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12 October 2020 | Story Leonie Bolleurs | Photo Supplied
Adriaan van der Walt
Although several international studies have used temperature metrics to statistically classify their seasonal divisions, a study in which Adriaan van der Walt was involved, would be the first known publication in a South African context using temperature as classification metric.

Gone are the days when we as South Africans would experience a three-month spring season, easing into summer, and then cooling off for three months before we hit winter.

Adriaan van der Walt, Lecturer in the Department of Geography at the University of the Free State (UFS), focuses his research on biometeorology (a specialist discipline exploring the role and climate change in physical and human environments) as well as climatology and geographic information systems.

He recently published an article: ‘Statistical classification of South African seasonal divisions on the basis of daily temperature data’ in the South African Journal of Science.

In this study, which Van der Walt undertook with Jennifer Fitchett, a colleague from the University of the Witwatersrand, data on daily maximum and minimum temperatures was collected from 35 meteorological stations of the South African Weather Service, covering the period between 1980 and 2015.

They went to great lengths to ensure that they had a complete set of data before presenting it to demonstrate seasonal brackets.

First for South Africa

Their statistical seasonal brackets indicate that South Africans now experience longer summers (from October to March), autumn in April and May, winter from June to August, and spring in September.

Although considerable work has been done using rainfall to determine seasonality in Southern Africa, Van der Walt believes that these methods did not work well as there are too many inconsistencies in this approach, as identified by Roffe et al. (2019, South African Geographical Journal). To make matters more complicated – as a semi-arid region, and with desert conditions along the west coast – some regions do not have enough rainfall to use as a classifier.

Temperature, on the other hand, worked well in this study. “Temperature, by contrast, is a continuous variable, and in Southern Africa has sufficient seasonal variation to allow for successful classification,” says Van der Walt.

He continues: “Although several international studies used temperature metrics to statistically classify their seasonal divisions, this study would be the first known publication in a South African context using temperature as classification metric.”

Van der Walt says what we understand as seasons largely relates to phenology – the appearance of blossoms in spring, the colouration and fall of leaves in autumn, and the migration of birds as a few examples. “These phenological shifts are more sensitive to temperature than other climatic variables.”

Seasonal brackets

According to Van der Walt, they believe that a clearly defined and communicated method should be used in defining seasons, rather than just assigning months to seasons.

“One of the most important arguments of our work is that one needs to critically consider breaks in seasons, rather than arbitrarily placing months into seasons, and so we welcome any alternate approaches,” he says.

A number of sectors apply the temperature-based division to their benefit. “For example, in the tourism sector it is becoming increasingly important to align advertising with the season most climatically suitable for tourism,” says Van der Walt.

Temperature-based division is also used to develop adaptive strategies to monitor seasonal changes in temperature under climate change. However, Van der Walt points out that each sector will have its own way of defining seasons. “Seasonal boundaries should nevertheless be clearly communicated with the logic behind them,” he says.

News Archive

Death may come in adorable little packages
2015-03-23

The main host of the Lassa virus is the Natal Mulimammate mouse.

Photo: Supplied

Postdoctoral researcher, Abdon Atangana, of the Institute for Groundwater Studies at the university recently published an article online about the Lassa Haemorrhagic fever in the Natural Computing Applications Forum. In addition to the terminal transmissible sickness recognised as Ebola haemorrhagic fever, there is another strain called Lassa haemorrhagic fever.

The disease is classified under the arenaviridae virus family. The first outbreaks of the disease were observed in Nigeria, Liberia, Sierra Leone, and the Central African Republic. However, it was first described in 1969 in the town of Lassa, in Borno State, Nigeria.

The main host of the Lassa virus is the Natal Mulimammate mouse, an animal indigenous to most of Sub-Saharan Africa. The contamination in humans characteristically takes place through exposure to animal excrement through the respiratory or gastrointestinal tracts.

Mouthfuls of air containing tiny particle of infective material are understood to be the most noteworthy way of exposure. It is also possible to acquire the infection through broken skin or mucous membranes that are directly exposed to the infective material.

“The aim of my research was to propose a novel mathematical equation used to describe the spread of the illness amongst pregnant women in West Africa. To achieve this, I used my newly-proposed derivative with fractional order called beta-derivative. Since none of the commonly used integral transform could be used to derive the solution of the proposed model, I proposed a new integral transform called Atangana-Transform, and used it, together with some iterative technique, to derive the solution of the model.

“My numerical simulations show that the disease is as deadly amongst pregnant women as Ebola,” Abdon said.

Abdon’s research was submitted to one of Springer’s top-tier journals with an impact factor 1.78. The paper was accepted and published February 2015.

Read more about Abdon’s research.

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