Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (p. 76-80).

Thesis (Ph.D.) - University of St Andrews, June 2009.

Thesis (M.S.)--University of Missouri-Columbia, 2005. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (December 13, 2006) Vita. Includes bibliographical references.

Master of Science / Department of Agronomy / William T. Schapaugh Jr / Yield in soybean (Glycine max (L.) Merr) needs to dramatically increase across the world to feed the growing population. Remote sensing and high-throughput phenotyping may provide a tool to better phenotype soybean genotypes. This research was conducted to: 1) examine the relationships between NDVI and CT with seed yield, maturity, lodging, and height, 2) determine if the time of day and growth stage have an effect on the spectral readings, 3) examine the relationships between spectral reflectance and traits associated with drought tolerance, and 4) evaluate how weather variables impact the ability of vegetative indices and canopy temperature to detect differences among genotypes. Ninety genotypes from the mapping population derived from the cross between KS4895 x Jackson were evaluated in Manhattan, KS, in 2013 and in McCune, Pittsburg, and Salina, KS in 2014. Genotypes were planted in a randomized complete bloc design in four-row, 3.4m long plots spaced 76 cm apart. Plant height, lodging, maturity and seed yield was collected on the center two rows of each plot. Spectral readings used to calculate a normalized differential vegetative index (NDVI) and canopy temperature (CT) were taken during reproductive growth. Nitrogen fixation trait and drought tolerance data was collected by the University of Arkansas. This population exhibited a substantial genetic variation for all traits evaluated. Correlations of NDVI and CT entry means with the agronomic traits were small and inconsistent. Time of day and growth stage were not important in differentiating genotypes. Differences in NDVI and CT did account for some genetic variation in drought tolerance traits, however, the strength of the associations were small. None of the weather variables were consistently associated with an increase or decrease in entry or error variance across the four environments. Stronger associations need to be established to use NDVI or CT to characterize differences in genotypes in a plant breeding program

Statistical post-processing techniques are used to remove systematic biases in modeled data. Models have shortcomings in the physical parameterization of weather events and have the inability to handle sub-grid phenomena successfully. The accuracy of forecasts interpolated to station points is limited by the horizontal resolution of the model. The magnitude of the bias at a station point depends upon geographical location and season. A neural network (NN) is a statistical downscaling method that seeks to model the linear or non-linear relationship between a set of different predictors and the predictand. NN’s have a training rule whereby the weights of connections between predictors and the predictand, are adjusted on the basis of the data. NN systems have been developed by using as input, different model variables from the NCEP Ensemble Prediction System (EPS) and Eta model to forecast minimum/maximum temperature and rainfall (Quantitative Precipitation Forecast (QPF) and Probability of Precipitation (PoP)), respectively. Results show some potential for improved NN forecasts over the forecast generated by the Numerical Weather Prediction (NWP) models. The implementation of a NN system can serve as a guidance tool in operational forecasting but with one difficulty that the NWP model has to be frozen, meaning no upgrades or changes on the model. / Dissertation (MSc)--University of Pretoria, 2009. / Geography, Geoinformatics and Meteorology / Unrestricted

The correlations between moon phases and precipitation maximums were investigated for selected stations in British Columbia in order to determine if they existed for: (a) individual stations; (b) grouped stations; (c) annual occurrences; (d) seasonal occurrences; and (e) geographic areas. The analysis consisted of a graphical presentation and a statistical test for randomness. Graphs of annual and seasonal moving totals for grouped and Individual stations were prepared. They were analyzed for peaks in the configuration of the graphs and for annual and seasonal components through the use of the X2p test. It is apparent from this study that there is a relationship between moon phases and precipitation maximums for grouped stations and individual stations in British Columbia. The evidence for the annual components of "lunar" precipitation for the individual stations shows, statistically, that the distributions are non-random and, graphically, that peaks are visible. Moreover, a shift of the peaks with latitude is discernible for the stations of British Columbia and it is suggested that this shift exists on a global scale. The evidence for the seasonal components of "lunar" precipitation for the individual stations is not as conclusive, either statistically or graphically. The seasonal graphs show peaks but the test for randomness yields inconsistent results. / Arts, Faculty of / Geography, Department of / Graduate

In this thesis, I introduce a promising framework for representing an air traffic flow (stream) and flow-management action operating under weather uncertainty. I propose to use a meshed queuing and Markov-chain model---specifically, a queuing model whose service-rates are modulated by an underlying Markov chain describing weather-impact evolution---to capture traffic management in an uncertain environment. Two techniques for characterizing flow-management performance using the model are developed, namely 1) a master-Markov-chain representation technique that yields accurate results but at relatively high computational cost, and 2) a jump-linear system-based approximation that has promising scalability. The model formulation and two analysis techniques are illustrated with numerous examples. Based on this initial study, I believe that the interfaced weather-impact and traffic-flow model analyzed here holds promise to inform strategic flow contingency management in NextGen.

Thesis. 1976. M.S.--Massachusetts Institute of Technology. Dept. of Meteorology. / Microfiche copy available in Archives and Science. / Bibliography: leaf 38. / by Alan L. Adams. / M.S.

Thesis. 1978. M.S.--Massachusetts Institute of Technology. Dept. of Meteorology. / Microfiche copy available in Archives and Science. / Bibliography : leaves 64-65. / M.S.

No description available.