Le rôle pivot des variables latentes pourle raisonnement statistique conditionnel. Exemples d'applications environnementales des processus ponctuels marqués.

peer reviewedEn statistique bayésienne, le raisonnement conditionnel probabiliste fonde la solidarité étroite entre modélisation et inférence. Dans le cadre de ce raisonnement, un rôle pivot est joué par les variables latentes. Ce mode de raisonnement peut s’avérer utile aussi en statistique fréquentiste. On présente trois séries hydrométéorologiques décrites par des modèles de processus ponctuels marqués de complexité croissante. Sur ces exemples, on montre comment récolter les fruits de la souplesse de modélisation et des facilités de calcul apportées par les variables latentes. Ces variables améliorent la conceptualisation de variables de structure dans les modèles statistiques et permettent aux calculs d’inférence de bénéficier des algorithmes MCMC en relation avec les techniques «d’augmentation de données»

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer, studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory, a versatile observatory designed to address the Hot and Energetic Universe science theme, selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), it aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over an hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (including the X-IFU cryostat and the cooling chain), due to an unanticipated cost overrun of Athena. In this paper, after illustrating the breakthrough capabilities of the X-IFU, we describe the instrument as presented at its SRR, browsing through all the subsystems and associated requirements. We then show the instrument budgets, with a particular emphasis on the anticipated budgets of some of its key performance parameters. Finally we briefly discuss on the ongoing key technology demonstration activities, the calibration and the activities foreseen in the X-IFU Instrument Science Center, and touch on communication and outreach activities, the consortium organisation, and finally on the life cycle assessment of X-IFU aiming at minimising the environmental footprint, associated with the development of the instrument. Thanks to the studies conducted so far on X-IFU, it is expected that along the design-to-cost exercise requested by ESA, the X-IFU will maintain flagship capabilities in spatially resolved high resolution X-ray spectroscopy, enabling most of the original X-IFU related scientific objectives of the Athena mission to be retained. (abridged).Comment: 48 pages, 29 figures, Accepted for publication in Experimental Astronomy with minor editin

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory. Athena is a versatile observatory designed to address the Hot and Energetic Universe science theme, as selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), X-IFU aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over a hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (including the X-IFU cryostat and the cooling chain), due to an unanticipated cost overrun of Athena. In this paper, after illustrating the breakthrough capabilities of the X-IFU, we describe the instrument as presented at its SRR (i.e. in the course of its preliminary definition phase, so-called B1), browsing through all the subsystems and associated requirements. We then show the instrument budgets, with a particular emphasis on the anticipated budgets of some of its key performance parameters, such as the instrument efficiency, spectral resolution, energy scale knowledge, count rate capability, non X-ray background and target of opportunity efficiency. Finally, we briefly discuss the ongoing key technology demonstration activities, the calibration and the activities foreseen in the X-IFU Instrument Science Center, touch on communication and outreach activities, the consortium organisation and the life cycle assessment of X-IFU aiming at minimising the environmental footprint, associated with the development of the instrument. Thanks to the studies conducted so far on X-IFU, it is expected that along the design-to-cost exercise requested by ESA, the X-IFU will maintain flagship capabilities in spatially resolved high resolution X-ray spectroscopy, enabling most of the original X-IFU related scientific objectives of the Athena mission to be retained. The X-IFU will be provided by an international consortium led by France, The Netherlands and Italy, with ESA member state contributions from Belgium, Czech Republic, Finland, Germany, Poland, Spain, Switzerland, with additional contributions from the United States and Japan.The French contribution to X-IFU is funded by CNES, CNRS and CEA. This work has been also supported by ASI (Italian Space Agency) through the Contract 2019-27-HH.0, and by the ESA (European Space Agency) Core Technology Program (CTP) Contract No. 4000114932/15/NL/BW and the AREMBES - ESA CTP No.4000116655/16/NL/BW. This publication is part of grant RTI2018-096686-B-C21 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. This publication is part of grant RTI2018-096686-B-C21 and PID2020-115325GB-C31 funded by MCIN/AEI/10.13039/501100011033

Modelling the propagation pathway of street-traffic noise : practical comparison of German guidelines and real-world measurements

In Germany, several guidelines were developed to model the noise propagation pathway. The study compares the guidelines DIN 18005, RLS-90 and VDI 2714, all of which provide some kind of sound object line source suited to model street traffic noise. Differences between those guidelines are explained, and their effect on practical calculations is shown in a real-world situation, National Road N4, in Arlon, Belgium. Calculated results are compared to measurements made on critical points along the road. The paper emphasises the understanding of the inner workings of models. In order to avoid differences in calculated results due to software design methods applied, all calculations are made using one single commercially available simulation program. Additionally, this allows for a test of guideline sensitivity to changes in input parameters

Temporal evolution and extreme value analysis of precipitations in Burkina Faso

Modeling of damaging extreme events is of great interest for the risk managers who want to implement some protections. It is based on the so-called generalized extreme values model. In the environmental sciences, we need to model the extremes of two or more processes like the daily rainfall recorded in various points of a given region. Each individual process could be modeled using univariate technique, but this strategy could not take into account for dependence of extreme values. For instance, consider two sites A and B fairly close to one another. If we observe an extreme value of the daily rainfall at site A, this information impacts the probability to observe an extreme value at site B even if we never recorded such value at B. The basic modeling tool is formed by so-called max-stable processes which take into account the possible spatial dependence through so-called extremal coefficient. We illustrate with annual maximum daily rainfall values recorded in 41 stations in Burkina Faso

Comparative CCN concentration measurements between two sites in the Meuse valley and occurrence of localized dense fogs in relation with industrial activities

peer reviewe

Applications de l'approche bayésienne à la représentation des pluies mensuelles africaines par la loi des fuites.

Ce texte présente une analyse bayésienne d'un processus ponctuel marqué particulier (la loi des fuites) avec application à des problèmes de modélisation environnementale hydrométéorologique sur les données africaines de Ghezala (Tunisie) et Ataktamé (Togo)

Statistique bayésienne des processus ponctuels marqués. Le rôle des variables latentes dans la démarche de modélisation.

En statistique bayésienne le raisonnement conditionnel est à la base de la solidarité étroite entre modélisation et calcul par algorithmes MCMC. Un des aspects les plus fructueux de son utilisation est l'utilisation explicite des variables latentes ou cachées. On présente trois exemples de séries météorologiques représentées par des modèles de processus ponctuels marqués de complexité croissante. Sur ces exemples on montre la souplesse de modélisation et les facilités de calcul apportées par les variables latentes en relation avec les techniques "d'augmentation de données de Tanner"

Radial tree-growth modelling with fuzzy regression.

A so-called fuzzy linear regression is used in dendroecology to model empirically tree growth as a function of a bioclimatic index representing the water stress, i.e., the ratio of actual evapotranspiration to potential evapotranspiration. The response function predicts tree growth as (fuzzy) intervals, narrow in the domain where the bioclimatic index is most limiting and becoming progressively larger elsewhere. The method is tested with a population of Pinus pineaL. from the Provence region in France. It is shown that fuzzy linear regression gives results comparable with those obtained using a linear response function. The interval of credibility given by the fuzzy regression suggests that more precise expected growth is obtained for high water stress, which is typical of Mediterranean climate. Fuzzy linear regression can be also a method to test different hypotheses on several potential predictors when any further experimental approach is quite impossible as it is for trees in their natural environment. To sum up, fuzzy regression could be a first step before the construction of a kind of growth simulator adapted to different environments of a given species. In environmental sciences, the fuzzy response function thus appears to be an approach between the mechanistic and the statistical descriptive approaches