Includes bibliographical references (leaves 180-195). / Evidence exists that sea surface temperature (SST) variability in the South Indian Ocean may significantly influence weather and climate patterns in the southern African region. SST, in tum, can be influenced by variability in ocean fluxes, observations of which are limited in the South Indian Ocean and it is necessary to augment them with estimates derived from models. Two sets of variability in this region are examined in this thesis. The first concerns the large-scale interannual variability of the oceans neighbouring South Africa and the second, inter-ocean fluxes south of Africa on meso-through to interannual timescales. In terms of the former, a global ocean model forced with 50 years of NCEP (National Centre for Environmental Prediction) re-analyses winds and heat fluxes, has been used to investigate the evolution and forcing of interannual SST variability in the South Indian Ocean and co-variability patterns in the South Atlantic. Secondly, an eddy- permitting model is used to investigate volume, heat and salt fluxes in the oceanic region south of Africa and the effect of variations in the strength of wind forcing. Interannual dipole-like SST variability in the South Indian and South Atlantic Oceans were realistically simulated using the global ocean model, ORCA2. The model results imply that there are connections between large-scale modulations of the midlatitude atmospheric circulation of the Southern Hemisphere and co-evolving SST variability in the South Atlantic and South Indian Oceans. The atmospheric variability results in an increase (decrease) in strength of the anticyclonic wind fields over each ocean during positive (negative) dipole events. The resulting wind anomalies lead to changes in surface heat fluxes, short wave radiation, meridional Ekman heat transport and upwelling, all of which contribute to the evolution of these SST dipole patterns. Evidence is found of links between these dipole patterns and the Antarctic Oscillation and ENSO (El Niño Southern Oscillation).

No description available.

Tropical cyclones (TCs) are the most devastating weather phenomenon in nature with the powerful storm surge events occurring when severe and large TCs make landfall along coastlines. Although there have been significant strides in the TC track forecasts over the last 30 years, skills in TC intensity prediction still lag behind. Intensity may be impacted by the mixing length temperature (known as Tdy) and barrier layer thickness (BLT). Similar to cyclones in other tropical ocean basins, tropical cyclones in the South West Indian Ocean also cause significant social and economic damage in southeastern Africa and Madagascar. To forecast TC intensity more accurately, monitoring upper ocean conditions in the South Indian Ocean is of top priority. Two areas in the relatively poorly studied South Indian Ocean where such upper ocean characteristics of relevance to tropical cyclones need to be better understood are the Seychelles Chagos Thermocline Ridge (SCTR) and the Mozambique Channel. In the first part of the study, the variability of Tdy and BLT in the South West Indian Ocean, focused on the SCTR region and their relationships with tropical cyclones are investigated. It is shown that rapid cyclone intensification is influenced by large Tdy values, thick barrier layers and the presence of anticyclonic eddies. Both BLT and Tdy fields are modulated by the westward propagation of Rossby waves, which are often associated with ENSO. For example, the 1997-1998 El Nino shows a strong signal in Tdy, SST and BLT over the South West Indian Ocean. After this event, an increasing trend in Tdy occurred over most of the basin which may be associated with changes in atmospheric circulation. A rise in SST, Power Dissipation Index and frequency of Category-5 tropical cyclones also occurred post-1998. A case study of TC Bansi in the South West Indian Ocean and its relation to upper ocean heat content was presented. This tropical cyclone is of interest due to its unusual track and also because of all the damage it caused. Anomalously deep thermocline and high Tdy values were observed around December 2014-January 2015 in the South West Indian Ocean and analysis of the upper ocean structure during Bansi showed that its rapid intensification to Category 4 was related to its passage over a high Tdy (warm core) eddy region and a deep barrier layer. The second area focussed on, the Mozambique Channel, is not only a region of relatively high TC activity with highly vulnerable coastal populations, but also very energetic in terms of mesoscale ocean eddies and tidal forcing. Changes in upper ocean characteristics in the Mozambique Channel due to tidal forcing are examined as they may have significant impacts on the upper ocean structure and thus influence tropical cyclones which often occur in this region. Two experiments were conducted using the Regional Ocean Modelling System (ROMS); one forced with tides (Tide) and the other experiment without tidal forcing (NoTide). On seasonal time scales, the tidal forcing simulation shows warmer temperatures in the upper layer particularly near strong ocean currents (North East Madagascar Current and South East Madagascar Current). In Tide, warming near these currents is intensified during winter due to the southeast trade winds, while in summer, poleward advection of warmer waters south of 16-17 oS seemed more prominent. On weather time scales, these changes in the upper ocean structure, especially near the coast or in shallow regions can alter the intensity of passing tropical cyclones. When a storm encounters a warm anticyclonic eddy, as the case of TC Japhet studied in the thesis, the SST cooling by the cyclone is substantially reduced, the mixing length temperature is increased and the mixed layer is deepened. These changes can be important for TC evolution. SST variability over the South West Indian Ocean influences southern African summer rainfall and the regional atmospheric circulation either through regional modes as well as influences the landfall frequency of tropical cyclones on Mozambique (Vitart et al., 2003). Besides SST, a link has recently been found between the regional precipitation over southern Africa and tropical cyclone heat potential (a measure of upper ocean heat content) in the South West Indian Ocean (Malan et al., 2013). In this study, the relationships between an index of southern African summer rainfall (SARI) and Tdy in the South Indian Ocean at zero (January-March) and one season (October-December) lag were analyzed. A region in the southern Mozambique Channel, termed as Tdysmc, showed the strongest positive correlation with SARI at zero lag. Another strong but negative correlation with SARI at one season lag is found in the core of the Seychelles Chagos Thermocline Ridge region, termed as Tdycsctr. Composite analysis (neutral with respect to ENSO) indicated that when Tdysmc is enhanced over the South Mozambique Channel during JFM, positive rainfall anomalies prevail over large parts of subtropical southern Africa and the Congo Basin with reduced rainfall occuring over most of Madagascar and northern Mozambique. The rainfall differences are associated with enhanced easterly flow towards Madagascar transporting more moisture towards Mozambique and Tanzania, consistent with the increased rainfall. During positive Tdysmc JFM seasons, more tropical cyclones (TCs) were formed in the SWIO and more of them crossed the Mozambique Channel compared to negative Tdysmc seasons. Furthermore, during positive Tdysmc seasons, the landfalling TC was generated in the Mozambique Channel while during the negative Tdysmc ones, it was formed in the central South Indian Ocean. Positive Tdysmc seasons also have increased number of Category5 TCs in the Mozambique Channel. These results suggest that changes in the mixing length temperature, Tdysmc index which can be estimated from satellite data can be useful to monitor and potentially predict regional precipitation as well as the frequency and intensity of tropical cyclones that impact the south-eastern coast of Africa.

Submesoscale dynamics O(1-10 km, hours to days) are considered to strongly affect the stratification of the upper ocean. In the Southern Ocean, studies of submesoscale dynamics are biased to regions preconditioned for strong frontal activity and topographical influence. This dissertation considers the role of submesoscales on the evolution of mixed layer depth and upper ocean stratification in the open-ocean Subantarctic Ocean. First, we present autonomous ocean glider measurements from spring to late-summer to show that transient increases in stratification within the mixed layer during spring result in rapid mixed layer shoaling events. A realistically-forced simulation using a one-dimensional mixed layer model fails to explain these observed stratification events. We show that during this time, baroclinic mixed layer instabilities periodically induce a restratification flux of over 1000 W. m2, suggesting that the unexplained restratification is likely a result of submesoscale flows. Second, we study four separate years of seasonal-length (mid-winter to latesummer) glider experiments to define how submesoscale flows may induce interannual variations in the onset of spring/summer mixed layer restratification. Sustained temporal increases of stratification above the winter mixed layer, which defines the onset of seasonal restratification, can differ by up to 28 days between the four years studied. To explain this discrepancy, equivalent heat fluxes of baroclinic mixed layer instabilities (restratification) and Ekman buoyancy flux (restratification or mixing) are parameterized into a one-dimensional mixed layer model. Simulations including the parameterizations reveal a seasonal evolution of mixed layer stratification which is significantly more comparable to the glider observations than model simulations using heat and freshwater fluxes alone. Furthermore, the parameterization dramatically improves the sub-seasonal variability of mixed layer stratification, particularly during the onset of seasonal restratification when the mixed layer remains deep despite a positive surface heat flux. Following this, we characterize the full seasonal cycle of submesoscale flows using a realistically-forced 1/36 NEMO simulation of the Atlantic Southern Ocean. We show that deep winter mixed layers enhance the upper ocean available potential energy, which through the release of baroclinic mixed layer instabilities drive increased vertical buoyancy flux and potential to kinetic energy. These processes are associated with strong vertical velocities within the mixed layer characterized by large instantaneous upwelling and downwelling fluxes at the location of fronts. The insights from the glider observations propose that baroclinic mixed layer instabilities lead to increased near surface restratification in winter to spring, but are regulated by the synoptic-scale increases in Ekman buoyancy flux, which can keep the mixed layer deep for up to a month after surface warming. We propose the balance between restratification by baroclinic mixed layer instabilities and strong Ekman buoyancy flux driven by the passing of Southern Ocean storms is key in setting the large inter-annual variations of seasonal mixed layer restratification in the Subantarctic Ocean. Finally, we constrain the ability of gliders to represent regional submesoscale dynamics to provide context to current observations and inform future field work operations. Virtual gliders simulated within the 1/36 simulation show that horizontal buoyancy gradients in the Subantarctic are largely isotropic. We show that increasing the number of gliders sampling simultaneously over one month from one to a swarm of six results in improving the representation of the total distribution of horizontal buoyancy gradients across the Subantarctic from 10% to 42%. Similarly, by having a single glider sampling for six consecutive months, the distribution of horizontal buoyancy gradients observed increases to 47% of the total distribution. The insights presented in this dissertation enhance our understanding of submesoscale flows in the open-ocean Southern Ocean. These results are likely to have direct implications for physical and biological processes related to the ocean’s role on climate.

The Indian Ocean Tuna Commission conducted a small-scale tagging programme (2002-2009) and also a large-scale tagging programme: the Regional Tuna Tagging Programme of the Indian Ocean (RTTP-IO, 2005-2009). Both tagging programmes known as the Indian Ocean Tuna Tagging Project (IOTTP), targeted three main species of tuna commercially exploited in the Indian Ocean: bigeye (Thunnus obesus), skipjack (Katsuwonus pelamis) and yellowfin (Thunnus albacares). The two programmes tagged 219,149 tuna and 34,294 recaptures were reported to the commission. This study focused on tuna behaviour in the Indian Ocean looking at seasonal impacts, inter-annual variability in relation to ocean environment, survival estimates, movement patterns, size-groups and school-type: Free Schools (FS) and Fish Aggregating Devices (FADs). Using a multivariate approach, it was found that the years 2005 to 2007 were most abundant in recoveries of skipjack adults (77.45%) while yellowfin adults were mainly abundant during 2008 to 2011. It also showed that year and zone were significant factors influencing local abundance in tuna. The Kaplan-Meier survival curves enabled estimates on the longevity of the three species to be made. It was estimated that the cohorts (99%) vanished at 12, 5.8 and 10 years for bigeye, skipjack and yellowfin, respectively. The years 2006 (cold-productive phase) and 2007 (warmchlorophyll depleted phase) showed tuna movement patterns changing with an El Ni˜no event and primary productivity. Tuna tagged in the Tanzanian region, showed that those under FADs moved pre-dominantly towards the Somalian and Seychelles waters, while those in FS moved to the Seychelles and Mozambique waters. General Additive Model (GAM) analyses showed that the area bounded by 5⁰N-5⁰S and 45⁰-55⁰E was the main tag recovery regions for tuna under FADs. While in FS, the core recovery region was observed to be from 0⁰N-10⁰S and 50⁰-60⁰E. Recoveries were distributed in the temperature range 25-29 ⁰C. Modelling tuna movement and drift related to ocean surface currents and swimming speed, a closer match between simulated and actual recovery positions were obtained for large tuna (particularly free schools) in comparison to small tuna associated with FADs.

The Southern Ocean plays an important role in mitigating the effects of anthropogenically driven climate change. The region accounts for 43% of oceanic uptake of anthropogenic carbon dioxide (CO₂). This is foreseen to change with increasing greenhouse gas emissions due to ocean chemistry and climate feedbacks that regulate the carbon cycle in the Southern Ocean. Studies have already shown that Southern Ocean CO₂ is subject to interannual variability. Measuring and understanding this change has been difficult due to sparse observational data that is biased toward summer. This leaves a crucial gap in our understanding of the Southern Ocean CO₂ seasonal cycle, which needs to be resolved to adequately monitor change and gain insight into the drivers of interannual variability. Machine learning has been successful in estimating CO₂ in may parts of the ocean by extrapolating existing data with satellite measurements of proxy variables of CO₂. However, in the Southern Ocean machine learning has proven less successful. Large differences between machine learning estimates stem from the paucity of data and complexity of the mechanisms that drive CO₂. In this study the aim is to reduce the uncertainty of estimates, advance our understanding of the interannual drivers, and optimise sampling of CO₂ in the Southern Ocean. Improving the estimates of CO₂ was achieved by investigating: the impact of increasing the gridding resolution of input data and proxy variables, and Support vector regression (SVR) and Random Forest Regression (RFR) as alternate machine learning methods. It was found that the improvement gained by increasing gridding resolution was minimal and only RFR was able to improve on existing error estimates. Yet, there was good agreement of the seasonal cycle and interannual trends between RFR, SVR and estimates from the literature. The ensemble mean of these methods was used to investigate the variability and interannual trends of CO₂ in the Southern Ocean. The interannual trends of the ensemble confirmed trends reported in the literature. A weakening of the sink in the early 2000's, followed by a strengthening a strengthening of the sink into the early 2010's. Wind was the overall driver of dominant decadal interannual trends, being more important during winter due to the increased efficacy of entrainment processes. Summer interannual variability of CO₂ was driven primarily by chlorophyll, which responded to basin scale changes in drivers by the complex interaction with underlying physics and possibly sub-mesoscale processes. Lastly CO₂ sampling platforms, namely ships, profiling floats and moorings, were tested in an idealised simulated model environment using a machine learning approach. Ships, simulated from existing cruise tracks, failed to adequately resolve CO₂ below the uncertainty threshold that is required to resolve the seasonal cycle of Southern Ocean CO₂. Eight high frequency sampling moorings narrowly outperformed 200 profiling floats, which were both able to adequately resolve the seasonal cycle. Though, a combination of ships and profiling floats achieved the smallest error.

The apparent fluorescence quantum yield of chlorophyll-a (ΦF ), i.e. the ratio of photons emitted as chlorophyll-a fluorescence to those absorbed by phytoplankton, serves as a first order measure of photosynthetic efficiency and a photophysiological indicator of the resident phytoplankton community. Drivers of ΦF variability, including taxonomy, nutrient availability, and light history, differ in magnitude of influence across various biogeographic provinces and seasons. A Multi-Exciter Fluorometer (MFL, JFE Advantech Co., Ltd.) was selected for use in in situ ΦF derivation and underwent an extensive radiometric calibration for this purpose. Wavelength-specific ΦF was determined for 66 in situ field stations, sampled in the Atlantic Southern Ocean during the austral winter of 2012 and summer of 2013/ 2014. Phytoplankton pigments, macronutrient concentrations, and light levels were simultaneously measured to investigate their influence on ΦF . While no relationship was observed between macronutrient levels and ΦF , an inverse relationship between light and ΦF was apparent. This was likely due to the influence of speciesspecific fluorescence quenching mechanisms employed by local populations. ΦF derived from ocean colour products (Φsat) from the Moderate Resolution Imaging Spectroradiometer (MODIS) were compared to in situ ΦF to assess the performance of three existing Φsat algorithms. Results indicate that accounting for chlorophyll-a fluorescence reabsorption, the inherent optical properties of the surrounding water column, and the sensor angle of observation, is crucial to reducing Φsat uncertainty. A hybrid combination of two of the algorithms performed best, and was used to derive Φsat for stations co-located to in situ iron measurements in the Atlantic Southern Ocean. A significant negative relationship was observed, indicative of the effects of iron availability on quantum yield and its potential as a proxy for iron limitation. However, separating the individual contributions of light, taxonomy, and iron limitation to Φsat variability remains a challenge. A time series analysis of Φsat was also undertaken, which revealed a prominent Φsat seasonal cycle. Ultimately, increased in situ sampling would expedite the development of improved Φsat algorithms; the routine retrieval of Φsat would offer insight into phytoplankton dynamics in undersampled regions such as the climate relevant Southern Ocean.

Includes bibliographical references (p. 176-188). / An analytical framework for the simulation and quantitative interpretation of ocean colour data is presented, providing an inverse reflectance algorithm designed for the detection of harmful algal blooms. The adopted framework focuses on establishing quantitative relationships between optically important algal intracellular properties and inherent optical properties (IOPs), such as the absorption and backscattering coefficients, and the resultant effects on remote-sensing reflectance. A principal aim of the study is to establish the determinant variables of the IOPs associated with natural algal assemblages, and provide a means of simulating these IOPs. Algal size is an important determinant of optical properties, and the study demonstrates algal IOP simulation, using equivalent particle size distributions that can be simply parameterised with regard to effective cell diameter. Statistical analyses of causal variability are also conducted on absorption data from a variety of natural algal assemblages, revealing the relative importance of cell size, intracellular Chi a concentration, and accessory pigment complement. An improved understanding of algal angular scattering is regarded as key to the analytical modelling of ocean colour, and the use of two-layered spherical models for the simulation of algal scattering properties is investigated. Preliminary validation of the combined use of the equivalent size and two-layered models indicates that they are capable of adequately simulating the remote-sensing reflectance properties of high biomass bloom waters.

Bibliography: leaves 96-97. / Global Acoustic Propagation is a recently developed scientific discipline within the study of long range underwater acoustic propagation. Acoustic propagation over extremely long ranges involves a combination of effects from earth curvature and the global distribution of oceanographic and geophysical features. Antipodal receptions, that is to ranges of the order of 20Mm (1 Megameter = 1 000 km), require underwater acoustic propagation to very long ranges and thus effects due to the form of the earth and the range dependence of the sound speed field within the ocean can not be ignored. The purpose of this thesis is to investigate the nature of antipodal receptions with reference to the form of the earth and horizontal sound speed variations within the ocean and thereby contribute to the new and specialized field of study, Global Acoustic Propagation. Close to an acoustic source acoustic energy diverges so that local signal strengths decrease with distance from the source. However, as the antipodal region is approached acoustic energy that has not been blocked by bathymetric features will refocus, counteracting the distance loss rule. Thus at antipodal sites there is a good prospect of receiving a focused signal. Even so, the ellipsoidal form of the earth and the horizontal variability within the sound speed field of the ocean means that the re-focusing will result in a region of enhanced signal rather than an exact antipodal point. The precise detail of the advantage of placing receivers in the antipodal region will depend upon the paths taken by the acoustic energy and the characteristics of the acoustic medium encountered along each path. The proposal for this thesis is to develop an algorithm to determine the nature of the antipodal region under certain physical assumptions. The physical assumptions are referred to as the geometric assumption, which refers to the form of the earth, and the refractive assumption, which refers to the horizontal variability of sound speed within the world oceans.

Bibliography p.217-232. / Anomalous climatic conditions have contributed to poverty, wlnerability and unemployment, which are major concerns of many southern African governments. Western countries continue to give food aid during drought periods and are looking for new and effective ways of supporting national food security plans (Walker, 1989a). Food security is a very difficult problem in Africa. A number of agricultural national programs have been planned to alleviate the problem but crop yields and living standards continue to deteriorate in many African countries. Unfavorable macro-economic conditions, debt repayments, civil war, political instabilities and mismanagement of resources make the situation more complex. It may be considered that anomalous climatic events (droughts or floods) are important factors, which contribute to acute food shortage. Seasonal rainfall forecasts are an important management tool for donor countries as well as local farmers. The failure to utilize forecasts based on sound scientific knowledge would negate attempts at achieving food security (W orId Meteorological Organization, 1996). It is for this reason that rainfall is an important input parameter in attaining self-sufficiency in food. Rainfall varies in space and time over southern Africa (preston-Whyte and Tyson, 1988; Walker 1989b; Mason, 1992; Rocha, 1992; Makarau, 1995). Further investigations of year-to-year variability of southern African summer rainfall are required in order to understand mechanisms and make accurate seasonal forecasts. Therefore, research work in climate should have high priority in African countries. The need to understand and predict the interannual variations of the atmosphere and the oceans has resulted in formation of global programs like the Tropical Ocean Global Atmosphere (TOGA) and World Climate Research Program (Climate Variability and Predictability, CLIVAR, 1995 and 1998). 2 Determination of the dynamics of droughts and floods continues to be a major problem. Correct prediction of extreme events such as droughts, floods, cold and warm spells involves knowing the mechanisms as well as the local and remote forcings. Several mechanisms have been suggested but more empirical research is required to understand and predict climate variability of southern African on intra-seasonal and inter-annual time scales. This study focuses on inter-annual and intra-seasonal variability of southern African climate with the view of identifying climatic regional and local features that influence summer rainfall and its fluctuations over southern Africa as whole. In order to achieve this, determination and refining of rainfall-SST anomaly relationships is carried out. Teleconnection patterns and coherent structure of interannual variability are revealed. Atmospheric mean meteorological features over Southern Africa and adjacent oceans have direct impact on summer rainfall. Thus determination of mean features using up-graded new and longer data sets provides a basis for investigating inter-annual and intraseasonal variability. This study presents mean characteristics of peak summer (December, January and February) based on 14 years ECMWF gridded data set. This study is motivated by a desire to understand climatic controls of interannual summer rainfall variability over southern African. The intensity of summer rainfall is modulated on synoptic, intra-seasonal, interannual and decadal time scales.