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The main object of this thesis was to investigate the possibility of integrating a visualization of meteorological data in an interactive GIS-based simulation environment. The work was carried out at at the Swedish Defence Research Agency (FOI). Focus was put on meteorological parameters affecting radar signals. The task consisted of mapping of existing visualization methods used for weather and investigating suitable data sources and structures. Furthermore, the work was implemented in Java and NASA's API WorldWind. The result was evaluated through a semi-structured interview held with a focus group at FOI. The data chosen was model data describing precipitation rate from the European organization ECMWF's open database. A software module was developed to decode and structure the data which were later fetched and visually represented using symbols from the MIL-STD-2525 standard. The main conclusion drawn from the interview was that the proposed implementation was suitable for some scenarios. Alternative visualisations have to be developed from which the user will be able to choose from. The data module serves together with the symbols as a good start for further visualizaiton work.

Spatially distributed estimates of meteorological data are becoming increasingly important as inputs to spatially explicit landscape, regional, and global models. Accurate estimates of meteorological values such as temperature, precipitation, and evapotranspiration are required for a number of landscape scale models, including those of regeneration, growth, and mortality in forest ecosystems. Given a set of meteorological data, researchers are confronted with a variety of stochastic and deterministic interpolation methods to estimate meteorological variables at unsampled locations. Depending on the spatial attributes of the data, accuracies may vary widely among different spatial interpolation methods. The choice of spatial interpolator is especially important in mountainous regions where data are sparse and variables may change over short spatial scales. While there have been comparisons of interpolation methods, few research efforts have been directed towards comparing the effectiveness of different spatial interpolators in predicting temperature. Due to the additional effort kriging and cokriging entails, it was decided to compare the effectiveness of kriging and cokriging in estimating mean, maximum, and minimum temperature at unsampled locations with less computationally intensive interpolation techniques such as inverse distance weighted averaging, cubic splining, the fitting of a trend surface, polynomial regression, and the lapse rate method. Eight interpolation techniques (inverse distance squared, optimal inverse distance, cubic splining, trend surface analysis, regression, kriging, cokriging, and the lapse rate method) were compared in their ability to predict temperature at unsampled locations. Temperature data for two regions, two scales (minimum and maximum temperatures) and three temporal scales (10 year mean, seasonal, and daily) were prepared and the eight methods were compared on the basis of bias, MAE, and MSE. In addition, summary statistics of interpolated mean, minimum, and maximum temperatures were recorded to determine how well the interpolated data represented the original temperature values. This dissertation provides evidence that certain apriori data characteristics such as temperature range, temperature variance, and temperature correlation with elevation may influence interpolator choice. The dissertation results also indicate that spatial scale and the relative spatial density and distribution of sampling stations may influence interpolator choice. These results should be of interest to scientists studying global warming. The MAEs associated with interpolation techniques which did not use ancillary information were far greater than the 0.5°F to 1.0°F estimate of global warming over the past 100 years. The use of regression techniques which utilize the relationship between temperature and elevation as ancillary information offers significant improvement over the current inverse distance weighting methods. The dissertation also shows that when station elevations are not representative of regional elevations, bias occurs. In Region 2, stations were underrepresented for higher elevations. Interpolation techniques which did not use elevation as ancillary information were biased 1.0°F to 3.0°F above techniques which used elevation. While it is unclear what the extent of this effect is on a global scale, one would suspect the use of distance weighting techniques would bias global estimates upwards. These dissertation results should also be of interest to scientists who use kriging and cokriging to interpolate irregularly spaced data onto a rectangular grid. The results indicate that when data are isotropic, less subjective methods, such as optimal inverse distance, have lower MAE values. The semivariogram fitting methodology outlined in this dissertation demonstrates how to fit semivariograms iteratively using an indicative goodness of fit (IGF) metric. Semivariogram fitting using an IGF is less subjective and more accurate than traditional fit-by-sight methods. Despite its mathematical elegance, kriging and cokriging did not perform better than many other less computationally intensive methods. In addition, when there is a more intensely sample covariate which is highly correlated, polynomial regression gave far better results than kriging or cokriging. The results of this dissertation should also be of interest to users of geographic information systems (GISs). Because climatic data such as temperature is sampled from an irregular network, a number of interpolation techniques can be used to convert the data to a regular grid for use in visualization, models and GISs. This dissertation shows that the choice of spatial interpolator can influence the resulting data accuracy. In addition, data attributes influence the choice of interpolator. What is dissertation shows, is that through preliminary data analyses, an interpolator may be chosen which yields the most accurate grid for input into a GIS. It should be noted that this dissertation has wider ranging applications beyond the three examples mentioned above. The results should be of interest in any field where point data is interpolated onto a regular grid. Additional application areas include, but are not limited to, medical imaging, scientific visualization, weather forecasting, ecological modeling, forestry, petroleum exploration, and hydrological modeling. / Ph. D.

In this paper, a set of local radiosonde meteorological data, from 1990 to 2005, have been used to statistically analyze the refractivity gradient, DeltaN, at the lowest 65 m, 100 m and 1 km of the atmosphere above the surface of the Earth in the Gulf region. These three levels are the reference atmospheric layers in which the refractivity gradients have been evaluated by the ITU-R Recommendations P.453-10 and P.452-12The vertical variations of the refractivity profile aredisplayed through the cumulative distributions of the refractivity gradients at the targeted levels. The obtained results are compared for the three layers and also compared with the estimated values in the ITU maps and tables when available. Index Terms – Atmospheric refraction, Refractivity gradient.

The understanding of the dynamics of the climatic variables is critical to model and predict climatic and environmental changes. Traditional measures collected by the meteorological stations network are dispersedly located throughout the territory in the northern high latitudes and errors associated to these variations can be considerable. Our goal is to evaluate the contribution of the remote sensing by passive microwaves compared to the ground measurements for better characterizing the variations in the surface temperature during the winter. In the presence of snow, extraction of the surface parameters by microwave measurements is a complex and ill-conditioned problem. We evaluated a semi-empirical relation based on a theoretical analysis to estimate the surface temperatures with the measured brightness temperatures at 19 and 37 GHz (vertical polarization). Simulations of emissivity made with the Helsinki Technology University (HUT) model, the knowledge of the land cover, and the forest biomass enable us to define this relationship.The results of the comparison between the calculated surface temperatures and the air temperatures for the entire Canada (137 stations) and for two winters, 1992-93 and 2002-03 (16359 measurements) show a significant correlation with an estimation error ranging between 4 and 7[degrees Celsius] according to the regions considered. These results are discussed according to region and type of land cover (grassland, forest, tundra).

Os centros operacionais e de pesquisa em previsão numérica do tempo geralmente trabalham com uma grande quantidade de dados complexos multivariados, tendo que interpretá-los num curto espaço de tempo. Técnicas de visualização científica podem ser utilizadas para ajudar a entender o comportamento atmosférico. Este trabalho descreve a arquitetura e as facilidades apresentadas pelo sistema VisualMet, que foi implementado com base em um estudo das tarefas desenvolvidas pelos meteorologistas responsáveis pelo 8º Distrito de Meteorologia, em Porto Alegre. Este centro coleta dados meteorológicos três vezes ao dia, de 32 estações locais, e recebe dados similares do Instituto Nacional de Meteorologia, localizado em Brasília, e do National Meteorological Center, localizado nos Estados Unidos. Tais dados são resultados de observações de variáveis tais como temperatura, pressão, velocidade do vento e tipos de nuvens. As tarefas dos meteorologistas e as classes de dados foram observadas e analisadas para definir as características do sistema. A arquitetura e a implementação do VisualMet seguem, respectivamente, uma abordagem orientada a ferramentas e o paradigma de programação orientada a objetos. Dados obtidos das estações meteorológicas são instancias de uma classe chamada "Entidade". Três outras classes de objetos representando ferramentas que suportam as tarefas dos meteorologistas foram modeladas. Os objetos no sistema são apresentados ao usuário através de duas janelas, "Base de Entidades" e " Base de Ferramentas". A implementação da "Base de Ferramentas" inclui ferramentas de mapeamento (para produzir mapas de contorno, mapas de ícones e gráficos), ferramentas de armazenamento (para guardar e recuperar imagens geradas pelo sistema) e uma ferramenta de consulta (para ler valores de variáveis de estações selecionadas). E dada especial atenção a ferramenta de mapa de contorno, onde foi utilizado o método Multiquádrico para interpolação de dados. O trabalho apresenta ainda um estudo sobre métodos de interpolação de dados esparsos, antes de descrever detalhadamente os resultados obtidos com a ferramenta de mapa de contorno. Estes resultados (imagens) são discutidos e comparados com mapas gerados manualmente por meteorologistas do 8º Distrito de Meteorologia. Possíveis extensões do presente trabalho são também abordadas. / The weather forecast centers deal with a great volume of complex multivariate data, which usually have to be understood within short time. Scientific visualization techniques can be used to support both daily forecasting and meteorological research. This work reports the architecture and facilities of a system, named VisualMet, that was implemented based on a case study of the tasks accomplished by the meteorologists responsible for the 8th Meteorological District, in the South of Brazil. This center collects meteorological data three times a day from 32 local stations and receives similar data from both the National Institute of Meteorology, located in Brasilia, and National Meteorological Center, located in the United States of America. Such data result from observation of variables like temperature, pressure, wind velocity, and type of clouds. The tasks of meteorologists and the classes of application data were observed to define system requirements. The architecture and implementation of Visual- Met follow the tool-oriented approach and object-oriented paradigm, respectively. Data taken from meteorological stations are instances of a class named Entity. Three other classes of tools which support the meteorologists' tasks are modeled. Objects in the system are presented to the user through two windows, "Entities Base" and "Tools Base". Current implementation of the "Tools Base" contains mapping tools (to produce contour maps, icons maps and graphs), recording tools (to save and load images generated by the system) and a query tool (to read variables values of selected stations). The results of applying the multiquadric method to interpolate data for the construction of contour maps are also discussed. Before describing the results obtained with the multiquadric method, this work also presents a study on interpolation methods for scattered data. The results (images) obtained with the contour map tool are discussed and compared with the maps drawn by the meteorologists of the 8th Meteorological District. Possible extensions to this work are also presented.

<p>Visualization is the process of constructing methods, which are able to synthesize interesting and informative images from data sets, to simplify the process of interpreting the data. In this thesis a new approach to construct meteorological visualization methods using neural network technology is described. The methods are trained with examples instead of explicitely designing the appearance of the visualization.</p><p>This approach is exemplified using two applications. In the fist the problem to compute an image of the sky for dynamic weather, that is taking account of the current weather state, is addressed. It is a complicated problem to tie the appearance of the sky to a weather state. The method is trained with weather data sets and images of the sky to be able to synthesize a sky image for arbitrary weather conditions. The method has been trained with various kinds of weather and images data. The results show that this is a possible method to construct weather visaualizations, but more work remains in characterizing the weather state and further refinement is required before the full potential of the method can be explored. This approach would make it possible to synthesize sky images of dynamic weather using a fast and efficient empirical method.</p><p>In the second application the problem of computing synthetic satellite images form numerical forecast data sets is addressed. In this case a mode is trained with preclassified satellite images and forecast data sets to be able to synthesize a satellite image representing arbitrary conditions. The resulting method makes it possible to visualize data sets from numerical weather simulations using synthetic satellite images, but could also be the basis for algorithms based on a preliminary cloud classification.</p> / Report code: LiU-Tek-Lic-2004:66.

Kατά τις τελευταίες δύο δεκαετίες θεωρείται ότι υπάρχουν ενδείξεις πιθανού συσχετισμού των μεταβολών του εκλυόμενου ραδονίου στο έδαφος και της σεισμικής δραστηριότητας. Παρότι στην Ελλάδα εκδηλώνεται το μεγαλύτερο μέρος της σεισμικής δραστηριότητας της Ευρώπης, δεν έχουν πραγματοποιηθεί συστηματικές έρευνες έως τώρα. Η περιοχή της διατριβής καλύπτει την ανάγκη ανάλυσης της έκλυσης ραδονίου από περιβαλλοντικές παραμέτρους και τη σεισμικότητα. Το πείραμα χωροθετήθηκε στην περιοχή του Κορινθιακού κόλπου λόγω του ότι: 1) παρουσιάζεται υψηλή σεισμικότητα, η σεισμικότητα σε αυτή την περιοχή δε είναι εντοπισμένη σε ένα συγκεκριμένο τμήμα της, αλλά χαρακτηρίζει την ευρύτερη περιοχή. 2) Στην περιοχή εκδηλώνονται συχνά σεισμικά γεγονότα όλων των μεγεθών, σχετιζόμενα με τη σεισμικότητα της ίδιας της περιοχής, αλλά και λόγω διέγερσης σεισμικών ρηγμάτων στην εγγύς περιοχή (π.χ. σεισμοί Αλκυονίδων 1981 και σεισμοί Αθήνας 1999). 3) Η ύπαρξη στην περιοχή ενός μεγάλου αριθμού ρηγμάτων, τα οποία έχουν σαφή επιφανειακή έκφραση. Η ύπαρξη ρηγμάτων με σαφή επιφανειακή έκφραση δίνει επιπλέον τη δυνατότητα μέτρησης της ροής ραδονίου μέσα από ένα ρήγμα. 4) Στην περιοχή μελέτης υπάρχουν καλής ακρίβειας σεισμολογικά και μετεωρολογικά δεδομένα, έτσι ώστε να μπορεί να συσχετισθεί η επίπτωση των μετεωρολογικών αλλαγών με τις μετρήσεις ραδονίου. Η συγκεκριμένη περιοχή δε χαρακτηρίζεται από βίαιες μετεωρολογικές μεταβολές, οι οποίες επηρεάζουν την έκλυση του ραδονίου. / Over the last decades evidence for correlation between radon emission and earthquake activity suggests that monitoring of radon in soil gas can be used as a method to predict future earthquakes. However, although the method is promising for earthquake prediction and most of the seismic activity in Europe is released in Greece, no systematic experiments were conducted so far. In this study we present preliminary results of a two years experiment through the monitoring of eight sites in the Megara basin. In each site, soil radon exhalation was monitored in shallow boreholes (80 cm deep), using CR39 films, which were exposed every 15-day. The Megara basin was selected as a study area for the following reasons: (a) the basin is actively deformed and most of this deformation is accommodated by strong historic earthquakes. The most recent of these events are the 1981 Corinth earthquake sequence. (b) Within the basin large faults have spectacular outcrops, and or still preserve seismic ruptures. Thus the tectonic setting of the monitoring sites is well known in its tectonic position. (c) The entire experiment is set up quite close to Athens, thus earthquake epicenters are calculated fairly well and detailed meteorological data are also available. The experiment includes a series of monitoring sites distributed from Megara town to the coast of the Alkyonides bay, that it well known as the epicenter of the 1981 Corinth earthquakes. In essence the coastal area of the Gulf is rather the surface expression of the South Alkyonides Fault zone. Surface displacement along this fault during the 1981 event reached up to 1 m north side down. Based on these monitoring sites, we present the first results regarding the background soil radon concentration in the Megara basin as well as radon exhalation through a fault. Specifically, we present data of radon exhalation through a still preserved co-seismic rupture, 20 north of the rupture on the hanging wall block and 200 m south of the rupture within the footwall block of the South Alkyonides Fault zone.

Le micotossine sono metaboliti tossici prodotti da funghi in grado di svilupparsi sulle derrate alimentari. Diverse strategie sono state considerate per risolvere questo problema studiando la crescita di funghi/produzione di micotossine. Questa tesi è focalizzata sullo sviluppo/validazione di modelli matematici per prevedere la contaminazione di micotossine (deossinivalenolo, fumonisine e aflatossine) in cereali (mais/grano) sulla base di dati meteorologici. Il primo capitolo fornisce un’introduzione sulla teoria dei modelli e sui pat-sistemi modelizzati. Il secondo si concentra sulla presenza di tricoteceni e zearalenone nel frumento coltivato in Italia. Nel cap.3 sono stati confrontate le differenze predittive di modelli empirici/meccanicistici per la contaminazione di deossinivalenolo nel grano. Nel cap.4 è stata descritta la contaminazione da fumonisine e aflatossine in mais coltivato in Italia. I capitoli 5 e 6 analizzano il pato-sistema mais-Aspergillus flavus, il primo si concentra sulla sporulazione di A. flavus , il secondo sullo sviluppo di un modello per prevedere la contaminazione da aflatossina. Un altro modello meccanicistico per prevedere la presenza di fumonisina nel mais è descritto nel cap.7. L'ultimo capitolo riassume l'attività svolta nel progetto europeo MYCORED in cui sono stati coinvolti diversi paesi in tutto il mondo che hanno fornito i dati necessari per la validazione dei modelli. / Mycotoxin are toxic secondary metabolite produced by fungi able to colonize crops and thus posing a potential menace to human/animal health. Several strategies have been considered to mitigate the problem studying the variables related to mould growth and mycotoxin production. This thesis focuses on the development and validation of mechanistic models to predict mycotoxins (deoxinivalenol, fumonisins and aflatoxins) contamination in cereals (maize/ wheat) based on meteorological data. The first chapter introduce modelling theory, and patho-systems analysed. Chapter 2 focuses on trichothecenes and zearalenone occurrence in wheat produced in Italy. Predictive performance of empirical and mechanistic models for deoxnivalenol contamination in wheat were discussed in chapter 3. Chapter 4 described fumonisins and aflatoxins occurrence in maize grown in Italy. Chapters 5 and 6 analised the patho-system maize-Aspergillus flavus; the former focuses on the dynamics of A. flavus sporulation the lalatter on the development of a mechanistic model to predict aflatoxin produced by A. falvus. Another mechanistic model for Fusarium ear rot and fumosin production in maize (chapter 7). The last chapter summarised the activity done in the European project MYCORED in which several countries worldwide were involved and wheat and/or maize samples collected with data necessary for model validation.

Os centros operacionais e de pesquisa em previsão numérica do tempo geralmente trabalham com uma grande quantidade de dados complexos multivariados, tendo que interpretá-los num curto espaço de tempo. Técnicas de visualização científica podem ser utilizadas para ajudar a entender o comportamento atmosférico. Este trabalho descreve a arquitetura e as facilidades apresentadas pelo sistema VisualMet, que foi implementado com base em um estudo das tarefas desenvolvidas pelos meteorologistas responsáveis pelo 8º Distrito de Meteorologia, em Porto Alegre. Este centro coleta dados meteorológicos três vezes ao dia, de 32 estações locais, e recebe dados similares do Instituto Nacional de Meteorologia, localizado em Brasília, e do National Meteorological Center, localizado nos Estados Unidos. Tais dados são resultados de observações de variáveis tais como temperatura, pressão, velocidade do vento e tipos de nuvens. As tarefas dos meteorologistas e as classes de dados foram observadas e analisadas para definir as características do sistema. A arquitetura e a implementação do VisualMet seguem, respectivamente, uma abordagem orientada a ferramentas e o paradigma de programação orientada a objetos. Dados obtidos das estações meteorológicas são instancias de uma classe chamada "Entidade". Três outras classes de objetos representando ferramentas que suportam as tarefas dos meteorologistas foram modeladas. Os objetos no sistema são apresentados ao usuário através de duas janelas, "Base de Entidades" e " Base de Ferramentas". A implementação da "Base de Ferramentas" inclui ferramentas de mapeamento (para produzir mapas de contorno, mapas de ícones e gráficos), ferramentas de armazenamento (para guardar e recuperar imagens geradas pelo sistema) e uma ferramenta de consulta (para ler valores de variáveis de estações selecionadas). E dada especial atenção a ferramenta de mapa de contorno, onde foi utilizado o método Multiquádrico para interpolação de dados. O trabalho apresenta ainda um estudo sobre métodos de interpolação de dados esparsos, antes de descrever detalhadamente os resultados obtidos com a ferramenta de mapa de contorno. Estes resultados (imagens) são discutidos e comparados com mapas gerados manualmente por meteorologistas do 8º Distrito de Meteorologia. Possíveis extensões do presente trabalho são também abordadas. / The weather forecast centers deal with a great volume of complex multivariate data, which usually have to be understood within short time. Scientific visualization techniques can be used to support both daily forecasting and meteorological research. This work reports the architecture and facilities of a system, named VisualMet, that was implemented based on a case study of the tasks accomplished by the meteorologists responsible for the 8th Meteorological District, in the South of Brazil. This center collects meteorological data three times a day from 32 local stations and receives similar data from both the National Institute of Meteorology, located in Brasilia, and National Meteorological Center, located in the United States of America. Such data result from observation of variables like temperature, pressure, wind velocity, and type of clouds. The tasks of meteorologists and the classes of application data were observed to define system requirements. The architecture and implementation of Visual- Met follow the tool-oriented approach and object-oriented paradigm, respectively. Data taken from meteorological stations are instances of a class named Entity. Three other classes of tools which support the meteorologists' tasks are modeled. Objects in the system are presented to the user through two windows, "Entities Base" and "Tools Base". Current implementation of the "Tools Base" contains mapping tools (to produce contour maps, icons maps and graphs), recording tools (to save and load images generated by the system) and a query tool (to read variables values of selected stations). The results of applying the multiquadric method to interpolate data for the construction of contour maps are also discussed. Before describing the results obtained with the multiquadric method, this work also presents a study on interpolation methods for scattered data. The results (images) obtained with the contour map tool are discussed and compared with the maps drawn by the meteorologists of the 8th Meteorological District. Possible extensions to this work are also presented.