The Verification of different model configurations of the Unified Atmospheric Model over South Africa

In 2006 a Numerical Weather Prediction (NWP) model known as the Unified Model (UM) from the United Kingdom Meteorological Office (UK Met Office) was installed at the South African Weather Service (SAWS). Since then it has been used operationally at SAWS, replacing the Eta model that was previously used. The research documented in this dissertation was inspired by the need to verify the performance of the UM in simulating and predicting weather over South Africa. To achieve this aim, three model configurations of the UM were compared against each other and against observations. Verification of rainfall as well as minimum and maximum temperature for the year 2008 was therefore done to achieve this. 2008 is the first year since installation, where all the configurations of the UM used in the study are present. For rainfall verification the model was subjectively verified using the eyeball verification for the entire domain of South Africa, followed by objective verification of categorical forecasts for rainfall regions grouped according to standardized monthly rainfall totals obtained by cluster analysis and finally objective verification using continuous variables for selected stations over South Africa. Minimum and maximum temperatures were subjectively verified using the eyeball verification for the entire domain of South Africa, followed by objective verification of continuous variables for selected stations over South Africa, grouped according to different heights above mean sea level (AMSL). Both the subjective and objective verification of the three model configurations of the UM (for both rainfall as well as the minimum and maximum temperatures) suggests that 12km UM simulation with DA gives better and reliable results than the 12km and 15km UM simulations without DA. It was further shown that although there was no significant difference between the model outputs from the 12km and the 15km UM without DA, the 15km UM simulation without DA, proved to me more reliable and accurate than the 12km UM simulation without DA in simulating minimum and maximum temperatures over South Africa, on the other hand the 12km UM simulation without DA is more reliable and accurate than the 15km UM simulation without DA in simulating rainfall over South Africa.Dissertation (MSc)--University of Pretoria, 2013.gm2014Geography, Geoinformatics and Meteorologyunrestricte

Granger causality of the local Hadley cell and large-scale cloud cover over South Africa

This study demonstrates that Hadley cell dynamics could be used as a proxy to determine cloud cover and thus solar energy potential over South Africa. Granger causality was used to investigate causal interactions between the Hadley cell and cloud cover for the period 1980–2015, and such links were established. Areas of strong causality are found over the northwestern parts of South Africa. Moreover, weak causality from cloud cover to the Hadley cell does exist, with vertical velocity being the main variable responsible for this causality, which hence indirectly links cloud cover to Hadley cell causality. Significance: Hadley cell dynamics may be used to identify regions of cloudlessness over South Africa. Hadley cell dynamics may further be used as a proxy for cloud cover towards understanding the solar energy potential in South Africa within the context of climate variability and change

Assessment of smallholder farmers’ perception and adaptation response to climate change in the Olifants catchment, South Africa

Climate change is expected to affect the livelihood of rural farmers in South Africa, particularly the smallholder farmers, due to their overwhelming dependence on rain-fed agriculture. This study examines smallholder farmers’ perception of climate change, the adaptation strategies adopted and factors that influence their adaptive decisions. The unit of data collection was household interview and focus group discussion. Climate data for the Olifants catchment (1986–2015) were also collected to validate farmers’ perception of climate change with actual climate trend. Data collected were analysed using descriptive statistics, Mann–Kendall trend, Sen’s slope estimator and multinomial logit regression model. Results revealed that smallholder farmers are aware of climate change (98%), their perception of these changes aligns with actual meteorological data, as the Mann–Kendall test confirms a decreasing inter-annual rainfall trend ( 0.172) and an increasing temperature trend (0.004). These changes in temperature and precipitation have prompted the adoption of various adaptation responses, among which the use of improved seeds, application of chemical fertilizer and changing planting dates were the most commonly practised. The main barriers to the adoption of adaptation strategies were lack of access to credit facility, market, irrigation, information about climate change and lack of extension service. The implication of this study is to provide information to policy-makers on the current adaptation responses adopted by farmers and ways in which their adaptive capacity can be improved in order to ensure food security.The National Research Foundation-TheWorld Academy of Science (NRF-TWAS)https://iwaponline.com/jwccam2022Geography, Geoinformatics and Meteorolog