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The structure and variability of inter-annual and intra-seasonal circulation anomalies and their precursors are investigated over northern Tanzania. Area rainfall departures are computed in the period 1960-1990 and wet and dry years are identified. Northern Tanzania experiences bimodal rains centred on the seasons: March to May (Masika) and October to December (Vuli). Station inter-correlations in Masika are of order +0.4, whereas in Vuli correlations are of order+0.7. Using composite sequences of gridded sea surface temperatures (SST),outgoing longwave radiation (OLR) and winds in the lower- and upper troposphere, the- precursors of flood and drought are assessed. Composites are averaged for the specific season and for periods 2, 4 and 6 months prior; and the historical mean is subtracted to produce anomalies. In this way, evolution of extreme rainfall scenarios is tracked for predictive purposes. The patterns analysed show that when positive SST anomalies persist in the Indian Ocean, sympathetic negative OLR values and local rainfall enhancement are observed. Using pentad (5 day mean) rainfall time series for the area, wet spells are analysed for structure and evolution. ECMWF data for the peak in Vuli rainfall each year from 1986 to 1991 are averaged to form a single composite. The historical mean is subtracted from the composite to produce anomalies for the wet spell and the preceeding pentads.

MSc (Applied Radiation Science), North-West University, Mafikeng Campus The present study analysed inter-seasonal and intra-seasonal rainfall variability in the North West Province (NWP) South Africa. The observed rainfall data was obtained from South African Weather Service (SAWS) and Agricultural Research Council (ARC).The data used in the analysis covers a period of 31 rainfall seasons (1984 to 2015). The methodology used in the study to analyse rainfall variability was rainfall time series analysis while the rainfall trends were analysed using Man Kendall trend analysis and the Sens slope. Before evaluating rainfall variability in the province, NWP was classified into two homogeneous rainfall regimes using Cluster Analysis (CA). Cluster one (C1) covers central and southern stations while Cluster two (C2) covers the north-eastern stations in the province. The rainfall time series of the clusters show that C1 is increasing in aridity while in C2 the rainfall is showing an increase pattern. Mann Kendal trend test and Sens' slope estimator were used to study variability and trends in NWP rainfall. Trend analysis results of North West Province 1984-2015 seasonal rainfall indicated a general decrease in the province rainfall overtime. Four stations registered a statistically significant rainfall trend of which only one showed a negative rainfall trend. 9 out of 15 rainfall stations in C1 reported negative rainfall trend, while C2 is gradually becoming wetter with 82% of the stations showing a positive rainfall trend. In the intra-seasonal analysis, statistically significant stations (Delareyville, Taung, Olifantsport and Potchefstroom) were used. The results suggest that rainfall in North West Province shows a strong spatial and temporal variability at Intraseasonal scale. Tendency towards aridity can be expected due to the delay and frequency of below normal rainfall experienced in NWP. The rainfall in the region can go for about 14 consecutive recording below normal events. While only few above normal rainfall pentads are recorded. However, some limitations (e.g., data length), were encountered in this study. Masters

PhD (Geography), North-West University, Mafikeng Campus, 2017 The principal aim of this study was to relate the large-scale meteorological systems to the local seasonal rainfall characteristics (especially rainfall onset and variations/trends). In addition, the study established the relationship between the seasonal rainfall onset, mean climatological systems and anomalies and their respective dynamics in the north east of South Africa (Vhembe District). The two most significant forcings in Vhembe District that influence rainfall are the topographic effects and the large scale circulation, which are mutually interactive in some cases. Four steps of analyses were involved. In the first step humid and semi-arid climatic subdivisions of Vhembe District were assumed from earlier studies. The rainfall characteristics and trends for the local area were then analysed based on these climatic groups. This first step also included the task to determine seasonal rainfall onset changes over different decades and within decades from 1980 to 2009 for both humid and semi-arid areas. The results in this step were obtained using two techniques, namely Mann Kendal trend analysis and Sen's slope estimator, which were employed to test for the presence of statistically significant trends and magnitude respectively. The second step was to establish the degree to which the local gauge data captures the signal of large-scale climate forcing of the study area. This step was accomplished by examining rainfall estimated by global precipitation datasets (in this case Climate Prediction Centre (CPC)'s Merged Analysis of Precipitation (CMAP)) in order to compare and validate the seasonal rainfall onset obtained based on the analysis of local gauge data. The third step was to establish relationships between seasonal rainfall onset and change and large-scale mean atmospheric circulation. This was accomplished by exploring meteorological systems and indicators of moisture transport and accumulation (specific humidity, moisture flux and vertical motion), that feature during seasonal rainfall onset. The final step, explores the time-varying large-scale meteorological anomalies associated with the evolution of local seasonal rainfall characteristics. The third and fourth steps used the data products of NCEP/NCAR reanalysis output. The study has established differences and common denominators between humid and semi-arid zones during early and late seasonal rainfall onset in Vhembe District. For example, no large-scale moisture supply or convective activities are needed in the humid zone for seasonal rainfall to commence. While in the semi-arid zone, large-scale moisture supply and large-scale convective activities initiates seasonal rainfall onset. Doctoral

MSc (Environmental Science), North-West University, Mafikeng Campus, 2015 In arid and semi-arid environments like most parts of South Africa, the state of vegetation cover is an important indicator of the state of the environment. Climate variability coupled with different anthropogenic activities could affect vegetation cover at varying levels. This study aimed at assessing the pattern and magnitude of spatial and temporal vegetation cover changes before and after heavy rains in the Vhembe and Mopani Districts, Limpopo Province, South Africa. Utilising remote sensing methodology, Landsat TM images of 1995, 1997, 2005, 2007, 2010 and OLI-8 2013. Rainfall data for 1961-2011 were used to compute rainfall anomalies. Landsat classification of NDVI density classes for each image was computed for identifying vegetation cover changes. Classification of vegetation density based on NDVI categorised five major classes: non-vegetation (bare land or water), low density, medium density, high density and very high density classes. In addition, a correlation coefficient of heavy rainfall events and vegetation cover was done. The study established that there have been substantial changes in vegetation densities before and after heavy rainfall has occurred in the area. The study area received above normal rainfall in 1996, 2006 and 2011. Performing vegetation cover change analysis for the above normal rainfall years’, Vhembe and Mopani Districts showed similar patterns in vegetation cover change. This means that when vegetation cover increased in Vhembe District it also increased in Mopani District, though to a different degree. The change analysis showed an increase of 59.45 ha (5504.6%) for Vhembe and 0.81ha (90%) for Mopani in non-vegetation cover from 1995-1997 while, high and very high density decreased. Although some areas recorded a decrease in vegetation cover, there are also areas that had had an increase in vegetation during the study period. Results of the correlation coefficient revealed a significant weak correlation of (r = 0.44 and 0.18) in 1996, (r = 0.13 and 0.29) in 2006 and (r = 0.04 and – 0.36) in 2011 in Vhembe and Mopani Districts respectively, between NDVI and Mean Average Rainfall (MAR) with a residual of 19.4% (r² = 0.19), 1.7% (r² = 0.002) and 0.2 % (r² = 0.13) in Vhembe District during 1996, 2006 and 2010 respectively. Similarly, Mopani District accounted for 3.2 % (r² = 0.03), 5.3 % (r² = 0.05) and 15.2 % (r² = 0.15) in 1996, 2006 and 2011 respectively, suggesting that other factors influence vegetation cover changes in the study area. Hence, vegetation density cover change could be attributed to socio-economic activities, such as agriculture, veld fires, settlement expansions, and overgrazing. Land cover mapping and change detection studies are valuable especially for vegetation cover change. From the findings, the study recommended monitoring and analysing Land Use Land Cover Changes (LULCC) in order to understand drivers of the change in the Vhembe and Mopani District. These studies will make significant contribution towards the understanding of socio-economic drivers of vegetation cover change, and the impact on natural and human ecosystems. Masters

MSc (Environmental Sciences), North-West University, Mafikeng Campus, 2013 The aim of this study was to assess the impact of anthropogenic climate change on the plant biodiversity with a primary focus on the geographical area of the Soutpansberg region of South Africa. It is of primary importance to establish the effects of anthropogenic climate change on the vegetation of Soutpansberg in order to preserve the natural state of vegetation as much as possible. However, it has been noted on several studies that indigenous plant species will not only diminish due to climate change but also due to incorrect forest management The releve method was adapted and used to assess the structure and composition of vegetation in each of the delineated areas (North West - NW; North East - NE; South West - SW; South East - SE; Centre - SE) of the Soutpansberg. Geographic Information System (GIS) and remote sensing technology was further utilised to assess the vegetation cover qver time in the study area as well as classifying the vegetation change over time into various classes. Climate data; rainfall and temperature were assessed for pattern, distribution, variability and associated them to the occurrence of different plant life forms found across the Soutpansberg Mountain range. The results obtained indicated that there is a high variation in vegetation composition, density and species richness as the rainfall and temperature varies across the mountain range. Within the delineated areas of the Soutpansberg: NW; NE; SW; SE; Centre, vegetation richness and density were assessed. The richness and density at the Centre was found to be above 80% with forest cover still very much intact. This was followed by the SE with about 75 % of natural forest cover , the SW which is fast making a transition from forest to woodland while the NE has become more of woodland with a scattered forest layer; the NW which is composed of grassland and thickets. Furthermore the Normalized Difference Vegetation Index (NOVI) values from remotely sensed images indicate a change in vegetation vigour across the years and across the mountain from east to west corresponding in line with observed climate variability. A classification of the vegetation of the Soutpansberg using unsupervised classification, categorized the vegetation into 10-13 functional types. The functional type classification provided the opportunity for undertaking analyses to develop an understanding of the vegetation change over time through image to image subtraction (change detection). The results provide evidence of vegetation change in the study area and also that as time passes with little or no actions taken to curb anthropogenic climate change effects on vegetation, indigenous plant species will diminish. Of more significance, is the fact that the richness amongst different life forms in the same mountain range is explained by different climatic factors (rainfall and temperature), indicating that rainfall and temperature affect the coexistence of different vegetation types and have a different effect on different life forms. Results confirmed that anthropogenic climate change affect the vegetation of the Soutpansberg with such effects varying across the mountain and the magnitude changes over time and space. These effects resulted in decrease in biomass and vigour of indigenous vegetation across the range with time. Masters

Thesis (Ph.D.(Environmental Science) North-West University, Mafikeng Campus, 2012 Doctoral