be played by Australian governments in facilitating improved weather proofing technology diffusion. This applies to governments in their various roles, but particularly as regulators, clients/owners and investors in research & development and education. In the role as regulators, findings suggest Australian governments should be encouraging the application of innovative finance options and positive end-user incentives to promote the uptake of weather proofing technology. Additionally, in their role as clients/owners, diffusion can be improved by adjusting building and infrastructure specifications to encourage designers and constructors to incorporate extreme weather proofing technology in new and redeveloped built assets. Finally, results suggest greater investment is required in research and development and improved knowledge sharing across the construction supply chain to further mitigate risks associated with greater incidences of extreme weather events.

A threshold analysis of dengue transmission in terms of weather variables and imported dengue cases in Australia

Dengue virus (DENV) transmission in Australia is driven by weather factors and imported dengue fever (DF) cases. However, uncertainty remains regarding the threshold effects of high-order interactions among weather factors and imported DF cases and the impact of these factors on autochthonous DF. A time-series regression tree model was used to assess the threshold effects of natural temporal variations of weekly weather factors and weekly imported DF cases in relation to incidence of weekly autochthonous DF from 1 January 2000 to 31 December 2009 in Townsville and Cairns, Australia. In Cairns, mean weekly autochthonous DF incidence increased 16.3-fold when the 3-week lagged moving average maximum temperature was <32 °C, the 4-week lagged moving average minimum temperature was ≥24 °C and the sum of imported DF cases in the previous 2 weeks was >0. When the 3-week lagged moving average maximum temperature was ≥32 °C and the other two conditions mentioned above remained the same, mean weekly autochthonous DF incidence only increased 4.6-fold. In Townsville, the mean weekly incidence of autochthonous DF increased 10-fold when 3-week lagged moving average rainfall was ≥27 mm, but it only increased 1.8-fold when rainfall was <27 mm during January to June. Thus, we found different responses of autochthonous DF incidence to weather factors and imported DF cases in Townsville and Cairns. Imported DF cases may also trigger and enhance local outbreaks under favorable climate conditions.

Imported Dengue cases, weather variation and autochthonous Dengue incidence in Cairns, Australia

BACKGROUND Dengue fever (DF) outbreaks often arise from imported DF cases in Cairns, Australia. Few studies have incorporated imported DF cases in the estimation of the relationship between weather variability and incidence of autochthonous DF. The study aimed to examine the impact of weather variability on autochthonous DF infection after accounting for imported DF cases and then to explore the possibility of developing an empirical forecast system. METHODOLOGY/PRINCIPAL FINDS Data on weather variables, notified DF cases (including those acquired locally and overseas), and population size in Cairns were supplied by the Australian Bureau of Meteorology, Queensland Health, and Australian Bureau of Statistics. A time-series negative-binomial hurdle model was used to assess the effects of imported DF cases and weather variability on autochthonous DF incidence. Our results showed that monthly autochthonous DF incidences were significantly associated with monthly imported DF cases (Relative Risk (RR):1.52; 95% confidence interval (CI): 1.01-2.28), monthly minimum temperature ((o)C) (RR: 2.28; 95% CI: 1.77-2.93), monthly relative humidity (%) (RR: 1.21; 95% CI: 1.06-1.37), monthly rainfall (mm) (RR: 0.50; 95% CI: 0.31-0.81) and monthly standard deviation of daily relative humidity (%) (RR: 1.27; 95% CI: 1.08-1.50). In the zero hurdle component, the occurrence of monthly autochthonous DF cases was significantly associated with monthly minimum temperature (Odds Ratio (OR): 1.64; 95% CI: 1.01-2.67). CONCLUSIONS/SIGNIFICANCE Our research suggested that incidences of monthly autochthonous DF were strongly positively associated with monthly imported DF cases, local minimum temperature and inter-month relative humidity variability in Cairns. Moreover, DF outbreak in Cairns was driven by imported DF cases only under favourable seasons and weather conditions in the study.

Managing health risks of extreme weather events : need for a systematic approach

The Climate Commission recently outlined the trend of major extreme weather events in different regions of Australia, including heatwaves, floods, droughts, bushfires, cyclones and storms. These events already impose an enormous health and financial burden onto society and are projected to occur more frequently and intensely. Unless we act now, further financial losses and increasing health burdens seem inevitable. We seek to highlight the major areas for interdisciplinary investigation, identify barriers and formulate response strategies.