scholarly journals Modelling average maximum daily temperature using r largest order statistics: An application to South African data

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Murendeni M. Nemukula ◽  
Caston Sigauke
Keyword(s):  
South Africa ◽  
Order Statistics ◽  
South African ◽  
Heat Waves ◽  
Value Theory ◽  
Extreme Value ◽  
Daily Temperature ◽  
Diagnostic Tools ◽  
Maximum Daily Temperature ◽  
Average Maximum

Natural hazards (events that may cause actual disasters) are established in the literature as major causes of various massive and destructive problems worldwide. The occurrences of earthquakes, floods and heat waves affect millions of people through several impacts. These include cases of hospitalisation, loss of lives and economic challenges. The focus of this study was on the risk reduction of the disasters that occur because of extremely high temperatures and heat waves. Modelling average maximum daily temperature (AMDT) guards against the disaster risk and may also help countries towards preparing for extreme heat. This study discusses the use of the r largest order statistics approach of extreme value theory towards modelling AMDT over the period of 11 years, that is, 2000–2010. A generalised extreme value distribution for r largest order statistics is fitted to the annual maxima. This is performed in an effort to study the behaviour of the r largest order statistics. The method of maximum likelihood is used in estimating the target parameters and the frequency of occurrences of the hottest days is assessed. The study presents a case study of South Africa in which the data for the non-winter season (September–April of each year) are used. The meteorological data used are the AMDT that are collected by the South African Weather Service and provided by Eskom. The estimation of the shape parameter reveals evidence of a Weibull class as an appropriate distribution for modelling AMDT in South Africa. The extreme quantiles for specified return periods are estimated using the quantile function and the best model is chosen through the use of the deviance statistic with the support of the graphical diagnostic tools. The Entropy Difference Test (EDT) is used as a specification test for diagnosing the fit of the models to the data.

Stochastic comparison of parallel systems with Pareto components

2021 ◽  
pp. 1-13
Author(s):  
Sameen Naqvi ◽  
Weiyong Ding ◽  
Peng Zhao
Keyword(s):  
Order Statistics ◽  
Extreme Value Theory ◽  
Pareto Distribution ◽  
Parallel Systems ◽  
Value Theory ◽  
Extreme Value ◽  
Stochastic Comparison ◽  
Shape Parameters ◽  
Scale Parameters ◽  
Dispersive Ordering

Abstract Pareto distribution is an important distribution in extreme value theory. In this paper, we consider parallel systems with Pareto components and study the effect of heterogeneity on skewness of such systems. It is shown that, when the lifetimes of components have different shape parameters, the parallel system with heterogeneous Pareto component lifetimes is more skewed than the system with independent and identically distributed Pareto components. However, for the case when the lifetimes of components have different scale parameters, the result gets reversed in the sense of star ordering. We also establish the relation between star ordering and dispersive ordering by extending the result of Deshpande and Kochar [(1983). Dispersive ordering is the same as tail ordering. Advances in Applied Probability 15(3): 686–687] from support $(0, \infty )$ to general supports $(a, \infty )$ , $a > 0$ . As a consequence, we obtain some new results on dispersion of order statistics from heterogeneous Pareto samples with respect to dispersive ordering.

scholarly journals Heatwaves in the Future Warmer Climate of South Africa

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 712
Author(s):  
Innocent Mbokodo ◽  
Mary-Jane Bopape ◽  
Hector Chikoore ◽  
Francois Engelbrecht ◽  
Nthaduleni Nethengwe
Keyword(s):  
Climate Change ◽  
South Africa ◽  
Greenhouse Gas ◽  
Greenhouse Gas Emission ◽  
Heat Waves ◽  
Future Climate ◽  
Future Climate Change ◽  
South African Society ◽  
Average Maximum ◽  
The Future

Weather and climate extremes, such as heat waves (HWs), have become more frequent due to climate change, resulting in negative environmental and socioeconomic impacts in many regions of the world. The high vulnerability of South African society to the impacts of warm extreme temperatures makes the study of the effect of climate change on future HWs necessary across the country. We investigated the projected effect of climate change on future of South Africa with a focus on HWs using an ensemble of regional climate model downscalings obtained from the Conformal Cubic Atmospheric Model (CCAM) for the periods 2010–2039, 2040–2069, and 2070–2099, with 1983–2012 as the historical baseline. Simulations were performed under the Representative Concentration Pathway (RCP) 4.5 (moderate greenhouse gas (GHG) concentration) and 8.5 (high GHG concentration) greenhouse gas emission scenarios. We found that the 30-year period average maximum temperatures may rise by up to 6 °C across much of the interior of South Africa by 2070–2099 with respect to 1983–2012, under a high GHG concentration. Simulated HW thresholds for all ensemble members were similar and spatially consistent with observed HW thresholds. Under a high GHG concentration, short lasting HWs (average of 3–4 days) along the coastal areas are expected to increase in frequency in the future climate, however the coasts will continue to experience HWs of relatively shorter duration compared to the interior regions. HWs lasting for shorter duration are expected to be more frequent when compared to HWs of longer durations (over two weeks). The north-western part of South Africa is expected to have the most drastic increase in HWs occurrences across the country. Whilst the central interior is not projected to experience pronounced increases in HW frequency, HWs across this region are expected to last longer under future climate change. Consistent patterns of change are projected for HWs under moderate GHG concentrations, but the changes are smaller in amplitude. Increases in HW frequency and duration across South Africa may have significant impacts on human health, economic activities, and livelihoods in vulnerable communities.

scholarly journals Extreme Value Theory Applied to r Largest Order Statistics Under the Bayesian Approach

2019 ◽  
Vol 42 (2) ◽  
pp. 143-166 ◽  
Author(s):  
Renato Santos Silva ◽  
Fernando Ferraz Nascimento
Keyword(s):  
Monte Carlo ◽  
Order Statistics ◽  
Bayesian Approach ◽  
Extreme Value Theory ◽  
Likelihood Estimation ◽  
Value Theory ◽  
Extreme Value ◽  
Environmental Data ◽  
Heavy Tailed ◽  
The Bayesian Approach

Extreme Value Theory (EVT) is an important tool to predict efficient gains and losses. Its main areas of analyses are economic and environmental. Initially, for that form of event, it was developed the use of patterns of parametric distribution such as Normal and Gamma. However, economic and environmental data presents, in most cases, a heavy-tailed distribution, in contrast to those distributions. Thus, it was faced a great difficult to frame extreme events. Furthermore, it was almost impossible to use conventional models, making predictions about non-observed events, which exceed the maximum of observations. In some situations EVT is used to analyse only the maximum of some dataset, which provide few observations, and in those cases it is more effective to use the r largest-order statistics. This paper aims to propose Bayesian estimators' for parameters of the r largest-order statistics. During the research, it was used Monte Carlo simulation to analyze the data, and it was observed some properties of those estimators, such as mean, variance, bias and Root Mean Square Error (RMSE). The estimation of the parameters provided inference for its parameters and return levels. This paper also shows a procedure to the choice of the r-optimal to the r largest-order statistics, based on the Bayesian approach applying Markov chains Monte Carlo (MCMC). Simulation results reveal that the Bayesian approach has a similar performance to the Maximum Likelihood Estimation, and the applications were developed using the Bayesian approach and showed a gain in accurary compared with otherestimators.

CORRELATION COMMUNICATION BETWEEN METEOROLOGICAL PARAMETERS AT EXTREME VALUES OF MAXIMUM AIR TEMPERATURES

2020 ◽  
pp. 101-112
Author(s):  
S.V. Savchuk ◽  
V.E. Timofeev ◽  
O.A. Shcheglov ◽  
V.A. Artemenko ◽  
I.L. Kozlenko
Keyword(s):  
Air Temperature ◽  
Meteorological Parameters ◽  
Extreme Values ◽  
Daily Temperature ◽  
Sea Level Pressure ◽  
Maximum Daily Temperature ◽  
The North ◽  
Air Temperatures ◽  
Average Maximum ◽  
Maximum Air Temperature

The object of the study is the maximum daily air temperature during the months of the year over 1991-2016 by the data of 186 meteorological stations of Ukraine. Extreme values of the maximum daily temperature equal to or exceeded their 95th (Tmax95p and above, ºС) percentile were taken as extreme. The article sets the dates (137 cases) of extreme values of maximum air temperature on more than 60 % of the territory. For these dates, 13 meteorological parameters were selected: average, minimum, and maximum air temperatures; average, minimum and maximum relative humidity; station and sea-level pressure; average, maximum (from 8 synoptic hours) wind speed; rainfall; height of snow cover. The purpose of this work is to determine the correlation coefficient (K), in particular, statistically significant (K≤-0.6, K≥0.6), on these dates between selected meteorological parameters at 186 meteorological stations of Ukraine for 1991-2013. The density of the cases of statistically significant dependence between the meteorological parameters in extremely warm days in separate seasons is determined. In extremely warm days, meteorological parameters and areas with statistically significant correlations at K≤-0.6 were detected: T and F (focally in southern and some western regions with significant density) − in winter; T and F (with the highest density ubiquitous or almost ubiquitous), P and V (in a large number of regions, usually west or right-bank, but with less frequency) − in the transition seasons, and in the autumn between − T and F (in the south with smaller density) and P and F (in some areas of the north, northwest, west, lower east). In all seasons, such a correlation between other meteorological parameters had a focal distribution, usually with a smaller density. In these days, a focal distribution with a small frequency of dependencies at K≥0.6 was found between the meteorological parameters detected (F and V in transition seasons, T and F in winter), except for similar ones. However, such dependence is observed between T and V in some regions in winter and autumn and in some areas of south, southeast, east with a smaller density. The study of the maximum daily temperature is relevant, because from the level of natural hydrometeorological phenomena it is accompanied by dangerous phenomena, negatively affecting the weather dependent industries.

scholarly journals Implementing novel regimens for drug-resistant TB in South Africa: what can the world learn?

2020 ◽  
Vol 24 (10) ◽  
pp. 1073-1080
Author(s):  
N. Ndjeka ◽  
J. Hughes ◽  
A. Reuter ◽  
F. Conradie ◽  
M. Enwerem ◽  
...  
Keyword(s):  
South Africa ◽  
South African ◽  
Recent Change ◽  
New Drugs ◽  
Diagnostic Tools ◽  
Who Guidelines ◽  
Policy Changes ◽  
Close Collaboration ◽  
Resistant Tuberculosis ◽  
Global Leader

Worldwide uptake of new drugs in the treatment of rifampicin-resistant tuberculosis (RR-TB) has been extremely low. In June 2018, ahead of the release of the updated WHO guidelines for the management of RR-TB, South Africa announced that bedaquiline (BDQ) would be provided to virtually all RR-TB patients on shorter or longer regimens. South Africa has been the global leader in accessing BDQ for patients with RR-TB, who now represent 60% of the global BDQ cohort. The use of BDQ within a shorter modified regimen has generated the programmatic data underpinning the most recent change in WHO guidelines endorsing a shorter, injectable-free regimen. Progressive policies on access to new drugs have resulted in improved favourable outcomes and a reduction in mortality among RR-TB patients in South Africa. This supported global policy change. The strategies underpinning these bold actions include close collaboration between the South African National TB Programme and partners, introduction of new TB diagnostic tools in closely monitored conditions and the use of locally generated programmatic evidence to inform country policy changes. In this paper, we summarise a decade´s work that led to the bold decision to use a modified, short, injectable-free regimen with BDQ and linezolid under carefully monitored programmatic conditions.

scholarly journals Significant Factors Influencing Quality Assurance Practices in Small and Medium-Sized Construction Projects in South Africa

2019 ◽  
Vol 11 (2(J)) ◽  
pp. 30-44
Author(s):  
Kgashane Stephen Nyakala ◽  
Thinandavha Thomas Munyai ◽  
Jan-Harm Pretorius ◽  
Andre Vermeulen
Keyword(s):  
South Africa ◽  
Quality Assurance ◽  
South African ◽  
Financial Management ◽  
Construction Projects ◽  
Project Planning ◽  
Diagnostic Tools ◽  
Research Approach ◽  
Road Building ◽  
Factors Influencing

Although implementing quality assurance (QA) processes in construction play an important role in the South African economy has been acknowledged. However, constructions SMEs are faced with difficulties in improving rural road infrastructure and high-quality roads. Additionally, past research has failed to reach consensus on the construction process and socioeconomic settings in previously disadvantaged areas in South Africa, including the factors influencing negatively the performance of such factors. This research examines what factors facilitate or inhibit the success of construction SMEs and what actions can be taken to being distressed construction SMEs under control. The study adopted a quantitative research approach in which a three-section questionnaire was administered to 160 purposively chosen road- building experts in a South African construction SMEs. The questionnaire was structured into three parts, which sought the participants’ profile, identified the quality assurance practices (QAPs) incorporated in the construction SMEs’ road building programmes, and identified the factors that negatively influence the implementation of QA processes. Data was analysed using the Statistical Package for the Social Sciences (SPSS) version 22. Furthermore, to determine the reliability of the various constructs, mean scores, descriptive statistics and standard deviations were obtained. The empirical findings established eight QAPs that were reliable and valid for implementation processes that can control or minimise their causes of poor quality in projects undertaken by construction SMEs, level of skill acquisition; project planning and control techniques; project construction design; process implementation and process improvement; financial management; organisational structures; involvement of people; and quality standards and measurements. The eight factors attained high Cronbach Alpha values above the recommended 0.70 which indicates high internal consistencies among the sub-scales. Findings from this study should be useful to managers in similar environments may use the results of this study as either diagnostic tools or as a reference benchmark for strategic interventions in solving construction projects related problems. Furthermore, the researchers also recommend that these practices are for quality assurance in construction projects undertaken by SMEs in South Africa.

scholarly journals Statistical classification of South African seasonal divisions on the basis of daily temperature data

2020 ◽  
Vol 116 (9/10) ◽  
Author(s):  
Adriaan J. van der Walt ◽  
Jennifer M. Fitchett
Keyword(s):  
South Africa ◽  
South African ◽  
Ad Hoc ◽  
Temperature Data ◽  
Daily Temperature ◽  
Daily Maximum ◽  
Data Sets ◽  
Wide Range ◽  
African Context ◽  
June July

Across South Africa, a wide range of activities is influenced by differences in seasonality. In a South African context, there is little consensus on the timing of seasonal boundaries. Inconsistency exists through the use of ad-hoc approaches to define seasonal boundaries across South Africa. In this paper, we present one of the very first uniform statistical classifications of South African seasonal divisions on the basis of daily temperature data. Daily maximum and minimum temperature data were obtained from 35 selected South African Weather Service meteorological stations that had sufficiently complete data sets and homogeneous time series, spanning the period 1980–2015. An Euclidean cluster analysis was performed using Ward’s D method. We found that the majority of the stations can be classified into four distinct seasons, with the remaining 12 stations’ data best classified into three seasons, using Tavg as the classifier. The statistically classified seasonal brackets include summer (October/November/December/ January/February/March), early autumn (April) and late autumn (May), winter (June/July/August), and spring (September). Exploring the boundaries of seasons, the start of summer and end of winter months follow a southwest to northeastwards spatial pattern across the country. Summers start later and winters end later in the southwestern parts of the country, whereas in the northeast, summers start earlier and winters end earlier.

scholarly journals Tornadoes in South Africa: An Overview with a Case Study

2018 ◽  
Author(s):  
Offoro Kimambo
Keyword(s):  
South Africa ◽  
South African ◽  
Heat Waves ◽  
Warning System ◽  
Study Data ◽  
Study Analysis ◽  
Case Study Approach ◽  
Case Study Analysis ◽  
Study Approach

This paper contributes to the understating of tornadoes in South Africa using case study analysis. In South Africa tornadoes are the recurring phenomenon (the climatology) but they have received less attention. Damages from storms itself (tornadoes inclusive) are significant in South Africa relative to other weather-related disasters for example floods, heat waves, and droughts. Case study approach was adopted in the current study. Data were in the courtesy of the following, National Oceanic and Administration (NOOA), National Centers for Environmental Protections (NCEP), Eumetsat, and South African weather Service. The aim of the study was to provide an overview of the occurrence of tornadoes in South Africa using a case study. From the case study analysis, the tornadoes at Klerksdorp on March 4, 2007, was associated with the cold frontal systems and the cut-ff low (extratropical circulation) which were the dominant weather systems of the day. Case study approach may be the best way to study events of these nature for a more informed decision, for example, issuing an early warning system.  Case studies, for example, involving interaction between extratropical and tropical circulation may be also more informative.

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