Numerical modelling of the marine ecosystem requires the aggregation of diverse chemical and biological species into broad categories. To avoid large bias errors it is preferable to resolve as many explicit state variables and processes as possible. The cost of this increased complexity is greater uncertainty in model parameters and output. When comparing models, the importance of quantifying both bias error and the variability of unconstrained solutions was revealed as two marine ecosystem models were calibrated to data. Results demonstrated that all prior parameter information must include realistic error estimates if model uncertainty is to be quantied. Five simple ecosystem models were calibrated to observations from two North Atlantic sites; the Bermuda Atlantic Time-series Study (BATS) and the North Atlantic Bloom Experiment (NABE). Model-data mists were reduced by between 45 and 50%. The addition of model complexity (a parameterised microbial loop, a variable chlorophyll a to nitrogen ratio and dissolved organic nitrogen) led to larger improvements in model performance at BATS relative to NABE. Calibrated parameter values developed at NABE performed better than the default parameter values when applied at BATS. Solutions developed at BATS performed worse than the default values at NABE. The models lacked sucient ecological complexity to function well at BATS. Errors in the model were masked by errors in the calibrated parameters and the models did not perform well with regard to independent data. The models were well suited to reproducing the NABE data, and the calibrated models performed relatively well at BATS. The models were sensitive to the underlying physical forcing. Although the ecosystem models were originally calibrated within a poor representation of the physical environment at BATS, results from experiments using an improved physical model support the conclusion that the ecosystem models lacked the required complexity at that site.

The atmospheric concentration of CO2 has risen considerably since the industrial revolution, and the subsequent uptake of atmospheric CO2 by the oceans has affected the carbonate system and caused a reduction in the pH of the oceans. Model estimates involving future CO2 emission scenarios have predicted a significant increase of oceanic Dissolved Inorganic Carbon concentrations by the end of the century, corresponding to a decrease in oceanic pH by up to 0.4. In order to observe and predict changes in primary productivity and community structure in the oceans associated with future climate change, precise measurements of all the carbonate system parameters are important. The natural processes affecting the seasonal and regional variations of the carbonate chemistry are still poorly understood and sustained monitoring programs are required in order to determine the importance of hydrographical and biogeochemical forcings. The relationships between physical and biological parameters and carbonate system parameters were investigated in several regions of the North Atlantic Ocean, allowing a better understanding of the natural processes affecting the carbonate system in this ocean basin. For this purpose, the seasonal and inter-annual variability of the carbonate system in the Northeast Atlantic Ocean was studied through a ship of opportunity program, allowing observations of the short-term processes affecting the carbonate system and air-sea CO2 fluxes. The results showed contrasting effects of winter mixing and sea surface temperature on the carbonate system and the air-sea CO2 fluxes. In addition, the distributions of the carbonate system parameters were determined in the Iceland Basin and in the sub-tropical Northeast Atlantic Ocean. The carbonate system in the Iceland Basin was characterized by mesoscale variability associated to the presence and development of an eddy dipole in the study region; while the sub-tropical Northeast Atlantic Ocean showed spatial variability in all the chemical parameters, associated with coastal upwelling and remineralization in an oxygen minimum zone. Although the physics appeared to be the main forcing on the carbonate system in this study, the role of biology in the seasonality of the carbonate system is highly important. However, physical forcings tend to set the level for biological drawdown and therefore highly contribute to the variability of the carbonate system and CO2 fluxes.

The spatial and temporal distribution of phytoplankton around the Crozet Plateau, Southern Ocean, is studied through a variety of satellite datasets and in situ cruise and Argo float measurements. Parts of the study area regularly contain phytoplankton concentrations significantly enhanced over the other parts, and over most of the rest of the Southern Ocean, due to natural iron fertilization from the Crozet Islands. Study is made of these contrasts in order to further understand the processes that limit phytoplankton over the mostly High Nutrient Low Chlorophyll (HNLC) Southern Ocean. The longer timescales, larger areas and regularity of naturally iron-fertilized phytoplankton blooms make them preferable to study compared to studies of the effects of iron released from a ship. Data from these experiments, and from other islands in the Southern Ocean, is investigated in the context of the results found around the Crozet Plateau. The circulation patterns around the Crozet Plateau are studied in detail, with particular emphasis on understanding where surface water that has passed close to the Crozet Islands flows, as this is a known source of iron to the surface water. The surface mixed layer depth and incoming irradiance are also studied so that the variation in light availability with time and latitude can be understood. The distribution of phytoplankton is studied through satellite chlorophyll-a images, with values adjusted to match those observed in situ during the research cruises. The initial development of the bloom is controlled by variations in light availability but the advection and lateral mixing of iron is sufficient to explain the spatial extent of the bloom and the variations in peak chlorophyll-a concentrations. The variability of the strength of the bloom is driven mostly by variations in the iron utilization by phytoplankton during the preceding winter and wind-driven variations in the circulation.

Global Navigation Satellite System-Reflectometry (GNSS-R) is an innovative technique for ocean remote sensing. It exploits signals of opportunity from navigation constellations, to look primarily at the ocean surface roughness. This dissertation investigates the capabilities of GNSS-Reflectometry to convey information about sea state, and the response of GPS reflected signals to different wind and wave conditions. This is done through the use of real GPS-R data, as well as through simulations of the scattering of GPS signals from realistic ocean surfaces. A retrieval of ocean roughness parameters is carried out on four GNSS-R datasets, collected onboard the UK-DMC Satellite. Measured Delay-Doppler Maps (DDMs) from GPS-R data are least-square fitted to DDMs simulated using a theoretical (Zavorotny-Voronovich, or Z-V) model. The retrieved parameters are compared and validated against measurements from co-located NDBC buoys, and theoretical calculations, and a reasonable agreement is observed. A GPS scattering simulator is then presented, that uses explicit 3D ocean surface representations, and an innovative facet-based polarimetric scattering model, called the Facet Approach (FA). The results of the GPS scattering simulator are first analysed in the spatial domain, as 2D maps of normalized radar cross section and polarization ratio. These maps exhibit clear features related to the explicit waves of the underlying sea surface. A detailed analysis of noise-free idealized DDMs of both scattered GPS power and polarization ratio is then carried out for a variety of different ocean surfaces, both linear and non-linear. This analysis stresses in particular the importance of wave directionality as a crucial parameter that influences the DDM sensitivity to sea surface roughness ii and wave direction, and the polarization effects on the scattered signal. It is revealed that polarization is another important parameter, as it can convey information on wave direction and directionality, and potentially be used to identify nonlinearities on the sea surface. Finally, an investigation of subsets of noise-free idealized DDMs, computed at a high DD resolution, is presented, and its potentials as a tool for detecting the explicit waves on the sea surface are highlighted. The research and analyses of this PhD dissertation represent novel contributions to the field of GPR-Reflectometry. In particular, the analysis of satellite GPS-R data is the first one that makes use of the whole DDM, and of data collected onboard a satellite. The results from the GPS scattering simulator provide a comprehensive description of how and to what extent different parameters of the ocean surface, linked to wind and waves, influence the scattering of GPS signals. Furthermore, they identify polarization as a new crucial parameter for future GNSS-R missions, since it provides additional information about sea-state, and might be used as a potential indicator of sea surface nonlinearities.

In the oligotrophic Atlantic Ocean small algae are the dominant fixers of inorganic carbon. In situ experiments have shown that a large proportion of these algae are mixotrophs - eating bacteria (bacterivory) as well as obtaining energy from sunlight. Bacterivory performed by algae has implications for our understanding of the role of ultraplankton (<5 μm) in biogeochemical cycling. The motivation of this thesis is to explore how mixotrophy may be modelled in the subtropical Atlantic using a data driven approach. An ecosystem model incorporating ultraplankton mixotrophy was developed, constructed and parameterised using in situ data, initially through network analysis and later using a μ-Genetic Algorithm technique. The model highlights the key role of mixotrophy in the cycling of nutrients, in a region where fast nutrient turnover is important for the functioning of the ecosystem. In addition, the model reveals that bacterivory is the predominant route of nutrient acquisition for these mixotrophs and suggests that mixotrophy in this low nutrient region is an adaptive rather than a survival mechanism. This thesis also addresses wider questions related to model structure and assumptions. The need for an explicit dissolved organic phosphate variable in an ecosystem model for the oligotrophic Atlantic is questioned through in situ radio-nucleotide bioassay techniques. Additionally, ultraplankton spatial variability is statistically assessed and used to demonstrate that a zero-dimensional model is not necessarily applicable to an entire region, despite the ultraplankton community within that region being statistically similar according to multivariate analyses. Furthermore a comparison of in situ to remotely sensed data shows that ocean colour is limited in its ability to detect ultraphytoplankton, making the use of such data to calibrate and assess future models difficult. This thesis therefore not only contributes to our ability to model the oligotrophic Atlantic but more broadly to our understanding of the role of mixotrophs within it.

Long-term variability of the Red Sea deep water (RSDW) properties was investigated using hydrographic data stretching back to the beginning of the 19th century. The analysis of the potential temperature and salinity indicate that there is a signal of cooling and freshening trends between 1950 to 2011 in the RSDW by an average of 35.5 x10-4 ± 5.6x10-4 oC yr-1 and 13.8x10-4 ± 2.8x10-4 psu yr-1 respectively. Both trends of cooling and freshening are statistically significant with a confidence level of more than 95%. These cooling and freshening trends are consistent with the net heat loss trend in the three source regions for the deep water formation of the Red Sea by an average of -1.12 ± 0.49 Wm-2, -1.75 ± 0.49 Wm-2 and -1.58 ± 0.47 Wm-2 for the northern part of the Red Sea and the Gulfs of Suez and Aqaba respectively. The results suggest that the potential temperature and salinity seem to have decreased between 1950 and 2011 by as much as 0.12 oC and 0.13 psu respectively. These changes observed in the potential temperature and salinity in the RSDW are consistent throughout the Red Sea basin (subdivided into 2o grids) for the last three decades (1977-2011). An inverse box model of the Red Sea is constructed using two hydrographic sections in the southern basin during August 2001 from research vessel (R/V) Maurice Ewing to provide quantification of the summer field fluxes (volume, heat and salt). The results show that the volume transport of the Red Sea outflow water (RSOW) to the Indian Ocean through the Strait of Bab el Mandeb is 0.11 ± 0.06 Sv (1 Sv = 106 m3 s-1). There is a heat loss by advection with a magnitude of 23.5 ± 5.7 W m-2 during a summer month (August) that fits well with the previous estimate by Patzert (1974b) with magnitude of 21.81 W m-2 and with magnitude of -22 Wm-2 based on data from i ii Sofianos et al. (2002). There is a salt loss by advection with a magnitude of 0.98 x109 kg s-1 this estimate is supported by the analysis of Tragou et al. (1999) which gives a magnitude of 0.8 x109 kg s-1.

No description available.

The modelling of ocean waves is now carried out routinely at meteorological centres around the world. However, little is know about the source of the uncertainty in the predictions of waves produced, and sources can be numerous depending on the specific application. Historically it was felt that the dominant source of uncertainty originated from incomplete knowledge and expression of forcing winds. However more recent studies have focused on the underlying physical processes and their representations, with some authors questioning whether the limitation of the current modelling approach has been reached. Recently, methods for the statistical analysis of complex computer models, including models such as those used for wave prediction, have been developed. In this thesis these methods are applied to perform the first ever uncertainty analysis of a wave model. These new methods are applied to the state of the art wave model Wavewatch IIIr. This thesis principally explores the effect of tuning parameter uncertainty relating to the “Tolman and Chalikov” input and dissipation parameterisation, the discrete interaction approximation scheme for nonlinear wave-wave interactions and uncertainty about wind forcing, on wave simulation output, in a range of idealised cases, and realistically on Lake Michigan. The effectiveness of the statistical methods is first demonstrated in simple cases, before analysis is performed for progressively more complex simulations. In each case, uncertainty measures are computed with respect to simulation output in terms of summary wave statistics, typically including significant wave height and peak period. The analysis reveals nonlinear response and the relative importance of the various input, which in turn shows the active physical processes, and where the greatest sources of uncertainty lie. Both uncertainty about wind forcing and the process of nonlinear wave-wave interactions are found to be dominant in all cases, although energy dissipation is important in growing sea states. Finally, observational wave height data is used to perform a parameter calibration for simulations of stormy conditions on Lake Michigan, leading to improved performance.

This study seeks to investigate the global circulation and re-emergence of Subantarctic Mode Water (SAMW), which is thought to be important in providing the source of nutrients to drive biological production over large proportions of the world ocean. For this purpose, the HYbrid isopycnic-cartesian Coordinate Ocean general circulation Model (HYCOM) is congured to simulate the global ocean circulation for timescales of up to centuries. After development and validation of the model, a control run of 120 years is undertaken in order to reach a near-equilibrium. A tracer is then injected into the SAMW formation regions and used to track the global circulation of SAMW for a further 150 years. The upwelling regions in which SAMW is returned to the upper-ocean mixed layer are identied, and the importance of dierent mechanisms of SAMW/nutrient re-emergence north of the Southern Ocean is assessed. It is found that for the global ocean north of 30S, entrainment driven by surface buoyancy loss and/or wind stirring is the most important mechanism for SAMW re-emergence in the model (accounting for 33% of the total SAMW upwelling). Substantial regional variation in upwelling mechanisms exists though. Regridding mixing driven by the Ekman pumping eect and shear-induced mixing dominate SAMW upwelling in the equatorial oceans. Induction at isopycnal outcrops is critical to SAMW upwelling in the high-latitude North Atlantic. It is found that SAMW has little in uence in the North Pacic when compared with the North Atlantic and the dierent circulation and upwelling patterns of SAMW in the Northern Hemisphere are investigated in the model. The conned penetration distance of SAMW to the North Pacic is found to be associated with the relatively lighter density levels that the SAMW core resides at in the Pacic Ocean, and the dierent vertical extensions of the Equatorial Under Current (EUC) and Kuroshio Current (KC) there. The mechanisms of nutrient supply into the North Atlantic Ocean in association with the SAMW has been studied in more detail with a set of perturbation experiments. Intercomparison shows that the relatively high nutrient concentrations and primary production in the upper thermocline isopycnals and surface within the Gulf Stream (GS) are likely to be associated with the imported nutrients through isopycnal transport, and diapycnal mixing need not to be invoked to explain the Gulf Stream's high nutrient concentrations. Based on the tracer experiment, a new nutrient circulation and upwelling model is proposed for the North Atlantic Ocean, which comprises four steps following the seasonal cycle of the thermocline.

The 3D Chirp sub–bottom profiler acquires a true 3D seismic volume with decimetric horizontal and centimetric vertical resolutions, providing an ideal platform for shallow–water engineering, archaeology, military, and geological studies. In this thesis, I show how simple processing flows built around a combination of standard Chirp/Vibroseis techniques and well known industry methods produce effective and impressive results by considering an object identification case study in a shallow–water, harbour setting (Vardy et al., 2008). Both stacked and migrated volumes are used to identify 89 individual buried targets that are correlated with coincident objects. Through subsequent dredging, a 100 % detection success is demonstrated, along with the strong similarity between the migrated reflector morphology and co–incident object shape. However, this processing approach requires extensive manual input and very long processing times (� 1 month). For this reason, a new method for pre–stack 3D Kirchhoff imaging is developed. Correlation with a series of bandwidth limited theoretical source sweeps is used to frequency decompose the raw traces for pre–stack time migration using a constant velocity. By accommodating dispersion through imaging a series of band limited traces, rather than through Fourier Transform, processing times are reduced from � 1 month to c. two days for the object detection volume (i.e., approaching real–time application). The effectiveness of this new algorithm is examined using several synthetic volumes, allowing the degenerative effects of gaps in the fold to be explored. Finally, the application of the 3D Chirp system to geological cases is demonstrated through the geomorphological mapping of a sequence of mass movement events in Windermere, UK Lake District. Three mass movement deposits are identified in a 100 m by 400 m survey area. Through mapping of the package distributions and their interaction with the pre–existing sediments stratigraphy, they are identified as Younger Dryas climate amelioration deposits, resulting from the rapid deposition of gravitationally unstable, unconsolidated sediments. A metre–scale structural interpretation allows the depositional regimes (two being debris flow and the third a mass flow deposit) and dominant transport directions to be inferred.