Circulation atmosphérique hivernale dans le bassin Grenoblois : caractérisation et impact sur la qualité de l'air

This PhD work investigates the transport and spatial distribution of particulate matter in the alpine valley of Grenoble during wintertime. It is motivated by the adverse health effects that impact the inhabitants of the valley as a result of long term exposition to pollutants.Since detailed numerical modeling of the dispersion of pollutants at fine spatial scales is unpractical over long time scales, the first part of this PhD work attempts to identify large-scale weather types that can be associated with a characteristic atmospheric dynamics in the Grenoble valley. To obtain this weather type decomposition, classical (PCA+Kmeans) and less classical (convolutional LSTM neural network) methods are compared. The introduction of the temporal component as well as constraints linking synoptic and local scales are also studied. The result is that, for a limited number of weather types, only the one corresponding to the winter anticyclonic blocking seems to produce a characteristic local response.In the second part of the thesis, the impact of the variability within the winter anticyclonic blocking weather type on this local response is studied, via the simulation of four episodes with different characteristics. To this end, High Resolution Mesoscale Simulations (down to about 100 meters horizontal resolution) are used to accurately capture the dynamics in complex terrain. The emission inventory implemented in the numerical model allows, in combination with the dynamics, to obtain an accurate spatial representation of the air pollution.From a dynamical point of view, it appears that the atmospheric circulation at the valley bottom is very homogeneous from one episode to the next and driven by thermal effects. Conversely, the height of the thermal inversion and the vertical structure of the valley winds depend on the synoptic conditions. Concerning atmospheric pollution, the main result is that the concentration fields at the valley bottom are similar from one episode to the other because the winds flowing along the valley floor are similar. This concentration field contains the same hot spots of pollution whatever the episode, implying that the population living there might be exposed to poor air quality during anticyclonic winter episodes.Ce travail de thèse porte sur le transport et la distribution spatiale de polluants de type particules fines dans la vallée alpine de Grenoble en hiver. Il est motivé par l'impact sanitaire de l'exposition à la pollution dans la vallée, qui se fait sur un temps long.Temps long et échelles spatiales de la vallée ne pouvant être pris en compte simultanément dans le cadre d'une étude détaillée du transport de polluants, la première partie du travail de thèse concerne la recherche de types de temps à l'échelle synoptique qui puissent être chacun associés à une dynamique caractéristique dans la vallée de Grenoble. Pour obtenir cette décomposition en type de temps, des méthodes classiques (ACP+Kmeans) et moins classiques (réseau de neurones LSTM convolutifs) sont comparées. L'introduction de la composante temporelle ainsi que des contraintes reliant les échelles synoptiques et locales sont aussi étudiées. Il en résulte que, si un nombre restreint de type de temps est recherché, seul celui correspondant au blocage anticyclonique hivernal semble produire une réponse locale caractéristique.Dans la seconde partie du travail de thèse, l'impact de la variabilité au sein du type de temps blocage anticyclonique hivernal sur cette réponse locale est étudié, via la simulation de quatre épisodes présentant des caractéristiques différentes. Des Simulations des Grandes échelles à haute résolution (jusqu'à 100 mètres environ de résolution horizontale) sont menées pour cela, qui permettent de capturer la dynamique atmosphérique en terrain complexe. Le cadastre d'émission implémenté dans le modèle numérique permet, en combinaison avec la dynamique, d'avoir une représentation spatiale fine de la pollution atmosphérique.D'un point de vue dynamique, il ressort que la circulation atmosphérique en fond de vallée est très homogène d'un épisode sur l'autre et pilotée par les effets thermiques. A l'inverse, la hauteur de l'inversion thermique et la structure verticale des vents de vallées dépendent des conditions synoptiques. Concernant la pollution atmosphérique, la dynamique dominante en fond de vallée conduit à de fortes hétérogénéités spatiales dont la localisation ne dépend pas de l'épisode considéré

Circulation atmosphérique hivernale dans le bassin Grenoblois : caractérisation et impact sur la qualité de l'air

This PhD work investigates the transport and spatial distribution of particulate matter in the alpine valley of Grenoble during wintertime. It is motivated by the adverse health effects that impact the inhabitants of the valley as a result of long term exposition to pollutants.Since detailed numerical modeling of the dispersion of pollutants at fine spatial scales is unpractical over long time scales, the first part of this PhD work attempts to identify large-scale weather types that can be associated with a characteristic atmospheric dynamics in the Grenoble valley. To obtain this weather type decomposition, classical (PCA+Kmeans) and less classical (convolutional LSTM neural network) methods are compared. The introduction of the temporal component as well as constraints linking synoptic and local scales are also studied. The result is that, for a limited number of weather types, only the one corresponding to the winter anticyclonic blocking seems to produce a characteristic local response.In the second part of the thesis, the impact of the variability within the winter anticyclonic blocking weather type on this local response is studied, via the simulation of four episodes with different characteristics. To this end, High Resolution Mesoscale Simulations (down to about 100 meters horizontal resolution) are used to accurately capture the dynamics in complex terrain. The emission inventory implemented in the numerical model allows, in combination with the dynamics, to obtain an accurate spatial representation of the air pollution.From a dynamical point of view, it appears that the atmospheric circulation at the valley bottom is very homogeneous from one episode to the next and driven by thermal effects. Conversely, the height of the thermal inversion and the vertical structure of the valley winds depend on the synoptic conditions. Concerning atmospheric pollution, the main result is that the concentration fields at the valley bottom are similar from one episode to the other because the winds flowing along the valley floor are similar. This concentration field contains the same hot spots of pollution whatever the episode, implying that the population living there might be exposed to poor air quality during anticyclonic winter episodes.Ce travail de thèse porte sur le transport et la distribution spatiale de polluants de type particules fines dans la vallée alpine de Grenoble en hiver. Il est motivé par l'impact sanitaire de l'exposition à la pollution dans la vallée, qui se fait sur un temps long.Temps long et échelles spatiales de la vallée ne pouvant être pris en compte simultanément dans le cadre d'une étude détaillée du transport de polluants, la première partie du travail de thèse concerne la recherche de types de temps à l'échelle synoptique qui puissent être chacun associés à une dynamique caractéristique dans la vallée de Grenoble. Pour obtenir cette décomposition en type de temps, des méthodes classiques (ACP+Kmeans) et moins classiques (réseau de neurones LSTM convolutifs) sont comparées. L'introduction de la composante temporelle ainsi que des contraintes reliant les échelles synoptiques et locales sont aussi étudiées. Il en résulte que, si un nombre restreint de type de temps est recherché, seul celui correspondant au blocage anticyclonique hivernal semble produire une réponse locale caractéristique.Dans la seconde partie du travail de thèse, l'impact de la variabilité au sein du type de temps blocage anticyclonique hivernal sur cette réponse locale est étudié, via la simulation de quatre épisodes présentant des caractéristiques différentes. Des Simulations des Grandes échelles à haute résolution (jusqu'à 100 mètres environ de résolution horizontale) sont menées pour cela, qui permettent de capturer la dynamique atmosphérique en terrain complexe. Le cadastre d'émission implémenté dans le modèle numérique permet, en combinaison avec la dynamique, d'avoir une représentation spatiale fine de la pollution atmosphérique.D'un point de vue dynamique, il ressort que la circulation atmosphérique en fond de vallée est très homogène d'un épisode sur l'autre et pilotée par les effets thermiques. A l'inverse, la hauteur de l'inversion thermique et la structure verticale des vents de vallées dépendent des conditions synoptiques. Concernant la pollution atmosphérique, la dynamique dominante en fond de vallée conduit à de fortes hétérogénéités spatiales dont la localisation ne dépend pas de l'épisode considéré

Modeling of the wind power forecast errors and associated optimal storage strategy

Production forecast errors are the main hurdle to integrate variable renewable energies into electrical power systems. Regardless of the technique, these errors are inherent in the forecast exercise, although their magnitude significantly vary depending on the method and the horizon. As power systems have to balance out these errors, their dynamic and stochastic modeling is valuable for the real time operation. This study proposes a Markov Switching Auto Regressive-MS-AR-approach. The strength of such a model is to be able to identify weather types according to the reliability of the forecast. These types are captured with a hidden state whose evolution is controlled by a transition matrix. The autocorrelation and variance parameters of the AR models are then different from one state to another. After having validated its statistical relevance, this model is used to solve the problem of the optimal management of a storage associated with a wind power plant when this virtual power plant must respect a production commitment. The resolution is carried out by stochastic dynamic programming while comparing the proposed MS-AR with several other models of forecast errors. This illustrative problem highlights the improvements made by a fine modeling of forecast errors

Modeling of the wind power forecast errors and associated optimal storage strategy

Production forecast errors are the main hurdle to integrate variable renewable energies into electrical power systems. Regardless of the technique, these errors are inherent in the forecast exercise, although their magnitude significantly vary depending on the method and the horizon. As power systems have to balance out these errors, their dynamic and stochastic modeling is valuable for the real time operation. This study proposes a Markov Switching Auto Regressive-MS-AR-approach. The strength of such a model is to be able to identify weather types according to the reliability of the forecast. These types are captured with a hidden state whose evolution is controlled by a transition matrix. The autocorrelation and variance parameters of the AR models are then different from one state to another. After having validated its statistical relevance, this model is used to solve the problem of the optimal management of a storage associated with a wind power plant when this virtual power plant must respect a production commitment. The resolution is carried out by stochastic dynamic programming while comparing the proposed MS-AR with several other models of forecast errors. This illustrative problem highlights the improvements made by a fine modeling of forecast errors

Impact of climate change on persistent cold-air pools in an alpine valley during the 21st century

International audienceAbstract. When anticyclonic conditions persist over mountainous regions in winter, cold-air pools (i.e. thermal inversions) develop in valleys and persist from a few days to a few weeks. During these persistent cold-air pool (PCAP) episodes the atmosphere inside the valley is stable and vertical mixing is prevented, promoting the accumulation of pollutants close to the valley bottom and worsening air quality. The purpose of this paper is to address the impact of climate change on PCAPs until the end of this century for the alpine Grenoble valleys. The long-term projections produced with the general circulation model MPI (from the Max Planck Institute) downscaled over the Alps with the regional climate model MAR (Modèle Atmosphérique Régional) are used to perform a statistical study of PCAPs over the period 1981–2100. The trends of the main characteristics of PCAPs, namely their intensity, duration, and frequency, are investigated for two future scenarios, SSP2–4.5 and SSP5–8.5. We find that the intensity of PCAPs displays a statistically significant decreasing trend for the SSP5–8.5 scenario only. This decay is explained by the fact that air temperature over the century increases more at 2 m above the valley bottom than in the free air at mid-altitudes in the valley; this might be due to the increase of specific humidity near the ground. The vertical structure of two PCAPs, one in the past and one around 2050, is next investigated in detail. For this purpose, the WRF (Weather Research and Forecasting) model, forced by MAR for the worst-case scenario (SSP5–8.5), is used at a high resolution (111 m). The PCAP episodes are carefully selected from the MAR data so that a meaningful comparison can be performed. The future episode is warmer at all altitudes than the past episode (by at least 4 ∘C) and displays a similar inversion height, which are very likely generic features of future PCAPs. The selected episodes also have similar along-valley wind but different stability, with the future episode being more stable than the past episode. Overall, this study shows that the atmosphere in the Grenoble valleys during PCAP episodes tends to be slightly less stable in the future under the SSP5–8.5 scenario, and statistically unchanged under the SSP2–4.5 scenario, but that very stable PCAPs can still form

Impact of climate change on wintertime European atmospheric blocking

International audienceAbstract. We study the impact of climate change on wintertime atmospheric blocking over Europe focusing on the frequency, duration, and size of blocking events. These events are identified via the weather type decomposition (WTD) methodology applied on the output of climate models of the Coupled Model Intercomparison Project phase 6 (CMIP6). Historical simulations and two future scenarios, SSP2-4.5 and SSP5-8.5, are considered. The models are evaluated against the reanalysis, and only a subset of climate models, which better represent the blocking weather regime in the recent-past climate, is considered for the analysis. We show that the spatio-temporal characteristics of recent-past atmospheric blocking are in agreement with previous studies that define blocking events with blocking indexes. We find that frequency and duration of blocking events remain relatively stationary over the 21st century. We define a methodology that relies on the WTD for the blocking event identification in order to quantify the size of the blocking events, and we find that the blocking size is basically unchanged in the future