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Browsing Theses and Dissertations by Author "Bopape, M. M."
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Item Open Access Characteristics of deep moist convection and rainfall in cut-off lows over South Africa(2019-09-20) Muofhe, Tshimbiluni Percy; Chikoore, H.; Bopape, M. M.; Nethengwe, N. S.Out of all rain-producing weather systems, cut-off lows (COLs) are linked with the occurrence of high impact rainfall and in some cases short-lived floods which can last for 24 hours over South Africa. This study examined the characteristics associated with the present occurrence of the severe COL systems over South Africa from 2011 to 2017. The accuracy of the 4.4 km Unified Model (UM) which is currently in use for simulating areas of deep moist convection in South Africa was evaluated. The UM simulated geopotential height at 500 hPa as well as the associated 24 hours precipitation which were compared against the daily fields of geopotential height and 6-hourly precipitation from the European Centre for Medium-Range Weather Forecasts (ECMWF). COL events were categorized and analyzed according to the associated surface circulation patterns at 850 hPa. The seasonal distribution and duration of the systems over northern (10°E-33°E //22°-32°S) and southern (10°E-33°E //32°-35°S) regions of the study area were also analyzed. Results show COL systems shifting with season towards the north eastern parts of the country, with an increased number of events during the austral winter season during the study period. Systems which lasted for long time were observed during the austral winter and spring seasons. The UM tends to simulate areas of heavy precipitation accurately with poor simulation during the initial stages of the systems. The UM provided a more realistic-looking closed geopotential height and rainfall fields for systems which are coupled with a cold front at the surface. Application of the knowledge about the evolution in the characteristics of COL events from this study can improve the operational forecasting of these weather systems over the country.Item Open Access Heat waves in South Africa: Observed variabilty, structure and trends(2017-05-18) Mbokodo, Innocent Lifa; Nethengwe, N. S.; Chikoane, H.; Bopape, M. M.Heat waves are warm extreme temperature events that have environmental and socio-economic impacts in many regions across the world. Negative impacts of warm extreme temperatures over South Africa necessitate the need to study the nature of heat waves. Observations and satellite datasets are analysed in the investigation of the nature and trends of heat waves over South Africa in the present (1983-2012) and future (2010-2039, 2040-2069, 2070-2099) climates. Case study and composite analysis of National Centers for Environmental Prediction datasets were done using the Grids Analysis and Display Systems to get an in-depth understanding of the structure of heat waves in South Africa. Future climate model output obtained from the Conformal Cubic Atmospheric Model was used for future heat wave trends in South Africa. The simulations were made using the Representative Concentration Pathways 4.5 and 8.5. Heat waves are unusual events in the present climate (1983-2012) over much of the country, with 20 of the selected 24 stations experiencing an average of less than one heat wave per season. Heat waves are also more frequent and last longer during warm phase of El Niño-Southern Oscillation (ENSO) than in cool phase of ENSO with the north-east being the most prone region. Composite analysis of 500 hPa omega indicates subsidence over the interior of South Africa in both phases of ENSO. Heat waves in South Africa are localized and associated with a middle level high pressure system that persists over the interior inducing anticyclonic flow and subsidence. The anticyclonic circulation over a region experiencing heat wave weakens with decreasing height over land areas which may be due to frictional forces at the surface and the high is placed further south-east at the surface. Advection of dry continental northerly winds also contributes to high maximum temperatures during heat waves in the interior. Maximum temperatures are expected to increase drastically from the present-day climate to the 2070 – 2099 period, with an average increment of about 8°C during DJF in much of the central interior. As a result, heat wave occurrences are expected to be higher in the future warmer climates when climate change signal is higher. Most increases are expected for heat waves lasting for a week than those lasting for over 2 weeks. CCAM outputs also indicated that heat waves in South Africa are expected to last longer and become more intense during the future warmer climates. Longer lasting and more intense heat waves are expected over the Karoo than in other parts of the country.Item Open Access Impact of spatio-temporal variability of the Mascarene High on weather and climate over Southern Africa(2017-05) Xulu, Nkosinathi Goodman; Nethengwe, N. S.; Chikoane, H.; Bopape, M. M.Subtropical anticyclones locate and modulate weather and climate over subtropical belts for both the Northern and Southern Hemispheres. This study investigates the spatio-temporal variability of the Mascarene High over the South Indian Ocean on (anomalous) weather and climate over southern Africa at intraseasonal, seasonal, interannual, multidecadal and event time-scales. The Mascarene High is located 25-35°S, 40-110°E, playing a vital role in day-to-day weather and climate patterns conditions over southern Africa. Spatio-temporal characteristics of the Mascarene High investigated in this study span the period 1985-2014 and 2071-2100, using NCEP-NCAR reanalysis datasets for present-day climate observations and the Conformal-Cubic Atmospheric Model (CCAM) for future projections. The Mascarene High is analysed using mean sea level pressure (MSLP) extracted from ECMWF ERA-interim monthly reanalysis data. The Mascarene High is also subjected to Principal Components Analysis, depicting eastern displacements of the weather system to be dominant for weather and climate fluctuations over southern Africa. The Mascarene High migrates south (north) during austral summer (winter) and is centred over the eastern Indian Ocean in summer in connection with the Indian Ocean Subtropical Dipole. Event scale analysis is also employed for investigating Mascarene High blocking and induced anomalous weather. Mascarene High blocking leads to anomalous rainfall events over southern Africa associated with tropical cyclones, cut-off lows and cloud bands. There is also a vital geographical variability of the Mascarene High development, distribution and movement in the South Indian Ocean at the different time-scales. Projections of the Mascarene High indicate a shift in mean location as a result of future expansion and intensification. This projected expansion and intensification is expected to shift tropical cyclone trajectories equatorward, with the baroclinic structure of cold fronts expected to shift poleward affecting changes in the weather and climate of southern Africa. This finding is important as it projects changes in weather and climate conditions over southern Africa in a changing climate due to increased greenhouse gas emissions.Item Open Access Meteorological influences on malaria transmission in Limpopo Province, South Africa(2019-09-20) Ngwenya, Sandile Blessing; Nethengwe, N. S.; Chikoore, H.; Bopape, M. M.Semi-arid regions of Africa are prone to epidemics of malaria. Epidemic malaria occurs along the geographical margins of endemic regions, when the equilibrium between the human, parasite and mosquito vector populations are occasionally disturbed by changes in one or more meteorological factors and a sharp but temporary increase in disease incidence results. Monthly rainfall and temperature data from the South African Weather Service and malaria incidence data from Department of Health were used to determine the influence of meteorological variables on malaria transmission in Limpopo from 1998-2014. Meteorological influences on malaria transmission were analyzed using time series analysis techniques. Climate suitability for malaria transmission was determined using MARA distribution model. There are three distinct modes of rainfall variability over Limpopo which can be associated with land falling tropical cyclones, cloud bands and intensity of the Botswana upper high. ENSO and ENSO-Modoki explains about 58% of this variability. Malaria epidemics were identified using a standardized index, where cases greater than two standard deviations from the mean are identified as epidemics. Significant positive correlations between meteorological variables and monthly malaria incidence is observed at least one month lag time, except for rainfall which shows positive correlation at three months lag time. Malaria transmission appears to be strongly influenced by minimum temperature and relative humidity (R = 0.52, p<0.001). A SARIMA (2, 1, 2) (1, 0, 0)12 model fitted with only malaria cases has prediction performance of about 53%. Warm SSTs of the SWIO and Benguela Niño region west of Angola are the dominant predictors of malaria epidemics in Limpopo in the absence of La Niña. Warm SSTs over the equatorial Atlantic and Benguela Niño region results in the relaxation of the St. Helena high thus shifting the rainy weather to south-east Africa. La Niña have been linked with increased malaria cases in south-east Africa. During El Niño when rain bearing systems have migrated east of Madagascar ridging of the St. Helena high may produce conducive conditions for malaria transmission. Anomalously warmer and moist winters preceding the malaria transmission season are likely to allow for high mosquito survival and the availability of the breeding sites thus high population in the beginning of the transmission season hence resulting in increased epidemics.Item Open Access Rainfall variability and change in South Africa (1976-2065)(2019-09-20) Ncube, Tisang Manabalala; Chikoore. H.; Bopape, M. M.Rainfall is undoubtedly the most significant factor for life’s continuity. South Africa is prone to future climate uncertainties due to global climate change. The aim of this study is to investigate rainfall variability and change in South Africa on a present day (1976-2005), near-future (2006-2035) and far-future (2036-2065) climate. For the study, 3 RCMs (REMO2009, RCA4 and CCLM4-8-17), forming part of CORDEX-Africa project were nested within 5 different CIMP5_GCMs of low resolution. GPCC precipitation, NOAA GHCN_CAMS Land Temperature and other NCEP reanalysis products were useful in validating models in simulations of present-day climate. RCP4.5 and RCP8.5 emission scenarios from IPCC-AR5 were used for future climate projections. On the validation, each regional climate model displayed different signature on simulations, rainfall in particular because this is a variable that is affected most by sub-grid process. Simulations nested within MIROC5 simulated more precipitation than simulations forced with other GCMs, due to more large-scale moisture convergence into the nested domain. There were differences in projections of RCM nested within the same GCM, as well as with the same RCM nested within different GCMs, on the future. Models nested within MPI project wetter conditions over the eastern parts of Limpopo, while the other two projected drier conditions in the same area. REMO2009 forced on MPI uniquely projected drying of Western Cape throughout the seasons on both RCPs and futures. Simulations conducted with the RCP8.5 scenario forcing are generally found to be associated with either a larger increase in temperature, or an increase in area associated with higher temperature increases. CCLM4-8-17 forced on HadGEM2 projected below average temperatures over the northwest parts of the country under the RCP8.5 scenarios. MPI driving model projected a general reduction of evaporation values, with lowest over northeast, northwest parts and south coastal parts of South Africa, in contrary to adjacent oceans. In this study, we have sought to identify the sources of uncertainties amongst model simulations between either the RCMs or the driving GCMs.Item Open Access Simulating South African Climate with a Super parameterized Community Atmosphere Model (SP-CAM)(2019) Dlamini, Nohlahla; ; Chikoore, H.; Bopape, M. M.; Nethengwe, N. S.The process of cloud formation and distribution in the atmospheric circulation system is very important yet not easy to comprehend and forecast. Clouds affect the climate system by controlling the amount of solar radiation, precipitation and other climatic variables. Parameterised induced General Circulation Model (GCMs) are unable to represent clouds and aerosol particles explicitly and their influence on the climate and are thought to be responsible for most of the uncertainty in climate predictions. Therefore, the aim of the study is to investigate the climate of South Africa as simulated by Super Parameterised Community Atmosphere Model (SPCAM) for the period of 1987-2016. Community Atmosphere Model (CAM) and SPCAM datasets used in the study were obtained from Colorado State University (CSU), whilst dynamic and thermodynamic fields were obtained from the NCEP reanalysis ll. The simulations were compared against rainfall and temperature observations obtained from the South African Weather Service (SAWS) database. The accuracy of the model output from CAM and SPCAM was tested in simulating rainfall and temperature at seasonal timescales using the Root Mean Square Error (RMSE). It was found that CAM overestimates rainfall over the interior of the subcontinent during December - February (DJF) season whilst SPCAM showed a high performance in depicting summer rainfall particularly in the central and eastern parts of South Africa. During June – August (JJA), both configurations (CAM and SPCAM) had a dry bias with simulating winter rainfall over the south Western Cape region in cases of little rainfall in the observations. CAM was also found to underestimate temperatures during DJF with SPCAM results closer to the reanalysis. The study further analyzed inter-annual variability of rainfall and temperature for different homogenous regions across the whole of South Africa using both configurations. It was found that SPCAM had a higher skill than CAM in simulating inter-annual variability of rainfall and temperature over the summer rainfall regions of South Africa for the period of 1987 to 2016. SPCAM also showed reasonable skill simulating (mean sea level pressure, geopotential height, omega etc) in contrast to the standard CAM for all seasons at the low and middle levels (850 hPa and 500 hPa). The study also focused on major El Niño Southern Oscillation (ENSO) events and found that SPCAM tended to compare better in general with the observations. Although both versions of the model still feature substantial biases in simulating South African climate variables (rainfall, temperature, etc), the magnitude of the biases are generally smaller in the super parameterized CAM than the default CAM, suggesting that the implementation of the super parameterization in CAM improves the model performance and therefore seasonal climate prediction.