Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Modélisation hydrologique des précipitations et des crues extrêmes dans les bassins versants alpin

Les crues et les risques de débordement des barrages, notamment des digues en terre, en cas de fortes précipitations, préoccupent depuis longtemps les autorités et la population. Les études réalisées dans les dernières années ont montré que le réchauffement global du climat s'est accompagné d'une augmentation de la fréquence des fortes précipitations et des crues en Suisse et dans de nombreuses régions du globe durant le 20ème siècle. Les modèles climatiques globaux et régionaux prévoient que la fréquence des fortes précipitations devrait continuer à croître durant le 21éme siècle en Suisse et dans le monde. Cela rend les recherches actuelles sur la modélisation des pluies et des crues à une échelle fine encore plus importantes. En Suisse, pour assurer une bonne protection sur le plan humain et économique, des cartes de précipitations maximales probables (PMP) ont été réalisées. Les PMP ont été confrontées avec les précipitations extrêmes mesurées dans les différentes régions du pays. Ces PMP sont ensuite utilisées par les modèles hydrologiques pour calculer des crues maximales probables (PMF). Cette la méthode PMP-PMF nécessite toutefois un certain nombre de précautions. Si elle est appliquée d'une manière incorrecte ou sur la base de données insuffisantes, elle peut entraîner une surestimation des débits de crue, notamment pour les grands bassins et pour les régions montagneuses entraînant des surcoûts importants. Ces problèmes résultent notamment du fait que la plupart des modèles hydrologiques répartissent les précipitations extrêmes (PMP) de manière uniforme dans le temps sur l'ensemble du bassin versant. Pour remédier ce problème, cette thèse a comme objectif principal de développer un modèle hydrologique distribué appelé MPF (Modeling Precipitation Flood) capable d'estimer la PMF de manière réaliste à partir de la PMP distribuée de manière spatio-temporelle à l'aide des nuages. Le modèle développé MPF comprend trois parties importantes. Dans la première partie, les précipitations extrêmes calculées par un modèle météorologique à une méso-échelle avec une résolution horizontale de 2 km, sont réparties à une échelle locale (25 ou 50 m) de manière non-uniforme dans l'espace et dans le temps. La deuxième partie concerne la modélisation de l'écoulement de l'eau en surface et en subsurface en incluant l'infiltration et l'exfiltration. Et la troisième partie inclut la modélisation de la fonte des neiges, basée sur un calcul de transfert de chaleur. Le modèle MPF a été calibré sur des bassins versants alpins où les données de précipitations et du débit sont disponibles pour une période considérablement longue, qui inclut plusieurs épisodes de fortes pluies avec des débits élevés. À partir de ces épisodes, les paramètres d'entrée du modèle tel que la rugosité du sol et la largeur moyenne des cours d'eau dans le cas d'écoulement de surface ont pu être estimés. Suivant la même procédure, les paramètres utilisés dans la simulation des écoulements en subsurface sont également estimés indirectement, puisque des mesures directes de l'écoulement en subsurface et de l'exfiltration sont difficiles à obtenir. Le modèle de distribution spatio-temporelle de la pluie a aussi été validé en utilisant les images radar avec la structure de la pluie provoquée par un nuage supercellulaire. Les hyétogrammes obtenus sur plusieurs points du terrain sont très proches de ceux enregistrées avec les images radar. Les résultats de la validation du modèle sur les épisodes de fortes crues présentent une bonne synchronisation entre le débit simulé et le débit observé. Cette corrélation a été mesurée avec trois critères d'efficacité, qui ont tous donné des valeurs satisfaisantes. Cela montre que le modèle développé est valide et il peut être utilisé pour des épisodes extrêmes tels que la PMP. Des simulations ont été faites sur plusieurs bassins ayant comme données d'entrée la pluie de type PMP. Des conditions variées ont été utilisées, comme la situation du sol saturé, ou non-saturé, ou la présence d'une couche de neige sur le terrain au moment de la PMP, ce qui conduit à une estimation de PMF pour des scénarios catastrophiques. Enfin, les résultats obtenus montrent comment mieux estimer la valeur de la crue de sécurité des barrages, à partir d'une pluie extrême dix-millennale avec une période de retour de 10'000 ans.

The effect of scale in daily precipitation hazard assessment

Daily precipitation is recorded as the total amount of water collected by a rain-gauge in 24 h. Events are modelled as a Poisson process and the 24 h precipitation by a Generalised Pareto Distribution (GPD) of excesses. Hazard assessment is complete when estimates of the Poisson rate and the distribution parameters, together with a measure of their uncertainty, are obtained. The shape parameter of the GPD determines the support of the variable: Weibull domain of attraction (DA) corresponds to finite support variables as should be for natural phenomena. However, Fréchet DA has been reported for daily precipitation, which implies an infinite support and a heavy-tailed distribution. Bayesian techniques are used to estimate the parameters. The approach is illustrated with precipitation data from the Eastern coast of the Iberian Peninsula affected by severe convective precipitation. The estimated GPD is mainly in the Fréchet DA, something incompatible with the common sense assumption of that precipitation is a bounded phenomenon. The bounded character of precipitation is then taken as a priori hypothesis. Consistency of this hypothesis with the data is checked in two cases: using the raw-data (in mm) and using log-transformed data. As expected, a Bayesian model checking clearly rejects the model in the raw-data case. However, log-transformed data seem to be consistent with the model. This fact may be due to the adequacy of the log-scale to represent positive measurements for which differences are better relative than absolute

Mesoscale numerical analysis of the historical November 1982 heavy precipitation event over Andorra (Eastern Pyrenees)

From 6 to 8 November 1982 one of the most catastrophic flash-flood events was recorded in the Eastern Pyrenees affecting Andorra and also France and Spain with rainfall accumulations exceeding 400 mm in 24 h, 44 fatalities and widespread damage. This paper aims to exhaustively document this heavy precipitation event and examines mesoscale simulations performed by the French Meso-NH non-hydrostatic atmospheric model. Large-scale simulations show the slow-evolving synoptic environment favourable for the development of a deep Atlantic cyclone which induced a strong southerly flow over the Eastern Pyrenees. From the evolution of the synoptic pattern four distinct phases have been identified during the event. The mesoscale analysis presents the second and the third phase as the most intense in terms of rainfall accumulations and highlights the interaction of the moist and conditionally unstable flows with the mountains. The presence of a SW low level jet (30 m s-1) around 1500 m also had a crucial role on focusing the precipitation over the exposed south slopes of the Eastern Pyrenees. Backward trajectories based on Eulerian on-line passive tracers indicate that the orographic uplift was the main forcing mechanism which triggered and maintained the precipitating systems more than 30 h over the Pyrenees. The moisture of the feeding flow mainly came from the Atlantic Ocean (7-9 g kg-1) and the role of the Mediterranean as a local moisture source was very limited (2-3 g kg-1) due to the high initial water vapour content of the parcels and the rapid passage over the basin along the Spanish Mediterranean coast (less than 12 h).

Bayesian Markov-chain-Monte-Carlo inversion of time-lapse cross hole ground-penetrating radar data to characterize the vadose zone at the Arrenaes field site, Denmark

The ground-penetrating radar (GPR) geophysical method has the potential to provide valuable information on the hydraulic properties of the vadose zone because of its strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR traveltime data can allow for a significant reduction in uncertainty regarding subsurface van Genuchten-Mualem (VGM) parameters. Much of the previous work on the stochastic estimation of VGM parameters from crosshole GPR data has considered the case of steady-state infiltration conditions, which represent only a small fraction of practically relevant scenarios. We explored in detail the dynamic infiltration case, specifically examining to what extent time-lapse crosshole GPR traveltimes, measured during a forced infiltration experiment at the Arreneas field site in Denmark, could help to quantify VGM parameters and their uncertainties in a layered medium, as well as the corresponding soil hydraulic properties. We used a Bayesian Markov-chain-Monte-Carlo inversion approach. We first explored the advantages and limitations of this approach with regard to a realistic synthetic example before applying it to field measurements. In our analysis, we also considered different degrees of prior information. Our findings indicate that the stochastic inversion of the time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions compared with the corresponding priors, which in turn significantly improves knowledge of soil hydraulic properties. Overall, the results obtained clearly demonstrate the value of the information contained in time-lapse GPR data for characterizing vadose zone dynamics.

3D crosshole ERT for aquifer characterization and monitoring of infiltrating river water

The hydrogeological properties and responses of a productive aquifer in northeastern Switzerland are investigated. For this purpose, 3D crosshole electrical resistivity tomography (ERT) is used to define the main lithological structures within the aquifer (through static inversion) and to monitor the water infiltration from an adjacent river. During precipitation events and subsequent river flooding, the river water resistivity increases. As a consequence, the electrical characteristics of the infiltrating water can be used as a natural tracer to delineate preferential flow paths and flow velocities. The focus is primarily on the experiment installation, data collection strategy, and the structural characterization of the site and a brief overview of the ERT monitoring results. The monitoring system comprises 18 boreholes each equipped with 10 electrodes straddling the entire thickness of the gravel aquifer. A multi-channel resistivity system programmed to cycle through various four-point electrode configurations of the 180 electrodes in a rolling sequence allows for the measurement of approximately 15,500 apparent resistivity values every 7 h on a continuous basis. The 3D static ERT inversion of data acquired under stable hydrological conditions provides a base model for future time-lapse inversion studies and the means to investigate the resolving capability of our acquisition scheme. In particular, it enables definition of the main lithological structures within the aquifer. The final ERT static model delineates a relatively high-resistivity, low-porosity, intermediate-depth layer throughout the investigated aquifer volume that is consistent with results from well logging and seismic and radar tomography models. The next step will be to define and implement an appropriate time-lapse ERT inversion scheme using the river water as a natural tracer. The main challenge will be to separate the superposed time-varying effects of water table height, temperature, and salinity variations associated with the infiltrating water.

Polarimetric radar interferometry for improved mine detection and surface clutter rejection

A recently developed technique, polarimetric radar interferometry, is applied to tackle the problem of the detection of buried objects embedded in surface clutter. An experiment with a fully polarimetric radar in an anechoic chamber has been carried out using different frequency bands and baselines. The processed results show the ability of this technique to detect buried plastic mines and to measure their depth. This technique enables the detection of plastic mines even if their backscatter response is much lower than that of the surface clutter.

Buprenorphine and norbuprenorphine quantification in human plasma by simple protein precipitation and ultra-high performance liquid chromatography tandem mass spectrometry.

A highly sensitive ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method was developed for the quantification of buprenorphine and its major metabolite norbuprenorphine in human plasma. In order to speed up the process and decrease costs, sample preparation was performed by simple protein precipitation with acetonitrile. To the best of our knowledge, this is the first application of this extraction technique for the quantification of buprenorphine in plasma. Matrix effects were strongly reduced and selectivity increased by using an efficient chromatographic separation on a sub-2μm column (Acquity UPLC BEH C18 1.7μm, 2.1×50mm) in 5min with a gradient of ammonium formate 20mM pH 3.05 and acetonitrile as mobile phase at a flow rate of 0.4ml/min. Detection was made using a tandem quadrupole mass spectrometer operating in positive electrospray ionization mode, using multiple reaction monitoring. The procedure was fully validated according to the latest Food and Drug Administration guidelines and the Société Française des Sciences et Techniques Pharmaceutiques. Very good results were obtained by using a stable isotope-labeled internal standard for each analyte, to compensate for the variability due to the extraction and ionization steps. The method was very sensitive with lower limits of quantification of 0.1ng/ml for buprenorphine and 0.25ng/ml for norbuprenorphine. The upper limit of quantification was 250ng/ml for both drugs. Trueness (98.4-113.7%), repeatability (1.9-7.7%), intermediate precision (2.6-7.9%) and internal standard-normalized matrix effects (94-101%) were in accordance with international recommendations. The procedure was successfully used to quantify plasma samples from patients included in a clinical pharmacogenetic study and can be transferred for routine therapeutic drug monitoring in clinical laboratories without further development.

In-line Monitoring of Precipitation Process using Raman Spectroscopy and ATR-FTIR

Polymorfian jatkuva seuranta saostuksessa on hyödyllistä suunnittelun ja kidetuotteen ominaisuuksien sekä kiteytystä seuraavan jatkoprosessoinnin kannalta. Tässä diplomityössä on tutkittu L-glutamiinihapon kahden (- ja ß) polymorfimuodon liukoisuuden riippuvuutta pH:sta ja lämpötilasta.Tulokseksi saatiin, että kummankin polymorfin liukoisuus kasvoi sekä pH:ta ettälämpötilaa kasvatettaessa. ¿¿muodon liukoisuus oli korkeampi kuin ß-muodon liukoisuus valituilla pH-arvoilla eri lämpötiloissa. Lisäksi seurattiin puolipanostoimisen saostuksen aikana 1-litraisella laboratoriokiteyttimellä muodostuvan kiteisen polymorfiseoksen koostumusta hyödyntäen in-line Raman-spektroskopiaa. Myös liuoksen pH-muutosta seurattiin sekä liuoksen koostumusta ATR FTIR-spektroskopian (Attenuated Total Reflection Fourier Transform Infrared Spectrometer) avulla. Tutkittavina muuttujina olivat mm. sekoitusintensiteetti, sekoitintyyppi, reaktanttien (natriumglutamaatti ja rikkihappo) konsentraatiot sekä syötetyn rikkihapon syöttökohta kiteyttimessä. Työhön sisältyi 36 koetta ja osa kokeista toistettiin tulosten oikeellisuuden tarkistamiseksi. Inline-mittaustulosten verifioimiseksi kidenäytteet analysoitiin myös käyttämällä konfokaali Raman-mikroskooppia. Kidemorfologiaa tutkittiin SEM-kuvien (Scanning Eletronic Microscope) avulla. Työ osoitti, että Raman-spektroskopia on joustava ja luotettava menetelmä saostusprosessin jatkuvaan seurantaan L-glutamiinihapolla. Alhaiset lähtöainepitoisuudet tuottivat pääasiassa ¿¿muotoa, kun taas alhainen sekoitusteho edisti ß-muodon muodostumista. Syöttökohta vaikutti merkittävästi polymorfiaan. Kun rikkihapon syöttökohta oli epäideaalisesti sekoitetulla vyöhykkeellä, nousi ylikylläisyystaso korkeaksi ja päätuote oli tällöin ß-muotoa. 6-lapainen vinolapaturbiini (nousukulma 45o) ja 6-lapainen levyturbiini eivät merkittävästi poikenneet toisistaan muodostuvien polymorfien osalta.

Aplicación de imágenes radar de satélite a la cartografía de la vegetación en zonas boreales

El presente estudio se enmarca en el proyecto europeo SIBERIA. Trata de explorar el uso de imágenes radar de satélite (ERS y JERS) para la actualización de la cartografía de vegetación de zonas boreales. Se dispone de 8 imágenes de amplitud y coherencia tomadas en 1998, así como de un inventario de vegetación georreferenciado de dos pequeñas zonas. Se proponen tres tipos de clasificaciones supervisadas por el método de máxima verosimilitud. La primera con las imágenes de satélite, la segunda añadiendo algunas imágenes texturales, y la tercera utilizando sólo las imágenes de los componentes principales más significativos. Se siguen los criterios establecidos en el proyecto SIBERIA para la obtención de áreas de entrenamiento. Se propone una doble validación, por una parte vía matrices de confusión a partir de áreas de verdad-terreno obtenidas por el mismo método que las áreas de entrenamiento, y por otra parte contrastando y correlacionando las clasificaciones con los parámetros de inventario disponibles para dos pequeñas áreas de verdad-terreno. Los resultados indican una sensible mejora en la clasificación con la incorporación de imágenes texturales (la precisión aumenta de un 66% a un 75%), y señalan el parámetro biomasa como el mejor correlacionado con las clasificaciones derivadas (coeficiente de correlación r de hasta 0,49). Diferentes fuentes de error permiten augurar un margen de mejora para posteriores estudios.

Daily precipitation concentration across Europe 1971-2010

Daily Precipitation Concentration Index (CI) was used in this paper to investigate the statistical structure of daily precipitation across Europe based on 530 daily rainfall series for the period 1971-2010. Annual CI shows a North- West to South-East gradient (excluding Turkey and Greece). The same gradient is also observed in winter, spring and autumn, while in summer the gradient is North-South. Highest annual and seasonal daily concentrations of rainfall were detected in the western Mediterranean basin, mainly along Spanish and French coastlands. Latitude and distance from the sea seems to play a major role on spatial CI distribution; at subregional scale also relief plays an important role. The Mann-Kendall test did not identify uniform significant pattern in temporal trend across Europe for 1971-2010 period. The only broad areas with increasing annual and seasonal CI values are located in northern and south-western France and northern coastlands of the Iberian Peninsula. This findings suggest that daily precipitation distribution has not significantly changed during the 1971-2010 over Europe.

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.

Mesoscale numerical analysis of the historical November 1982 heavy precipitation event over Andorra (Eastern Pyrenees)

From 6 to 8 November 1982 one of the most catastrophic flash-flood events was recorded in the Eastern Pyrenees affecting Andorra and also France and Spain with rainfall accumulations exceeding 400 mm in 24 h, 44 fatalities and widespread damage. This paper aims to exhaustively document this heavy precipitation event and examines mesoscale simulations performed by the French Meso-NH non-hydrostatic atmospheric model. Large-scale simulations show the slow-evolving synoptic environment favourable for the development of a deep Atlantic cyclone which induced a strong southerly flow over the Eastern Pyrenees. From the evolution of the synoptic pattern four distinct phases have been identified during the event. The mesoscale analysis presents the second and the third phase as the most intense in terms of rainfall accumulations and highlights the interaction of the moist and conditionally unstable flows with the mountains. The presence of a SW low level jet (30 m s-1) around 1500 m also had a crucial role on focusing the precipitation over the exposed south slopes of the Eastern Pyrenees. Backward trajectories based on Eulerian on-line passive tracers indicate that the orographic uplift was the main forcing mechanism which triggered and maintained the precipitating systems more than 30 h over the Pyrenees. The moisture of the feeding flow mainly came from the Atlantic Ocean (7-9 g kg-1) and the role of the Mediterranean as a local moisture source was very limited (2-3 g kg-1) due to the high initial water vapour content of the parcels and the rapid passage over the basin along the Spanish Mediterranean coast (less than 12 h).