Ground-based weather radars provide information on the temporal evolution and the spatial distribution of precipitation on a macroscopic scale over a large area. However, the echoes measured by weather radars are always a superposition of forward and backward scattering effects which complicates their interpretation. The use of polarisation diversity enhances the number of independent observables measured simultaneously. This allows an effective separation of forward and backward scattering effects. Furthermore, it extends the capability of weather radars to retrieve also microphysical information about the precipitation. The dissertation at hand introduces new aspects in the field of polarimetric, ground-based, monostatic weather radars at S-, C-, and X-band. Relations are provided to change the polarisation basis of reflectivities. A fully polarimetric weather radar measurement at circular polarisation basis is analysed. Methods to check operationally the polarimetric calibration of weather radars operating at circular polarisation basis are introduced. Moreover, attenuation correction methods for weather radar measurements at linear horizontal / vertical polarisation basis are compared to each other, and the robustly working methods are identified. / Bodengebundene Wetterradare bieten Informationen über die zeitliche Entwicklung und die räumliche Verteilung von Niederschlag in einer makroskopischen Skala über eine große Fläche. Die Interpretation der Wetterradarechos wird erschwert, da sie sich aus einer Überlagerung von Vorwärts- und Rückwärtsstreueffekten ergeben. Die Anzahl der unabhängigen Wetterradarmessgrößen kann durch den Einsatz von Polarisationsdiversität erhöht werden. Dies ermöglicht eine effektive Trennung von Vorwärts- und Rückwärtsstreueffekten. Desweiteren erlaubt es die Bestimmung von mikrophysikalischen Niederschlagsparametern. Die vorliegende Dissertation betrachtet neue Aspekte für polarimetrische, bodengebundene, monostatische Wetterradare im S-, C- und X-Band. Gleichungen zur Polarisationsbasistransformation von Reflektivitätsmessungen werden eingeführt. Eine vollpolarimetrische Wetterradarmessung in zirkularer Polarisationsbasis wird analysiert. Neue Methoden, die eine Überprüfung der polarimetrischen Kalibrierung von Wetterradarmessungen in zirkularer Polarisationsbasis erlauben, werden betrachtet. Weiterhin werden Methoden zur Dämpfungskorrektur von Wetterradarmessungen in linearer horizontaler / vertikaler Polarisationsbasis miteinander verglichen und Empfehlungen von zuverlässigen Methoden gegeben.

Cette étude propose une unification des formulations mono- et multi-moments de la distribution granulométrique des pluies (DSD pour « drop size distribution ») proposées dans la littérature dans le cadre des techniques de mise à l’échelle (scaling). On considère dans un premier temps que la DSD normalisée par la concentration en gouttes (Nt, moment d'ordre 0 de la DSD) peut s’écrire comme une fonction de densité de probabilité (ddp) du diamètre normalisé par un diamètre caractéristique (Dc). Cette ddp, notée g(x) avec x=D/Dc, aussi appelé distribution générale, semble être bien représentée par une loi gamma à deux paramètres. Le choix d’un diamètre caractéristique particulier, le rapport des moments d’ordre 4 et 3, conduit à une relation d’auto-consistance entre les paramètres de la fonction g(x). Deux méthodes différentes, fondées sur 3 moments particuliers de la DSD (M0, M3 et M4) ou bien sur des moments multiples (de M0 à M6) sont proposées pour l’estimation des paramètres et ensuite évaluées sur 3 ans d’observations de DSD recueillies à Alès dans le cadre de l'Observatoire Hydrométéorologique Méditerranéen Cévennes-Vivarais (OHMCV). Les résultats révèlent que: 1) les deux méthodes d’estimation des paramètres ont des performances équivalentes; 2) malgré la normalisation, une grande variabilité de la DSD est toujours observée dans le jeu de données mis à l’échelle. Ce dernier point semble résulter de la diversité des processus micro-physiques qui conditionnent la forme de la DSD.Cette formulation est ensuite adaptée pour une mise à l’échelle avec un ou deux moments de la DSD en introduisant des modèles en loi puissance entre des moments dits de référence (par exemple l’intensité de la pluie R et / ou le facteur de réflectivité radar Z) et les moments expliqués (concentration en gouttes Nt, diamètre caractéristique Dc). De manière analogue à la première partie du travail, deux méthodes sont proposées pour estimer des paramètres climatologiques des DSD mises à l’échelle par un ou deux DSD moment(s). Les résultats montrent que: 1) la méthode d'estimation a un impact significatif pour la formulation de mise à l'échelle par un seul moment; 2) le choix du moment de référence dépend des objectifs d’étude: par exemple, le modèle mis à l'échelle par des moments d'ordre élevé produit une bonne performance pour les grosses gouttes mais pas pour les petites; 3) l’utilisation de deux moments au lieu d’un seul améliore significativement la performance du modèle pour représenter les DSD.Notre modèle est ensuite appliqué pour analyser la variabilité inter- événementielle selon trois paramètres (Nt, Dc et μ, ce dernier paramètre µ décrivant la forme de la fonction gamma). Différentes séquences de pluie ont été identifiées de façon subjective pour l’événement pluvieux intense des 21-22 octobre 2008 par des changements brusques des moments et/ou paramètres dans les séries temporelles correspondantes. Ces phases de pluie sont liées à des processus météorologiques différents. Une relation préliminaire est établie entre les observations radar et la variation des paramètres des DSD au sol telle que mesurée par le disdromètre. Les formulations de mise à l’échelle sont également appliquées pour des estimations des densités de flux d’énergie cinétique des précipitations à partir de l'intensité de la pluie et / ou de la réflectivité radar. Les résultats confirment que l’utilisation de deux moments (R et Z) améliore significativement les performances de ces modèles, malgré les caractéristiques d'échantillonnage très différentes des radars et des pluviomètres. Cette application ouvre des perspectives intéressantes pour la spatialisation de l’énergie cinétique des pluies dans le cadre des études sur le pouvoir érosif des pluies. / This study offers a unified formulation for the single- and multi-moment raindrop size distributions (DSD), which were proposed in the framework of scaling analysis in the literature. The key point is to consider the DSD scaled by drop concentration (Nt, 0th order DSD moment), as a probability density function (pdf) of raindrop diameter scaled by characteristic diameter (D/Dc). The Dc is defined as the ratio of the 4th to the 3rd DSD moment. A two-parameter gamma pdf model, with a self-consistency relationship, is found to be suitable for representing the scaling DSD formulation. For the purpose of parameter estimation, two different methods, based on three DSD moments (0th, 3rd and 4th moments) and multiple DSD moments (from 0th to 6th moments), are proposed and then evaluated through the 3-year DSD observations, collected at Alés within the activities of the Cévennes-Vivarais Mediterranean Hydrometeorological Observatory (CVMHO). The results reveal that: 1) the scaled DSD model parameterized by three moments (0th, 3rd and 4th moments) possesses a similar performance compared to that constructed by multiple DSD moments; 2) regardless the application of scaled technique, large variation is still exhibited in this climatological DSD scaled dataset. The scaled DSD formulation is, in a second step, adapted to the one- and two-moment scaling DSD formulations by introducing single and dual power-law models between the reference moments (e.g. rain rate R and/or radar reflectivity factor Z) and the explained moments (total concentration Nt, characteristic diameter Dc). Compared with previous DSD formulations presented in the literature, the presented approach explicitly accounts for the prefactors of the power-law models to produce a uniform and dimensionless scaled distribution, whatever the reference moment(s) considered. In the same manner, two methods based on 1) single or dual power-law models and 2) multiple DSD moments (from 0th to 6th moments), are proposed to estimate the climatological parameters in the one- and two-moment scaling DSD formulations. The results show that: 1) the estimation method has a significant impact on the climatological DSD formulation scaled by one moment; 2) the choice of the reference moment to scale DSD depends on the objectives of the research: e.g. the DSD model scaled by high order moment produces a good performance for large drops at the cost of a poor performance for the small ones; 3) using two scaling moments improves significantly the model performance to represent the natural DSD, compared to the one-moment DSD formulation. In terms of applications of scaling DSD model, the analysis of the inter-event variability is performed on the basis of the scaling formulation containing three parameters (Nt, Dc and µ describing the shape of the gamma function). Different rain phases can be identified by the sudden shifts of moments and parameters in DSD time series. It is found that these rain phases are well linked to different weather processes. And a preliminary relationship is established between the radar observations and DSD parameters. The climatological scaling DSD formulations are also used for the DSD reconstitutions and for rainfall kinetic energy flux density estimations by rain intensity and/or radar reflectivity factor. The results confirm that the application of two scaling moments (R and Z) improves significantly the performance of these models, regardless the different sampling characteristics between radar and raingauge.

Orientadores: Hilton Silveira Pinto / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola / Made available in DSpace on 2018-08-06T12:34:04Z (GMT). No. of bitstreams: 1 Avila_AnaMariaHeuminskide_D.pdf: 1178810 bytes, checksum: 3b4588a2aea0acf75e80295e33d537b6 (MD5) Previous issue date: 2006 / Resumo: Das variáveis que compõem o balanço hídrico, a precipitação é, certamente, o fator natural determinante da produção agrícola no país. A deficiência hídrica afeta praticamente todos os aspectos relacionados ao desenvolvimento e produtividade das culturas agrícolas. Por outro lado, o excesso de precipitação também pode influenciar negativamente na quantidade e na qualidade dos grãos a serem colhidos. Uma das maiores dificuldades para os tomadores de decisões é o acompanhamento das condições de tempo ocorridas, pois a rede de estações de superfície é deficiente e mal distribuída e nem sempre os dados são disponibilizados. Deve-se considerar ainda que a grande variabilidade espacial e temporal da precipitação impede que o pluviômetro represente adequadamente as chuvas incidentes em uma determinada área. A estimativa de precipitação a partir de imagens obtidas por satélites ou radares, em função da excelente cobertura espacial e temporal, pode apresentar-se como a única forma de obtenção de dados pluviométricos representativos de uma determinada área. O presente trabalho teve como objetivo propor um método de estimativa de precipitação para fins agrícolas, por meio de imagens do satélite meteorológico GOES-12, utilizando como ¿referência terrestre¿ os dados do radar meteorológico do IPMet/UNESP localizado em Bauru e quatro pluviômetros localizados dentro da área de cobertura do radar. Os resultados mostram que precipitações oriundas de nuvens mais frias são mais previsíveis pelos satélites do que provenientes de nuvens mais quentes. Nuvens com temperaturas em torno de 234K são capazes de produzir precipitação, mas nem toda nuvem com essa temperatura pode ser diretamente relacionada com precipitação na superfície. É demonstrado que o limiar de temperatura de brilho de 225K é o mais indicado para estimar precipitação em superfície, reforçando a hipótese de que há uma relação entre as informações obtidas pelo satélite e a precipitação em superfície. Assim como o modelo de MARSHALL E PALMER (1948) apresenta deficiências na relação Z-R, os modelos que utilizam a relação entre refletividade do radar e precipitação obtidos para a região não apresentaram melhor performance. O trabalho desenvolvido indica a possibilidade de acompanhamento de intervalos de estiagens em regiões agrícolas com o uso de imagens satelitarias tornando-se uma ferramenta adequada ao monitoramento agrícola e na estimativa de quebra de safras do país / Abstract: Considering the variables that compose the water balance, precipitation is certainly the most important factor for the agricultural yield in Brazil. The water deficiency affects practically all the aspects related to the development of the cultures. On the other hand, the precipitation excess can interfere as a negative factor in the quality of the final products. One of the highest difficulty for the decision makers in agriculture is the weather monitoring capability since, mainly in Brazil, the meteorological stations network is very poor, badly distributed and the data administrators normally impose restrictions for delivering information. The possibility of estimating precipitation from satellite images in function of the excellent space and time covering cicles can be analysed as an important way for collecting rainfall data for large areas. The present work has the objective of develop a method for estimating rainfall volume for agricultural purposes based on the use of meteorological images collected by the satellite GOES-12 having as terrestrial reference the images of the weather radar of IPMet/UNESP located in the city of Bauru, SP and 4 rain gauges inside the area of radar covering. The results showed that clouds with temperatures around 234K are capable to produce precipitation. As well as the model of MARSHALL and PALMER (1948) showed some deficiencies related to Z-R parameters, the models using the relation between reflectivity of the radar images and precipitation for the region also did not have better performance. The present work shows a possibility of using satellites images for estimating dry spells in large regions of the country that can interfere in the final yield of agriculture / Doutorado / Agua e Solo / Doutor em Engenharia Agrícola

A rotina operacional de monitoramento e previsão de tempo tem mudado bastante nos últimos anos. Além de informações convencionais existentes, que são bem conhecidas nos centros operacionais, os dados obtidos por sensoriamento remoto através de satélites, radares meteorológicos e sensores de detecção de descargas atmosféricas fornecem informações vitais e em tempo real, sendo estas as principais ferramentas para a detecção e previsão de tempestades severas. Na America do Sul, em especial o nordeste da Argentina, Paraguai, Uruguai e o sul do Brasil são regiões particularmente sujeitas a ocorrência de eventos severos (precipitação intensa, granizo, enchentes e intensa atividade elétrica, além de vendavais e tornados). No sul do Brasil, a distribuição mensal de chuvas é bastante uniforme, porém com alta variabilidade diária associada, principalmente, à passagem das frentes frias pela região e aos Sistemas Convectivos de Mesoescala, que se formam nessa região. A principal atividade econômica nessa região do Brasil é a agroindústria, diretamente dependente da distribuição da precipitação para a produção, como também susceptível aos fenômenos meteorológicos adversos associados. Além desta atividade, a região sul é responsável pela produção de, aproximadamente, 35% de toda a energia elétrica utilizada no país. O objetivo principal desta pesquisa foi estudar os aspectos espaciais e temporais da atividade elétrica durante os eventos de Sistemas Convectivos de Mesoescala (SCM) e examinar as possíveis relações entre o ambiente no qual essas tempestades se desenvolvem e as características elétricas e hidrometeorológicas desses, conforme observados por um radar meteorológico Doppler, e uma rede de detecção de relâmpagos, principalmente, e também com informações de satélites meteorológicos, dados de superfície e análises de modelos numéricos. Os resultados deste trabalho mostraram a importância das características dinâmicas na região, em especial a presença dos jatos em baixos níveis com a convergência de umidade na região para a organização dos eventos de SCM, como também a distribuição dos regimes de precipitação com características distintas de estrutura de refletividade observada por radar e também de atividade elétrica durante os eventos analisados. Espera-se que os resultados deste trabalho ajudem a entender melhor a relação dos sistemas convectivos de mesoescala e sua estrutura e evolução, como observados e detectados pelos sistemas remotos de monitoramento hidrometeorológico, além de um melhor entendimento e aperfeiçoamento de nossas habilidades de análise e previsão de tempo relacionados a esses eventos severos com precipitação intensa. / The operational routine in weather monitoring and forecasting has changed a lot in the past years. Besides conventional information, well known in operational centers, data from remote sensing such as satellite, weather radars and lightning detection network provide vital information in real time, as the main tools for severe weather detection and forecasting In South America, specially northeastern Argentina, Paraguay, Uruguay and southern Brazil are regions prone to severe weather (intense precipitation, hail, floddings, lightning, tornadoes and gust winds). In the South of Brazil, monthly precipitation distribution is very uniform, but with daily variability associated, mostly, with the passage of cold fronts through the region and to mesoscale convective systems, forming in this area. The major economical activity in this region of Brazil is agroindustry, directly dependent of precipitation distribution for production and also susceptible to diverse meteorological events associated with it. Besides this activity, the south region is responsible for the production of, approximately, 35\\% of all electric energy used in the country. The main goal of this research was to study spatial and temporal aspects of the electrical activity during MCS events, as observed by a weather radar and a network of ligthning detection sensors in the south of Brazil, and to examine possible relations between the environment in which these storms develop and electrical characteristics of these weather systems, using weather radar, lightning, satellite and numerical model information. The results of this work showed the importance of the dynamic characteristics in the regial, specially the presence of low level jets and humidity convergence in the region to organize MCS events, as well as a distribution of precipitation regimes whith distinct characteristics of radar reflectivity and electrical activity during the analysed events. With this work we expect to contribute with the understanding of the relation of MCS structure and evolution as observed and detected by hydrometeorological monitoring systems and to improve the comprehension and ability to analyse and forecast such severe weather systems.

Emerging technologies such as wireless local area networks and cellular telephones have dramatically increased the use of wireless communications services within the last 10 years. The shortage of available spectrum exists due to increasing demand for wireless services and current spectrum allocation regulations. To alleviate this shortage, Research aims to improve spectral efficiency and to allow spectrum sharing between separately managed and non-coordinating communications systems. This thesis explores the feasibility of spectrum sharing between airborne weather radar and wireless local area networks at 9.3 GHz – 9.5 GHz. Characteristics of flight paths of aircraft using airborne weather radar and the low duty cycle of radar transmissions offer unique opportunities for spectrum sharing. But it was found that the extremely sensitive receivers provide challenges for designing a communications system meant for widespread use. The probability of causing harmful interference to airborne weather radar is too great for most types of wireless local area networks, but a direct sequence spread spectrum scheme could share spectrum with airborne weather radar. Bit errors in wireless local area network links caused by airborne weather radar interference do not significantly decrease the performance of the wireless local area network system. The distribution of interference outside of the airborne weather radar receiver by using direct sequence spread spectrum combined with the acceptable bit error rates indicate that while spectrum sharing between airborne weather radar and wireless local area network at 9.3 GHz – 9.5 GHz is not feasible, direct sequence spread spectrum systems can share spectrum with airborne weather radars under more limited assumptions. / Master of Science

Ces dernières années, de nombreux efforts ont été entrepris pour mieux comprendre les phénomènes précipitants parfois à l’origine de crues de cours d’eau et d’inondations ravageuses. Courant 2009, un consortium auvergnat a été mis en place pour notamment surveiller et prévoir ces événements. Les travaux menés dans cette thèse visent d’une part à améliorer les estimations quantitatives des précipitations (QPE) et d’autre part à vérifier les prévisions issues de modèles numériques sur de petites zones d’étude telles qu’une agglomération. L’observation des précipitations peut être réalisée à l’aide soit d’un pluviomètre qui fournit une mesure directe et précise de la quantité de pluie tombée au sol mais ne renseigne pas sur la variabilité spatiale des pluies soit d'un RADAR météorologique qui donne une représentation détaillée de la structure spatiale des précipitations mais dont les estimations sont sujettes à diverses erreurs d’autant plus prononcées en régions montagneuses. Le premier défit de cette thèse a été de trouver la meilleure façon de combiner ces deux informations complémentaires. Deux techniques géostatistiques ont été sélectionnées pour obtenir la meilleur QPE : le krigeage avec dérive externe (KED) et la fusion conditionnée (MERG). Les performances de ces deux méthodes ont été comparées au travers de deux domaines d’étude qui présentent des résolutions spatio-temporelles différentes. La seconde partie de cette thèse est consacrée à la mise en place d’une méthodologie fiable permettant de comparer spatialement les champs de QPE alors reconstruits et les prévisions quantitatives des précipitations (QPF). L’effort fut porté sur le modèle « Weather Research et Forcasting » (WRF). Une étude préliminaire a été réalisée pour tester les capacités du modèle et plus particulièrement des schémas de microphysique à reproduire la pluie. Cette étude assure ainsi l’obtention de prévisions réalistes pour une application sur des cas réels. L’appréciation de la qualité des QPF s’est focalisée sur la quantification spatiale des erreurs de prévision en termes de structure, d’intensité et de localisation des systèmes précipitants (SAL : Wernli et al. 2008, 2009). / In the last decades, many efforts were made to better understand the origins of rain that sometimes lead to rivers runoff or devastating floods. In 2009, a consortium took place in Auvergne in order to observe and predict these events. These works were focused on the improvement of quantitative precipitation estimations (QPE) and the verification of numerical weather models over small areas such as urban environment. Rainfall measurement could be operated either by rain gauges which provides direct and precise rainfall estimations but unfortunately cannot capture the spatial variability or by using weather RADAR which provides a detailed spatial representation of precipitation but estimates are derived indirectly and are subject to a combination of errors which are most pronounced over complex terrain. The main issue of these works was to find the best way to combine both observational systems which are complementary as well. In order to obtain the more truthful fields of QPE, two geostatistical techniques were selected: the kriging with external drift (KED) and the conditional merging (MERG). The performances of these two methods have been experienced on two catchments with different spatial and temporal resolutions. The second part of these works is focused on a reliable method for QPE comparison and quantitative precipitation forecast (QPF). The main effort was focused on the “Weather Research and Forecasting” (WRF) model. A preliminary study was made to check the performances of the microphysics schemes of the model to ensure realistic forecasts for an application on real cases. The spatial verification of the model set up contains three distinct components that consider aspects of the structure, amplitude and location of the precipitation field (SAL : Wernli et al. 2008, 2009).

Lhumectation des surfaces végétales, due principalement aux précipitations sous forme de pluie ou de rosée, joue un rôle déterminant lors de la phase de contamination des plantes par de nombreux agents phytopathogènes. La connaissance de la pluie et de la rosée constitue un élément fondamental pour létude et la compréhension du fonctionnement des modèles de simulation des épidémies et des systèmes d'avertissements agricoles. Lobjectif de cette recherche est de contribuer à lamélioration du système davertissement des principales maladies cryptogamiques affectant le blé dhiver au sud de Belgique et au G-D de Luxembourg. Notre démarche a consisté, dans un premier temps à évaluer les potentialités du radar météorologique de Wideumont. Nous avons décrit son fonctionnement général ainsi que son principe de mesure et nous avons détaillé les différentes sources derreur qui affectent les estimations de précipitations dérivées des observations radar. Les mesures radar sont moins précises que les mesures de précipitations par des pluviomètres. Néanmoins, le radar permet dobserver en temps réel les précipitations sur un large domaine avec une très bonne résolution spatiale et temporelle. La comparaison quantitative et qualitative des précipitations mesurées au sol avec celles estimées par le radar a été faite sur une période de trois ans (2003, 2004 et 2005). Les résultats de la validation des cumuls mensuels font apparaître que le radar a tendance à sous-estimer les précipitations. Lerreur calculée pour lensemble des stations varie entre -50% et +12%. La validation qualitative du radar a été réalisée sur des occurrences de cumuls horaires. Les indices calculés à partir des tables de contingence donnent des valeurs de POD (Probability Of Detection) entre 0.44 et 0.80 durant la période étudiée. Limpact des estimations radar sur les périodes dinfection de Septoria tritici simulées par PROCULTURE a été évalué durant trois saisons culturales (2003, 2004 et 2005) par comparaison entre les données de sortie du modèle (alimenté par des estimations radar de précipitations horaires) et les estimations visuelles du développement des symptômes de la maladie sur les trois dernières feuilles. Les outputs de PROCULTURE via les données radar ont montré un grand accord entre la simulation et lobservation. Le radar météorologique devrait dès lors être bénéfique pour des régions où le réseau des pluviomètres est inexistant (ou moins dense) et où lincidence de la septoriose est importante. Dans un deuxième temps, sur base dune recherche bibliographique, un modèle dhumectation a été choisi. Le modèle sélectionné, appelé SWEB, se base sur le bilan énergétique et le bilan hydrique. Il simule la durée dhumectation due à la pluie et à la rosée sur lensemble du couvert végétal à partir des données issues des stations agrométéorologiques. Le modèle a été ensuite testé et validé sur différentes variétés de blé dhiver. Les données de sortie du modèle ont été comparées statistiquement aux mesures des capteurs (préalablement calibrés) et aux données dobservation obtenues sur des parcelles expérimentales et au champ durant les saisons culturales 2006 et 2007. Sur base des résultats obtenus, le modèle SWEB semble sous-estimer la durée dhumectation et plus particulièrement pour les événements de la fin dhumectation (dryoff). Lerreur moyenne en général est inférieure à 90 minutes. Dans un troisième temps, afin dobtenir une relation entre les périodes dhumectation et le développement de la septoriose sur les trois dernières feuilles, les périodes dhumectation simulées par SWEB ont été comparées dune part aux périodes dinfection de Septoria tritici simulées par PROCULTURE et dautre part aux estimations visuelles. Le modèle de la durée dhumectation simule avec succès des périodes dhumectations, dues à la fois à la rosée et à la pluie, qui ont déclenché linfection de la septoriose observée sur des parcelles expérimentales. Une durée minimale dhumectation favorable à linfection des feuilles de blé par Septoria tritici a été déterminée. Il est donc désormais nécessaire délaborer un système opérationnel intégrant le radar météorologique, le modèle de la durée dhumectation et le modèle épidémiologique. Notre travail a permis dacquérir via lanalyse des données agrométéorologiques et des données phytopathologiques, les connaissances nécessaires à lélaboration dun tel système et de participer ainsi à lamélioration des modèles davertissements existants. En effet, nous avons analysé les avantages et les limites du système radar comme données dentrée aux modèles et son aptitude dans la spatialisation des données. Nous avons également testé le modèle dhumectation pour la détermination des périodes dinfection nécessaires au développement de la septoriose. Dans une perspective dune meilleure opérationnalisation du système, lapproche envisagée pourrait facilement être intégrée dans le système existant pour la simulation dautres maladies comme les rouilles, loïdium et la fusariose à léchelle régionale. En définitive, ce travail aura prouvé une fois de plus lintérêt du "mariage" entre lagrométéorologie et la phytopathologie. [en] Summary - Weather-Radar Rainfall Measurement and Simulated Surface Wetness Duration for Septoria Leaf Blotch Risk Assessment. The persistence of free moisture on leaves, mainly as a result of precipitation in the form of rainfall or dew, plays a major role during the process of plant infection by most fungal pathogens. Acquiring rainfall and leaf moisture information is needed for accurate and reliable disease prediction and management. The objective of this research is to contribute to improve forecasting Septoria leaf blotch and other fungal pathogens on winter wheat in Belgium and Luxembourg./In the first part of this work, the potential of weather-radar rainfall estimates for plant disease forecasting is discussed. At first step, we focused on assessing the accuracy and limitations of radar-derived precipitation estimates, compared with rain-gauge data. In a second step, the Septoria leaf blotch prediction model PROCULTURE was used to assess the impact on the simulated infection rate of using, as input data, rainfall estimated by radar instead of rain gauge measurements. When comparing infection events simulated by PROCULTURE using radar-derived estimates and reference rain gauge measurements, the probability of detection (POD) of infection events was high (0.83 on average), and the false alarm ratio (FAR) of infection events was not negligible (0.24 on average). FAR decreased to 0 and POD increased (0.85 on average) for most stations, when the model outputs for both datasets were compared against visual observations of Septoria leaf blotch symptoms. Analysis of 148 infection events observed over three years at four locations showed no significant difference in the number of simulated infection events using either radar assessments or gauge measurements. This suggests that, for a given location, radar estimates are just as reliable for predicting infection events as rain gauges. As radar is able to estimate rainfall occurrence over a continuous space, unlike weather station networks that do observations at only a limited number of points, it has the great advantage of being able to predict the risk of infection at each point within an area of interest with an accuracy equivalent to rain gauge observations. This gives radar an important advantage that could significantly improve existing warning systems. In the second part, a physical model based on the energy balance, known as the Surface Wetness Energy Balance (SWEB), was applied for the simulation of Surface Wetness Duration (SWD) on winter wheat canopy. The model, developed in the United States on grapes canopies, was adapted for the winter wheat cultivars and was applied for use with agrometeorological data easily available from standard weather stations and weather-radar rainfall estimates. The SWEB model simulates surface wetness duration for both dew and rain events. The model was validated with data measured by sensors and with visual observations of SWD conducted in experimental plots during two cropping seasons in 2006 and 2007. The wetness was observed visually by assessing the presence or absence of surface water on leaves. Based on the results, the SWEB model appeared to underestimate surface wetness duration and especially for the dry-off events when compared statistically to visual observations. The error, on average, is generally less than 90 minutes. In order to establish a relationship between the surface wetness periods and Septoria leaf blotch development risk on the top three leaves, the SWEB model SWD outputs were compared with the number of hours of high probability of infection simulated by PROCULTURE as well as with visual plant diseases observations. A minimal surface wetness duration of favourable infection conditions for Septoria tritici was established. It is now required to develop an operational system that would integrate weather radar, surface wetness duration and foliar epidemic model. In this work, we have analyzed the advantages and limitations of the radar system as input to models and its ability for spatial interpolation of rainfall. We also tested the model for the determination of surface wetness periods required for Septoria Leaf Blotch Risk development. The proposed approach could be integrated in the existing system. Finally this approach shows once more the "happy marriage" between agrometeorology and plant disease management.

In this study a calibration concept for a multi-polarimetric weather radar is developed. Several common calibration techniques are analysed, but many are insufficient due to the non-reciprocal behaviour of the employed radar. Hence, an electronic calibration device was developed, which was designed for fast polarization determination of any polarization (including elliptical ones). The non-reciprocal behaviour was overcome by splitting receive and transmit calibration, which virtually uses the radar as a communication system. Beside the calibration a new and exible signal processing system was implemented on that radar which allows interleaved measurements using several polarimetric modes. This capability was used to analyse the STAR (hybrid basis with linear 45° transmit and horizontal/vertical receive) mode and the alternating H/V mode with respect to depolarization. Although it is known that depolarization causes errors in STAR mode, it is used in most commercial weather radars. / In dieser Arbeit wird ein Kalibrierkonzept für ein Multipolarisation-Radar entwickelt. Dazu wurden verschiedene gebräuchliche Techniken untersucht. Dabei stellte sich heraus, dass dieses Verfahren für das untersuchte nichtreziproke Radar unzureichend sind. Deshalb wurde ein elektronisches Kalibriergerät entwickelt, welches speziell der schnellen Messung von beliebigen Polarisationen - einschließlich Elliptischer - dient. Das nichtreziproke Verhalten wurde durch die Aufteilung in eine Sende- und eine Empfangskalibrierung umgangen, wodurch das Radar praktisch als Kommunikationssystem verwendet wird. Des Weiteren wurde eine neue, fexible Signalverarbeitung an dem Radar entwickelt, welches gemischte Messungen mit mehreren Polarisationsmoden erlaubt. Diese neuartige Möglichkeit wurde benutzt um den STAR-Modus, welches eine hybride Polarisationsbasis (linear 45° senden, horizontal/vertikal empfangen) benutzt, mit dem alternierende H/V-Modus zu vergleichen. Dabei wurde speziell das Verhalten des STAR-Modus im Hinblick auf Depolarisation untersucht, da dies bekanntermaßen zu Fehlern in den Messgrößenführen kann. Dies ist von besonderem Interesse, da der STAR-Modus in den meisten kommerziellen Wetterradarsystemen eingesetzt wird.

Il est connu qu’avoir un système d’observation de la pluie de haute résolution spatio – temporelle est crucial pour obtenir de bons résultats dans la modélisation pluie – écoulement. Le radar est un outil qui donne des estimations quantitatives de precipitation avec une très bonne résolution. Lorsqu’il est fusionné avec un réseau des pluviomètres les avantages des deux systèmes sont obtenus. Cependant, les estimations fournies par le radar ont des incertitudes différentes à celles qui sont obtenus avec les pluviomètres. Dans le processus de calcul pluie – écoulement l'incertitude des précipitations interagit avec l'incertitude du modèle hydrologique. L’objectif de ce travail est d’étudier les méthodes utilisées pour quantifier l'incertitude dans l'estimation des précipitations par fusion radar – pluviomètres et de l'incertitude dans la modélisation hydrologique, afin de développer une méthodologie d'analyse de leurs contributions individuelles au traitement pluie - écoulement.Le travail est divisé en deux parties, la première cherche à évaluer: Comment peut-on quantifier l'incertitude de l'estimation des précipitations par radar? Pour répondre à la question, l'approche géostatistique par Krigeage avec Dérive Externe (KED) et Génération Stochastique de la précipitation a été utilisée, qui permet de modéliser la structure spatio – temporaire de l’erreur. La méthode a été appliquée dans la région des Cévennes - Vivarais (France), où il y a un système très dense d'observation. La deuxième partie explique: Comment pourrais être quantifiée l'incertitude de la simulation hydrologique qui provient de l'estimation de précipitation par radar et du processus de modélisation hydrologique? Dans ce point, l'outil de calcul hydrologique à Mesoéchelle (HCHM) a été développé, c’est un logiciel hydrologique distribuée et temps continu, basé sur le Numéro de Courbe et l’Hydrographe Unitaire. Il a été appliqué dans 20 résolutions spatio - temporelles allant de 10 à 300 km2 et 1 à 6 heures dans les bassins de l’Ardèche (~ 1971 km2) et le Gardon (1810 km2). Apres une analyse de sensibilité, le modèle a été simplifié avec 4 paramètres et l’incertitude de la chaîne de processus a été analysée: 1) Estimation de precipitation; 2) Modélisation hydrologique; et 3) Traitement pluie - écoulement, par l’utilisation du coefficient de variation de l'écoulement simulé.Il a été montré que KED est une méthode qui fournit l’écart type de l’estimation des précipitations, lequel peut être transformé dans une estimation stochastique de l’erreur locale. Dans la chaîne des processus: 1) L'incertitude dans l'estimation de précipitation augmente avec la réduction de l’échelle spatio – temporelle, et son effet est atténué par la modélisation hydrologique, vraisemblablement par les propriétés de stockage et de transport du bassin ; 2) L'incertitude de la modélisation hydrologique dépend de la simplification des processus hydrologiques et pas de la surface du bassin ; 3) L'incertitude dans le traitement pluie - écoulement est le résultat de la combinaison amplifiée des incertitudes de la précipitation et la modélisation hydrologique. / It is known that having a precipitation observation system at high space - time resolution is crucial to obtain good results in rainfall - runoff modeling. Radar is a tool that offers quantitative precipitation estimates with very good resolution. When it is merged with a rain gauge network the advantages of both systems are achieved. However, radars estimates have different uncertainties than those obtained with the rain gauge. In the modeling process, uncertainty of precipitation interacts with uncertainty of the hydrological model. The objective of this work is: To study methods used to quantify the uncertainty in radar – raingauge merge precipitation estimation and uncertainty in hydrological modeling, in order to develop a methodology for the analysis of their individual contributions in the uncertainty of rainfall - runoff estimation.The work is divided in two parts, the first one evaluates: How the uncertainty of radar precipitation estimation can be quantified? To address the question, the geostatistical approach by Kriging with External Drift (KED) and Stochastic Generation of Precipitation was used, which allows to model the spatio - temporal structure of errors. The method was applied in the Cévennes - Vivarais region (France), where there is a very rich observation system. The second part explains: How can it be quantified the uncertainty of the hydrological simulation coming from the radar precipitation estimates and hydrological modeling process? In this point, the hydrological mesoscale computation tool was developed; it is distributed hydrological software in time continuous, within the basis of the Curve Number and the Unit Hydrograph. It was applied in 20 spatio-temporal resolutions ranging from 10 to 300 km2 and 1 to 6 hours in the Ardèche (~ 1971 km2) and the Gardon (1810 km2) basins. After a sensitivity analysis, the model was simplified with 4 parameters and the uncertainty of the chain of process was analyzed: 1) Precipitation estimation; 2) Hydrological modeling; and 3) Rainfall - runoff estimation, by using the coefficient of variation of the simulated flow.It has been shown that KED is a method that provides the standard deviation of the precipitation estimation, which can be transformed into a stochastic estimation of the local error. In the chain of processes: 1) Uncertainty in precipitation estimation increases with decreasing spatio-temporal scale, and its effect is attenuated by hydrological modeling, probably due by storage and transport properties of the basin; 2) The uncertainty of hydrological modeling depends on the simplification of hydrological processes and not on the surface of the basin; 3) Uncertainty in rainfall - runoff treatment is the result of the amplified combination of precipitation and hydrologic modeling uncertainties.

Submitted by Vinicius Machado Martinez null (vinicius@ipmet.unesp.br) on 2016-03-11T20:20:53Z No. of bitstreams: 1 defesa.pdf: 4478778 bytes, checksum: 15d0e211ad6c8ad44eabe8079cf63fa2 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-03-15T17:11:38Z (GMT) No. of bitstreams: 1 martinez_vm_me_soro.pdf: 4478778 bytes, checksum: 15d0e211ad6c8ad44eabe8079cf63fa2 (MD5) / Made available in DSpace on 2016-03-15T17:11:38Z (GMT). No. of bitstreams: 1 martinez_vm_me_soro.pdf: 4478778 bytes, checksum: 15d0e211ad6c8ad44eabe8079cf63fa2 (MD5) Previous issue date: 2016-01-25 / O campo de refletividade de ecos observados por radares meteorológicos está sujeito a interferências de fenômenos físicos da atmosfera que podem resultar em interpretações não realísticas do fenômeno observado. Buscando ajustar o campo de refletividade de ecos detectados simultaneamente por dois radares meteorológicos ao longo da distância, este estudo desenvolveu um sistema baseado em regras fuzzy (SBRF), do tipo Takagi-Sugeno de primeira ordem, que combina as variáveis distância (km) e refletividade (dBZ) para expressar a refletividade ajustada de alvos mais distantes de um radar em relação a outro radar mais próximo, de modo que os efeitos das interferências nas medidas dos radares possam ser minimizados. Os dados utilizados são oriundos de dois radares meteorológicos do IPMet/UNESP, localizados nos municípios de Bauru (22,3583° S; 49,0278° W) e Presidente Prudente (22.175°1 S; 51.3743° W), no Brasil, no período de um ano de dados (2010) do produto CAPPI, faixa de 3.5km de altitude. A saída do sistema é nomeada refletividade fuzzy (RF) e é obtida através de um conjunto de nove curvas de regressão linear, cujos coeficientes angulares e lineares foram estimados pelo método dos mínimos quadrados. Dois parâmetros foram utilizados para análise das curvas obtidas: o coeficiente de correlação de Pearson e o coeficiente de determinação. O sistema foi aplicado a 20.514 dados referentes a 18 pixels distribuídos sobre uma faixa de comum cobertura dos radares. O modelo foi avaliado através das estatísticas de erro médio (BIAS), erro quadrático médio (MSE) e pelo teste de Kolmogorov-Smirnov. Os resultados obtidos demonstram a capacidade do sistema em aproximar o campo de refletividade de dois radares que operam sobre uma área de comum cobertura, devendo constituir-se como uma ferramenta alternativa de interpretação no monitoramento de chuvas, nos processos de modelagem ambiental e em sugestões futuras de estimativa de chuva por radar. / The reflectivity field of echoes observed by weather radars is subjected to the interference of physical phenomena of the atmosphere that can result in unrealistic interpretations on its characteristics. Aiming to adjust the reflectivity field of echoes simultaneously detected by two weather radars over a distance, this study developed a Takagi-Sugeno fuzzy rule-based system, whose input variables are the distance(km) and the reflectivity(dBZ) of the echoes, in order to obtain the adjusted reflectivity of echoes more distant from a radar in relation to another closer radar that is considered to be less susceptible to interference and, therefore, more realistic. The data used are from two weather radars of IPMet/UNESP, located in the municipalities of Bauru (22.3583° S; 49.0278° W) and Presidente Prudente (22.1751° S; 51.3743° W), Brazil, which collected data of the CAPPI product in the period of one year (2010), with a sampling altitude range of 3.5 km. The system output is named “Fuzzy Reflectivity” (FR), obtained through the fuzzy approach of a set of nine linear regression curves, whose angular and linear coefficients were estimated by the method of least squares. Two parameters were used for the analysis of the curves obtained: the Pearson correlation coefficient and the coefficient of determination. The system was applied to 20,514 data related to 18 pixels spread over a range of common coverage of the radars. We evaluated the system performance by means of statistical parameters: average error (bias), mean square error (MSE) and Kolmogorov-Smirnov test. The results obtained demonstrate the system ability to refine the modeling of the issue in question in relation to the traditional statistical approaches, properly adjusting the reflectivity field of the echoes observed by two radars that operate over an area of common coverage and serving as an alternative interpretation tool in the monitoring of rains, in processes of environmental modeling and in future suggestions of rain estimate by radar.