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<p> An analysis was conducted to assess the relationship between the Arctic Oscillation (AO) and wintertime climatology of the Midwest and Tennessee Valley regions of the USA. In particular, this study focuses on variation in wintertime temperatures and snowfall totals during the top ten most positive and negative AO winters for the aforementioned regions. In addition, NCEP/NCAR reanalysis composite maps were created and examined to evaluate the relationship between certain atmospheric parameters and the opposing phases of the AO. In the Midwest and Tennessee Valley regions, variation in wintertime mean temperature and snowfall totals are associated with strong phases of the AO. The top ten most negative AO winters resulted in below average temperatures and above average snowfall totals. In contrast, the top ten most positive AO winters resulted in above average temperatures and below average snowfall totals. In addition, variation in mean wintertime temperature and snowfall totals is less significant during positive AO winters in comparison to negative AO winters. The top 10 most positive and negative AO winters appear to provide a significant link between anomalous middle and upper atmospheric circulation and atypical surface weather patterns across the Midwest and Tennessee Valley regions.</p>

<p>ABSTRACT Hail poses a substantial threat to life and property in the state of Florida. These losses could be minimized through better understanding of the relationships between atmospheric variables that impact hail formation in Florida. Improving hail forecasting in Florida requires analyzing a number of meteorological parameters and synoptic data related to hail formation. NOAA archive data was retrieved to create a database that was used to categorize text files of hail days. The text files were entered into the National Oceanic and Atmospheric Administration Earth System Research Laboratory website to create National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis maps of atmospheric variables for Florida hail days as well as days leading to the hail event. These data were then analyzed to determine the relationship between variables that affect hail formation, in general, across different regions and seasons in Florida using Statistical Product and Service Solutions. The reasoning for the differing factors affecting hail formation between regions, seasons and hail sizes were discussed, as well as forecasting suggestions relating to region and month in Florida. The study found that the majority of all hail that occurs in Florida is during the wet season. A low Lifted Index, high Precipitable Water and lower than average Sea Level Pressure, in most cases, is present during hail days in Florida. Furthermore, results show that Vector Wind magnitude increases as hail size increases. Additionally, several atmospheric variables useful to studying hail events, such as Lifted Index, Precipitable Water, Sea Level Pressure, Vector Wind and Temperature have significant correlations with each other depending on the region and season being observed. Strong correlations between low Lifted Index, high Precipitable Water values and the occurrence of hail events are discussed, as well as the relationship between temperature anomalies at various pressure levels and the occurrence of hail events.

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 &quot;TEN&quot; 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 &quot;TEN&quot; 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.

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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.

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