The use of relatively small nonerodible elements (gravel) in stabilising a mobile surface was investigated. The aim of this study is to determine the different factors that affect the sand erosion due to the presence of small immobile rough elements. A regular array of spherical glass marbles was distributed on a nine metre length in the working section of a 12 metres long boundary layer wind tunnel. A bed of dune sand was spread over the marbles filling the gaps and covering the marbles. Four different shear velocities were used with two different marble spacings. The experimental results showed that the sand erosion and the sand flux along an isolated sand bed containing both mobile and immobile elements is neither uniform nor steady. The marbles start to be exposed at a certain position along the wind tunnel (the position of the maximum flux gradient and thus the maximum erosion). This is followed by a gradual exposure of the rows of marbles along the wind tunnel downwind of the initial exposure. This process continues until all the marbles are exposed downwind. The marbles are also exposed upwind of the initial exposure but this propagates at much lower rate and some marbles remain covered with sand at the end of the experiment. The sand flux measured at the downwind end of the working section remains constant for some time. When the marbles start to expose at some distance upwind, it starts to decrease rapidly. This indicates that the effect of the nonerodible elements on sand flux is not a local effect. A numerical model was developed to simulate the mechanism of the sand erosion observed in the wind tunnel experiments. The model helps in determining the different factors that influence the sand flux and sand erosion due to the exposure of the nonerodible elements. The model succeeded in simulating the erosion process and in providing a qualitative prediction of the sand level and sand flux distribution along the sand bed.

Meteorologists have spent decades attempting to predict the weather over extended periods of time. Complex models of up to several million variables can only produce reliable predictions of up to four days. By representing the atmosphere in a multi-dimensional 'phase space', we hope to find preferred areas of this space where the weather will persist. Using a simple simulation model we applied 9 clustering methods, some of which are new, to the simulated data. These methods represent 3 different levels of interactions between the user and the method. While developing new cluster methods, we also developed an outlier method which is shown to be better than 16 current multivariate outlier methods, based on a real dataset. The results of the simulation studies indicate that the more interaction between the user and the method, the better the outcome. Next we adapted the usual Ward's, and Caussinus and Ruiz's clustering methods to take time into consideration. This created 6 new time constraint clustering methods which we applied to simulated data from a new time dependent simulated model. Consistent patterns were found and the results also indicate that if we apply the usual Ward's clustering method on suspected time dependent data then we would achieve the best outcome only 35% of the time, at most. Finally we looked at ways of sieving transient observations from cluster groups and highlighting significant transitions by applying several techniques to a meteorological dataset.

No description available.

This study is concerned with the preparation of a research datum line in historical climatology and will provide a valuable data set for a wide variety of researchers in the future who are interested in the relationship between aspects of the coastal and climate systems and the human-coastal environment interface. The principal objective was to create and prepare an original historical data base on the storms, floods, erosion events and sand movements in Scotland 1500-1991 A.D.

This thesis studies the potential impacts of lapse rate changes on the altitudinal thermal resource gradient in Northern England and hence of climate change on upland climate. The extreme marginality of the Pennine uplands in terms of climatic potential for plant growth is explained by reference to the maritime climate. Because the ground-based temperature lapse rate controls the altitudinal thermal resource gradient, the variation of daily temperature lapse rates by season and airflow is described, using 22 stations ranging from 8 to 847 metres above sea-level. Multiple regression models developed for each airflow in each month successfully describe surface temperature variation in most cases. Such models are used as a basis upon which to describe altitudinal variations in growing season parameters such as accumulated temperatures and frost frequency, for the present climate. Airflow scenarios, based on the regression models, describe the effects of changes in relative frequencies of airflow patterns. The altitudinal gradient in, and absolute values of, growing season parameters depend strongly on relative frequencies of Atlantic westerlies and more blocked conditions. Assuming the annual l000 dºC (degree-day) isotherm to represent the altitudinal limit to agricultural cultivation, individual annual elevations between 1801 and 1990 vary by over 300 metres. Extreme sensitivity to the circulatory pattern is also illustrated. Effects of temperature variability within airflows are at least as strong as those of mean conditions in many cases. The use of General Circulation Model output (UKHI 2 times C0(_2)) leads to strong changes in climatic potential. For example, few areas retain an annual temperature accumulation below 1000 dºC. Changes in frost parameters are also marked. Other climatic and non-climatic factors would have to be considered to predict land-use change. Preliminary analysis suggests that changes in other climatic elements (e.g. windiness or precipitation) will complement the effects of a temperature increase.

The need for the mariner to have better weather indicators for efficient ship routeing in the middle latitudes is demonstrated. The benefits of an early appreciation of the subtle changes in storm behaviour is shown in a case study. Monitoring of ship's performance through a frontal depression using a modified Tropical Storm Avoidance simulation, also developed by the author, shows the penalties of not minimising the effects of wind and waves. To accomplish the aims of this project diagnostic models are developed, firstly to show the overall movement of the frontal depression within the trough - ridge system and secondly to investigate the field structure appertaining to depression movement and development. The graphical diagnostic model, an animated movie loop, allows the detail from two levels to be combined, surface fronts superimposed on the 500 mb flow, and played back in sequence showing the sophisticated nature of storm movement. This insight naturally lead to the development of a numerical diagnostic model to study simple elements such as wind fields. Analysis of these data enabled a movement indicator for the frontal depression, the "TEN" Indicator, to be formulated and is based on the 500 mb contours. Further improvements in the diagnostic numerical model allows the gradients of synthesised elements to be calculated without the loss of boundary values, and uses a cubic spline technique based on the Lagrange Interpolation. Error analysis of the calculated wind fields is carried out to test the accuracy of the methods employed. The model is then used to analyse a number of depressions using various development techniques to test the model. The results from four occasions, of the many observed, are demonstrated showing the development ideas of Sutcliffe, Petterssen and the Q-Vector based on quasi-geostrophic theory. Divergence is also considered using gradient wind substitutions, adjusted for surface friction and modified to satisfy curvature effects in ridge systems. The four occasions illustrated demonstrates the similarities between each method, the location of vertical motion within a deepening depression is located slightly in advance of the warm front. The normalising of these vertical field indicators against the surrounding flow allows the visual and numerical appreciation of ascent in weak fields. This approach may be an advantage in further studies of cyclogenesis. The model wind fields are tested using operational wind data, both being calculated from the same digitised pressure fields. The Oceanroutes Operational Routeing Model is employed, using these data, to produce two routes using both the analysis and forecast data. The case study demonstrates the usefulness of the "TEN" Movement Indicator as it provides the mariner with the tools to examine depression movement, to check forecasts and to give him the confidence to question routeing orders. This method requires data for the surface and the 500 mb level. Recommendations are suggested to modify the surface weather chart format for the mariner by including both movement and development information which would economise and optimise weather data transmission for greater shipboard efficiency.

No description available.

A three-dimensional, hydrostatic, primitive equation model is developed to simulate the Plymouth sea breeze. The equations are integrated forward in time on a staggered mesh with a domain of 64km X 64km X 3km, using a combination of central and upstream differencing. The ground surface is assumed to be smooth and the heat input to the atmosphere transferred vertically without the explicit use of diffusion coefficients. This results in a less stringent stability condition on the timestep, thus reducing the computational cost of the simulations. Sensitivity tests for a two-dimensional version are presented, examining the influence of atmospheric stability, the synoptic scale flow and the magnitude of the surface heat flux. The major features of the raesoscale circulation are well represented including the strong overland updraughts associated with the sea breeze front. Frontal propagation rates are estimated in each simulation. and are found to be in general agreement with available data for Southern England. The preliminary three-dimensional results concern the sensitivity of the model to variations in the synoptic scale flow and the coastal configuration. The former tests show a more vigorous system developing with an offshore synoptic flow and a much weaker circulation for the onshore. The second test illustrates the development of a bay-induced landward bulge in the temperature gradient resulting in an asymmetric distribution of onshore convergence zones. The final simulations represent two case studies of Plymouth sea breeze events during August 1983 and May 1984. The major features of the system are again well simulated, however several key problem areas are identified. These involve the influence of topographic variations, the numerical grid resolution, the heat flux parameterisation and the role of turbulent transfer. Recommendations for further research are proposed and include the application of a terrain-following coordinate scheme and a new observational initiative. In addition, the need for an improved heat flux parameterisation and turbulence closure are identified.

Cloud motion wind (CMW) determination requires tracking of individual cloud targets. This is achieved by first clustering and then tracking each cloud cluster. Ideally, different cloud clusters correspond to diiferent pressure levels. Two new clustering techniques have been developed for the identification of cloud types in multi-spectral satellite imagery. The first technique is the Global-Local clustering algorithm. It is a cascade of a histogram clustering algorithm and a dynamic clustering algorithm. The histogram clustering algorithm divides the multi-spectral histogram into'non-overlapped regions, and these regions are used to initialise the dynamic clustering algorithm. The dynamic clustering algorithm assumes clusters have a Gaussian distributed probability density function with diiferent population size and variance. The second technique uses graph theory to exploit the spatial information which is often ignored in per-pixel clustering. The algorithm is in two stages: spatial clustering and spectral clustering. The first stage extracts homogeneous objects in the image using a family of algorithms based on stepwise optimization. This family of algorithms can be further divided into two approaches: Top-down and Bottom-up. The second stage groups similar segments into clusters using a statistical hypothesis test on their similarities. The clusters generated are less noisy along class boundaries and are in hierarchical order. A criterion based on mutual information is derived to monitor the spatial clustering process and to suggest an optimal number of segments. An automated cloud motion tracking program has been developed. Three images (each separated by 30 minutes) are used to track cloud motion and the middle image is clustered using Global-Local clustering prior to tracking. Compared with traditional methods based on raw images, it is found that separation of cloud types before cloud tracking can reduce the ambiguity due to multi-layers of cloud moving at different speeds and direction. Three matching techniques are used and their reliability compared. Target sizes ranging from 4 x 4 to 32 x 32 are tested and their errors compared. The optimum target size for first generation METEOSAT images has also been found.

No description available.