Apport des observations IASI pour la description des variables nuageuses du modèle AROME dans le cadre de la campagne HyMeX

Les données satellitaires représentent aujourd'hui la vaste majorité des observations assimilées dans les modèles de prévision numérique du temps. Leur exploitation reste cependant sous-optimale, seulement 10% du volume total est assimilé en opérationnel. Environ 80% des données infrarouges étant affectées par les nuages, il est primordial de développer l'assimilation des observations satellitaires dans les zones nuageuses. L'exploitation du sondeur hyperspectral infrarouge IASI a déjà permis une amélioration des prévisions météorologiques grâce à sa précision et son contenu en information jamais inégalés. Son utilisation dans les zones nuageuses reste cependant très complexe à cause de la forte non-linéarité des processus nuageux dans l'infrarouge. Cette thèse propose donc une méthode permettant d'exploiter au mieux les observations nuageuses du sondeur IASI. Un modèle de transfert radiatif avancé utilisant les propriétés microphysiques du nuage a été évalué. Cette méthode présente l'avantage majeur d'utiliser les profils de condensats nuageux produits par les modèles de prévision. Grâce à ce nouveau schéma, les profils de contenus en eau nuageuse ont pu être inversés avec succès à partir des observations IASI et d'un schéma d'assimilation variationnelle uni-dimensionnel (1D-Var). L'impact de ces observations en termes d'analyse et d'évolution des variables nuageuses dans le modèle de prévision a aussi été évalué. Cette étude est une première évaluation du choix des variables de contrôle utilisées lors des inversions. Un modèle simplifié uni-colonne du modèle de prévision AROME a permis de faire évoluer les profils analysés par le 1D-Var sur une période de trois heures. Des résultats prometteurs ont montré la bonne conservation de l'incrément d'analyse pendant plus d'une heure et demie de prévision. La formation des systèmes fortement précipitants étant fortement liée aux contenus en eau nuageuse, ces résultats encourageants laissent entrevoir des retombées majeures pour la prévision des évènements de pluie intense et les applications de prévision numérique à très courte échéance. ABSTRACT : Nowadays, most data assimilated in numerical weather prediction come from satellite observations. However, the exploitation of satellite data is still sub-optimal with only 10 to 15% of these data assimilated operationally. Keeping in mind that about 80% of infrared data are affected by clouds, it is a priority to develop the assimilation of cloud-affected satellite data. The hyperspectral infrared sounder IASI has already contributed to the improvement of weather forecasts thanks to its far better spectral resolution and information content compared to previous instruments. The use of cloud-affected IASI radiances is still very complicated due to the high non-linearity of clouds in the infrared. This PhD work suggests an innovative way to take advantage of cloud-affected radiances observed by IASI. An advanced radiative transfer model using cloud microphysical properties has been evaluated. This method has the advantage of using cloud water content profiles directly produced by numerical weather prediction models. Thanks to this new scheme, profiles of cloud water contents have been successfully retrieved from IASI cloud-affected radiances with a one dimensional variational assimilation scheme (1D-Var). The impact of these data in terms of analysis and evolution of cloud variables has been evaluated in a numerical weather prediction model. This study is the first step in evaluating the choice that has been made for the control variables used during the retrievals. A simplified one-dimensional version of the AROME model was used to run three-hour forecasts from the 1D-Var analysed profiles. Promising results have shown a good maintenance of the analysis increment during more than one hour and a half of forecast. In regard to these encouraging results, a positive impact on nearcasting applications and forecasts of heavy rainfall events, which are highly coupled to cloud variables, can be expected in the future

Combining ground-based microwave radiometer and the AROME convective scale model through 1DVAR retrievals in complex terrain: an Alpine valley case study

Abstract. A RPG-HATPRO ground-based microwave radiometer (MWR) was operated in a deep Alpine valley during the Passy-2015 field campaign. This experiment aims to investigate how stable boundary layers during wintertime conditions drive the accumulation of pollutants. In order to understand the atmospheric processes in the valley, MWRs continuously provide vertical profiles of temperature and humidity at a high time frequency, providing valuable information to follow the evolution of the boundary layer. A one-dimensional variational (1DVAR) retrieval technique has been implemented during the field campaign to optimally combine an MWR and 1 h forecasts from the French convective scale model AROME. Retrievals were compared to radiosonde data launched at least every 3 h during two intensive observation periods (IOPs). An analysis of the AROME forecast errors during the IOPs has shown a large underestimation of the surface cooling during the strongest stable episode. MWR brightness temperatures were monitored against simulations from the radiative transfer model ARTS2 (Atmospheric Radiative Transfer Simulator) and radiosonde launched during the field campaign. Large errors were observed for most transparent channels (i.e., 51–52 GHz) affected by absorption model and calibration uncertainties while a good agreement was found for opaque channels (i.e., 54–58 GHz). Based on this monitoring, a bias correction of raw brightness temperature measurements was applied before the 1DVAR retrievals. 1DVAR retrievals were found to significantly improve the AROME forecasts up to 3 km but mainly below 1 km and to outperform usual statistical regressions above 1 km. With the present implementation, a root-mean-square error (RMSE) of 1 K through all the atmospheric profile was obtained with values within 0.5 K below 500 m in clear-sky conditions. The use of lower elevation angles (up to 5°) in the MWR scanning and the bias correction were found to improve the retrievals below 1000 m. MWR retrievals were found to catch deep near-surface temperature inversions very well. Larger errors were observed in cloudy conditions due to the difficulty of ground-based MWRs to resolve high level inversions that are still challenging. Finally, 1DVAR retrievals were optimized for the analysis of the IOPs by using radiosondes as backgrounds in the 1DVAR algorithm instead of the AROME forecasts. A significant improvement of the retrievals in cloudy conditions and below 1000 m in clear-sky conditions was observed. From this study, we can conclude that MWRs are expected to bring valuable information into numerical weather prediction models up to 3 km in altitude both in clear-sky and cloudy-sky conditions with the maximum improvement found around 500 m. With an accuracy between 0.5 and 1 K in RMSE, our study has also proven that MWRs are capable of resolving deep near-surface temperature inversions observed in complex terrain during highly stable boundary layer conditions

Towards the profiling of the atmospheric boundary layer at European scale—introducing the COST Action PROBE

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Macrophage Death as a Pharmacological Target in Atherosclerosis

Atherosclerosis is a chronic inflammatory disorder characterized by the gradual build-up of plaques within the vessel wall of middle-sized and large arteries. Over the past decades, treatment of atherosclerosis mainly focused on lowering lipid levels, which can be accomplished by the use of statins. However, some patients do not respond sufficiently to statin therapy and therefore still have a residual cardiovascular risk. This issue highlights the need for novel therapeutic strategies. As macrophages are implicated in all stages of atherosclerotic lesion development, they represent an important alternative drug target. A variety of anti-inflammatory strategies have recently emerged to treat or prevent atherosclerosis. Here, we review the canonical mechanisms of macrophage death and their impact on atherogenesis and plaque stability. Macrophage death is a prominent feature of advanced plaques and is a major contributor to necrotic core formation and plaque destabilization. Mechanisms of macrophage death in atherosclerosis include apoptosis, passive or accidental necrosis as well as secondary necrosis, a type of death that typically occurs when apoptotic cells are insufficiently cleared by neighboring cells via a phagocytic process termed efferocytosis. In addition, less-well characterized types of regulated necrosis in macrophages such as necroptosis, pyroptosis, ferroptosis, and parthanatos may occur in advanced plaques and are also discussed. Autophagy in plaque macrophages is an important survival pathway that protects against cell death, yet massive stimulation of autophagy promotes another type of death, usually referred to as autosis. Multiple lines of evidence indicate that a better insight into the different mechanisms of macrophage death, and how they mutually interact, will provide novel pharmacological strategies to resolve atherosclerosis and stabilize vulnerable, rupture-prone plaques

Design of an Accurate and Stiff Wooden Industrial Robot: First Steps towards Robot Eco-sustainable Mechanical Design

International audienceThis paper investigates the feasibility of replacing metal robot links by wooden bodies for eco-sustainable design's purpose. Wood is a material with low environmental impact, and a good mass-to-stiffness ratio. However, it has significant dimensional and mechanical variabilities. This is an issue for industrial robots that must be accurate and stiff. To guarantee stiffness and accuracy performance of a wooden robot, we propose an integrated design process combining (i) proper wood selection, (ii) adequate sensor-based control strategies to ensure robot accuracy and (iii) a robust design approach dealing with wood uncertainties. Based on the use of this integrated design process, a prototype of a wooden five-bar mechanism is designed and manufactured. Experimental results show that it is realistic to design a wooden robot with performance compatible with Industry requirements in terms of stiffness (deformations lower than 400 microns for 20 N loads) and accuracy (repeatabil-ity lower than 60 microns), guaranteed in a workspace of 800 mm × 200 mm. These works provide a first step towards the eco-sustainable mechanical design of robots

Association of FcγRIIa R131H polymorphism with idiopathic pulmonary fibrosis severity and progression

<p>Abstract</p> <p>Background</p> <p>A significant genetic component has been described for idiopathic pulmonary fibrosis (IPF). The R131H (rs1801274) polymorphism of the IgG receptor FcγRIIa determines receptor affinity for IgG subclasses and is associated with several chronic inflammatory diseases. We investigated whether this polymorphism is associated with IPF susceptibility or progression.</p> <p>Methods</p> <p>In a case-control study, we compared the distribution of FcγRIIa R131H genotypes in 142 patients with IPF and in 218 controls using allele-specific PCR amplification.</p> <p>Results</p> <p>No differences in the frequency of FcγRIIa genotypes were evident between IPF patients and control subjects. However, significantly impaired pulmonary function at diagnosis was observed in HH compared to RR homozygotes, with evidence of more severe restriction (reduced forced vital capacity (FVC)) and lower diffusing capacity for carbon monoxide (D<smcaps>L</smcaps>_CO). Similarly, increased frequency of the H131 allele was observed in patients with severe disease (D<smcaps>L</smcaps>_CO< 40% predicted) (0.53 vs. 0.38; p = 0.03). Furthermore, the H131 allele was associated with progressive pulmonary fibrosis as determined by > 10% drop in FVC and/or > 15% fall in D<smcaps>L</smcaps>_COat 12 months after baseline (0.48 vs. 0.33; p = 0.023).</p> <p>Conclusions</p> <p>These findings support an association between the FcγRIIa R131H polymorphism and IPF severity and progression, supporting the involvement of immunological mechanisms in IPF pathogenesis.</p

Contribution of IASI radiances for the description of cloud variables in the AROME model in the context of the HyMeX campaign

Les données satellitaires représentent aujourd'hui la vaste majorité des observations assimilées dans les modèles de prévision numérique du temps. Leur exploitation reste cependant sous-optimale, seulement 10% du volume total est assimilé en opérationnel. Environ 80% des données infrarouges étant affectées par les nuages, il est primordial de développer l'assimilation des observations satellitaires dans les zones nuageuses. L'exploitation du sondeur hyperspectral infrarouge IASI a déjà permis une amélioration des prévisions météorologiques grâce à sa précision et son contenu en information jamais inégalés. Son utilisation dans les zones nuageuses reste cependant très complexe à cause de la forte non-linéarité des processus nuageux dans l'infrarouge. Cette thèse propose donc une méthode permettant d'exploiter au mieux les observations nuageuses du sondeur IASI. Un modèle de transfert radiatif avancé utilisant les propriétés microphysiques du nuage a été évalué. Cette méthode présente l'avantage majeur d'utiliser les profils de condensats nuageux produits par les modèles de prévision. Grâce à ce nouveau schéma, les profils de contenus en eau nuageuse ont pu être inversés avec succès à partir des observations IASI et d'un schéma d'assimilation variationnelle uni-dimensionnel (1D-Var). L'impact de ces observations en termes d'analyse et d'évolution des variables nuageuses dans le modèle de prévision a aussi été évalué. Cette étude est une première évaluation du choix des variables de contrôle utilisées lors des inversions. Un modèle simplifié uni-colonne du modèle de prévision AROME a permis de faire évoluer les profils analysés par le 1D-Var sur une période de trois heures. Des résultats prometteurs ont montré la bonne conservation de l'incrément d'analyse pendant plus d'une heure et demie de prévision. La formation des systèmes fortement précipitants étant fortement liée aux contenus en eau nuageuse, ces résultats encourageants laissent entrevoir des retombées majeures pour la prévision des évènements de pluie intense et les applications de prévision numérique à très courte échéance.Nowadays, most data assimilated in numerical weather prediction come from satellite observations. However, the exploitation of satellite data is still sub-optimal with only 10 to 15% of these data assimilated operationally. Keeping in mind that about 80% of infrared data are affected by clouds, it is a priority to develop the assimilation of cloud-affected satellite data. The hyperspectral infrared sounder IASI has already contributed to the improvement of weather forecasts thanks to its far better spectral resolution and information content compared to previous instruments. The use of cloud-affected IASI radiances is still very complicated due to the high non-linearity of clouds in the infrared. This PhD work suggests an innovative way to take advantage of cloud-affected radiances observed by IASI. An advanced radiative transfer model using cloud microphysical properties has been evaluated. This method has the advantage of using cloud water content profiles directly produced by numerical weather prediction models. Thanks to this new scheme, profiles of cloud water contents have been successfully retrieved from IASI cloud-affected radiances with a one dimensional variational assimilation scheme (1D-Var). The impact of these data in terms of analysis and evolution of cloud variables has been evaluated in a numerical weather prediction model. This study is the first step in evaluating the choice that has been made for the control variables used during the retrievals. A simplified one-dimensional version of the AROME model was used to run three-hour forecasts from the 1D-Var analysed profiles. Promising results have shown a good maintenance of the analysis increment during more than one hour and a half of forecast. In regard to these encouraging results, a positive impact on nearcasting applications and forecasts of heavy rainfall events, which are highly coupled to cloud variables, can be expected in the future

: École d'été 2016 - Analyse géométrique, géométrie des espaces métriques et topologie

W. Thurston's geometrization program has lead to manyoutstanding results in 3-manifold theory. Thanks to worksof G. Perelman, J. Kahn and V. Markovic, D. Wise, and I. Agol among others, compact 3-manifolds can now beconsidered to be reasonably well-understood.By contrast, noncompact 3-manifolds remainmuch more mysterious. There is a series of examples,beginning with work of L. Antoine and J. H. C. Whitehead,which show that open 3-manifolds can exhibit wildbehavior at infinity. No comprehensive structure theoryanalogous to geometrization à la Thurston is currently availablefor these objects In these lectures, we will focus on two aspects of the subject: (1) constructing interesting examples, and (2) finding sufficientconditions that rule out exotic examples, in particular inconnection with Riemannian geometry

: École d'été 2016 - Analyse géométrique, géométrie des espaces métriques et topologie

The Margulis lemma describes the structure of the group generated by small loops in the fundamental group of a Riemannian manifold, thus giving a picture of its local topology. Originally stated for homogeneous spaces by C. Jordan, L. Bieberbach, H. J. Zassenhaus, D. Kazhdan-G. Margulis, it has been extended to the Riemannian setting by G. Margulis for manifolds of non positive curvature. The goal of these lectures is to present the recent work of V. Kapovitch and B. Wilking who gave a sharp version of the Margulis lemma under the assumption that the Ricci curvature is bounded below. Their method uses the structure of « Ricci limit spaces » explained by T. Richard during his lectures

: École d'été 2016 - Analyse géométrique, géométrie des espaces métriques et topologie

The goal of these lectures is to introduce some fundamental tools in the study of manifolds with a lower bound on Ricci curvature. We will first state and prove the laplacian comparison theorem for manifolds with a lower bound on the Ricci curvature, and derive some important consequences : Bishop-Gromov inequality, Myers theorem, Cheeger-Gromoll splitting theorem. Then we will define the Gromov-Hausdorff distance between metric spaces which will allow us to consider limits of sequences of Riemannian manifolds, along the way we will prove Gromov’s precompactness theorem for sequences of manifolds with a Ricci lower bound. We will also see on examples what type of degeneration can occur when considering these « Ricci limit spaces », we will in particular encounter curvature blow up and volume collapsing. One of the major point in the study of these limit spaces is to understand which results on smooth manifolds with a Ricci lower bound carry on to the limit spaces, we will give an introduction to this topic by outlining the proof by Cheeger and Colding of the splitting theorem for limit spaces