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Dust forecasting has become important to military operations over the past three decades. Rules of thumb have been the primary resource for forecasting dust. In recent years, algorithms for weather models have been created to produce atmospheric dust concentration forecasts and are now coming into use operationally. The question becomes how good are the models and what causes errors in their forecasts? This study examines the accuracy of the U. S. Navy's Coupled Ocean Atmospheric Mesoscale Model dust module during the United Arab Emirates Unified Aerosol Experiment. The study also attempts to determine what causes any error if present. The primary method to verify the model's aerial coverage accuracy is through equitable threat score. Case studies are then conducted to verify the scores and identify sources of any errors identified. Results indicate the model performs well with respect to sourcing dust plumes. Errors in modeled aerial coverage as compared to real world observations appear to be the result of an inability for the model to properly advect suspended dust near the surface layer. Unconfirmed dust plumes in the model seemed to be the result of inaccurate surface characteristics.

Weather is essentially geo-spatial data that can be integrated with Geographic Information Systems (GIS). In this research a small prototype is designed and developed in order to demonstrate the basic capabilities of GIS-enabled operational meteorology. As the Air Force moves to net-centric operations, enabling weather information across an enterprise GIS is essential. Providing images is a fast and efficient means of enabling weather in a GIS. Providing the information in raw format is a better way to distribute GIS enabled weather. Since operators and users may still require an image format, both information and images should be provided. In order to provide the best possible support, Air Force Weather needs to rethink how it provides weather information, especially in a net-centric force. Air Force Weather has been slow to adopt this approach for various reasons such as a lack of bandwidth. The lack of resolution and accuracy of the numerical models was also a key consideration. While the models are still imperfect, their spatial resolution is now good enough to be used realistically in a GIS environment. The prototype developed for this research shows real-time delivery of weather information in GIS is possible and practical.

Ce travail s'interroge sur les fondements de l’Etat moderne en Afrique à travers l’oeuvre de Hegel. Confronter l’oeuvre de Hegel avec les réalités africaines relève en soi de l’audace à cause de sa thèse polémique sur l’anhistoricité des cultures non occidentales et spécialement celles de l’Afrique. Cependant, la pensée politique de Hegel constitue un cadre théorique original capable d’interpréter l’actualité la plus gaie (comme la prospérité des nations) et la plus absurde (comme une guerre civile ou la pauvreté). Ce que les peuples sont, ils le doivent à leur histoire, leurs cultures et à leurs institutions. Des auteurs comme Hippocrate, Montesquieu et Karl Ritter avaient fait de l’environnement géographique le facteur des civilisations, des progrès techniques et scientifiques des peuples. Mais chez Hegel, les hommes doivent à l’Etat moderne d’être libres d’une liberté qui compénètre toutes les sphères de la vie éthique. Là où l’Etat n’est pas, il n’y a ni liberté ni progrès / This work wonders about the bases of the modern State in Africa through the work of Hegel. To confront the work of Hegel with African realities raises in oneself of the audacity because of its polemical thesis on the anhistoricity of the nonWestern cultures and especially those of Africa. However, the political thought of Hegel constitutes an original theoretical framework able to interpret the merriest topicality (like the prosperity of the nations) and absurdest (like a civil war or poverty). What the people are, they owes it with their history, their cultures and at their institutions. Authors like Hippocrates, Montesquieu and Karl Ritter had made geographical environment the factor of civilizations, technical and scientific progress of the people. But at Hegel, the men must at the modern State be free of a freedom which compénètre all spheres of the ethical life. Where the State is not, there is neither freedom nor progress

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (p. 63-69).

Stochastic Weather Generators (SWG) try to reproduce the stochastic patterns of climatological variables characterized by high dimensionality, non-normal probability density functions and non-linear dependence relationships. However, conventional SWGs usually typify weather variables with unjustified probability distributions assuming linear dependence between variables. This research proposes an alternative SWG that introduces the advantages of the Copula modeling into the reproduction of stochastic weather patterns. The Copula based SWG introduces more flexibility allowing researcher to model non-linear dependence structures independently of the marginals involved, also it is able to model tail dependence, which results in a more accurate reproduction of extreme weather events. Statistical tests on weather series simulated by the Copula based SWG show its capacity to replicate the statistical properties of the observed weather variables, along with a good performance in the reproduction of the extreme weather events. In terms of its use in crop growth models for the ratemaking process of new insurance schemes with no available historical yield data, the Copula based SWG allows one to more accurately evaluate the risk. The use of the Copula based SWG for the simulation of yields results in higher crop insurance premiums from more frequent extreme weather events, while the use of the conventional SWG for the yield estimation could lead to an underestimation of risks.

A study was conducted to quantify weather conditions at specific growth stages of Canadian western Spring wheat (Triticum aestivum) and relate those growing conditions to variations in wheat grade and quality characteristics and to develop pre-harvest prediction models for wheat quality using weather input data. Six Canadian western spring wheat genotypes were grown in five locations across the Canadian prairies during the 2003 and 2004 growing seasons. Intensive weather data was collected during the growing season at each location and used to calculate accumulated heat stress, useful heat, moisture demand, moisture supply, moisture use and moisture stress variables for numerous crop development stages. Grain samples were graded, milled and underwent an extensive analysis of flour, dough, and bread making quality. ANOVA indicated that genotype, environment and their interactions had significant effects on most quality parameters tested. Environmental contribution to wheat quality variance was considerably larger than the variance contribution of either genotype or GxE interaction. Using the weather and crop development stage information, significant regression equations with high regression coefficients were developed for most quality parameters using just a single independent weather variable. Multiple regression equations with even higher R2 values were developed using three complex weather variables, leading to the opportunity to predict wheat quality 2-5 weeks prior to harvest. Equally strong prediction models were developed utilizing basic weather variables which could be obtained from weather stations monitoring only daily maximum and minimum air temperature and precipitation. The development periods of planting to jointing and anthesis to soft dough were the stages most frequently exhibiting the highest correlation to wheat quality indicating weather needs to be monitored during the entire growing season to accurately predict quality. Grain quality forecast models were validated using 2005 weather and crop data. Prediction models developed from the 2003 and 2004 data required modification in order to accurately and consistently predict the grain properties in 2005. / February 2007

Ten years (1997 - 2006) of summer (June, July, August) daytime (14 - 00 Z) Weather Surveillance Radar - 1988 Doppler data for Houston, TX were examined to determine the best radar-derived lightning forecasting predictors. Convective cells were tracked using a modified version of the Storm Cell Identification and Tracking (SCIT) algorithm and then correlated to cloud-to-ground lightning data from the National Lightning Detection Network (NLDN). Combinations of three radar reflectivity values (30, 35, and 40 dBZ) at four isothermal levels (-10, -15, -20, and updraft -10 degrees C) and a new radar-derived product, vertically integrated ice (VII), were used to optimize a radar-based lightning forecast algorithm. Forecasts were also delineated by range and the number of times a cell was identified and tracked by the modified SCIT algorithm. This study objectively analyzed 65,399 unique cells, and 1,028,510 to find the best lightning forecast criteria. Results show that using 30 dBZ at the -20 degrees C isotherm on cells within 75 km of the radar that have been tracked for at least 2 consecutive scan produces the best forecasts with a critical success index (CSI) of 0.71. The best VII predictor was 0.734 kg m-2 on cells within 75 km of the radar that have been tracked for at least 2 consecutive scans producing a CSI of 0.68. Results of this study further suggest that combining the radar reflectivity and VII methods can result in a more accurate lightning forecast than either method alone.

Weather is a major contributing factor in aviation accidents, incidents and delays. Doppler weather radar has emerged as a potent tool to observe weather. Aircraft carry an onboard radar but its range and angular resolution are limited. Networks of ground-based weather radars provide extensive coverage of weather over large geographic regions. It would be helpful if these data can be transmitted to the pilot. However, these data are highly voluminous and the bandwidth of the ground-air communication links is limited and expensive. Hence, these data have to be compressed to an extent where they are suitable for transmission over low-bandwidth links. Several methods have been developed to compress pictorial data. General-purpose schemes do not take into account the nature of data and hence do not yield high compression ratios. A scheme for extreme compression of weather radar data is developed in this thesis that does not significantly degrade the meteorological information contained in these data. The method is based on contour encoding. It approximates a contour by a set of systematically chosen ‘control’ points that preserve its fine structure upto a certain level. The contours may be obtained using a thresholding process based on NWS or custom reflectivity levels. This process may result in region and hole contours, enclosing ‘high’ or ‘low’ areas, which may be nested. A tag bit is used to label region and hole contours. The control point extraction method first obtains a smoothed reference contour by averaging the original contour. Then the points on the original contour with maximum deviation from the smoothed contour between the crossings of these contours are identified and are designated as control points. Additional control points are added midway between the control point and the crossing points on either side of it, if the length of the segment between the crossing points exceeds a certain length. The control points, referenced with respect to the top-left corner of each contour for compact quantification, are transmitted to the receiving end. The contour is retrieved from the control points at the receiving end using spline interpolation. The region and hole contours are identified using the tag bit. The pixels between the region and hole contours at a given threshold level are filled using the color corresponding to it. This method is repeated till all the contours for a given threshold level are exhausted, and the process is carried out for all other thresholds, thereby resulting in a composite picture of the reconstructed field. Extensive studies have been conducted by using metrics such as compression ratio, fidelity of reconstruction and visual perception. In particular the effect of the smoothing factor, the choice of the degree of spline interpolation and the choice of thresholds are studied. It has been shown that a smoothing percentage of about 10% is optimal for most data. A degree 2 of spline interpolation is found to be best suited for smooth contour reconstruction. Augmenting NWS thresholds has resulted in improved visual perception, but at the expense of a decrease in the compression ratio. Two enhancements to the basic method that include adjustments to the control points to achieve better reconstruction and bit manipulations on the control points to obtain higher compression are proposed. The spline interpolation inherently tends to move the reconstructed contour away from the control points. This has been somewhat compensated by stretching the control points away from the smoothed reference contour. The amount and direction of stretch are optimized with respect to actual data fields to yield better reconstruction. In the bit manipulation study, the effects of discarding the least significant bits of the control point addresses are analyzed in detail. Simple bit truncation introduces a bias in the contour description and reconstruction, which is removed to a great extent by employing a bias compensation mechanism. The results obtained are compared with other methods devised for encoding weather radar contours.