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La météo en Antarctique. Observer l’actuel - Prévoir l’avenir
12/05/2022 16:30
Avec Jean-Baptiste Madeleine (LMD-IPSL)
Face à l'anthropocène : quels regards adopter pour accompagner l'orientation et l'action ?
25/04/2022 17:30
Ce séminaire est organisé dans le cadre de Prof en Fac.
Comprendre le 6e rapport du GIEC - 3e volet
21/04/2022 18:00
Assistez à la restitution du rapport du groupe III du GIEC par Céline Guivarch, chercheuse impliquée dans sa rédaction.
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À l'origine des fleuves dans les Andes semi-arides : le rôle hydrologique des glaciers rocheux et des tourbières vu par les méthodes hydrogéophysiques et isotopiques
07/05/2021 12:00
Dans les Andes semi-aride du Chili, les glaciers rocheux sont d’une importance majeure, car ils délivrent de l’eau aux saisons les plus critiques. Ils sont de plus prépondérants par rapport aux glaciers blancs dans cette région des Andes.
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Modelling the regional impacts of irrigation on the climate, water cycle, and atmospheric boundary layer over the Iberian Peninsula
01/12/2025 13:30
Irrigation is a widespread agricultural practice expected to keep expanding in the future. It is recognized as a major anthropogenic driver of land-atmosphere interactions, significantly affecting regional climate, continental and atmospheric water cycle components, surface energy balance, and the atmospheric boundary layer (ABL). Under climate change, in semi-arid regions like most of the Mediterranean basin, it is associated with major challenges regarding water availability, increased evaporative demand, and disrupted precipitation patterns, justifying efforts to understand and represent the diversity of its impacts.
This thesis investigates the regional effects of irrigation on the water cycle, climate, and the atmospheric boundary layer over the Iberian Peninsula using the ICOLMDZOR limited area model (LAM) at 25-kilometre resolution. This new regional climate model stems from the global climate model developed at Institut Pierre-Simon Laplace (IPSL-CM), using the ORCHIDEE land surface model with a new routing scheme, and the ICOLMDZ atmospheric model. The LAM is evaluated over the region under recent climate (2010-2022), and simulations with and without irrigation are compared to isolate its impacts. Simulations of future climate under the SSP5-8.5 scenario are also analysed to assess how these impacts interact with those of climate change.
This work first demonstrates the dominant influence of irrigation on the ability of the land surface model to simulate river discharge in offline simulations. It identifies an appropriate set of parameters for the river routing and irrigation schemes over the Iberian Peninsula, to adapt to a 1-arcminute resolution topography and better reflect regional irrigation practices.
Using this improved representation of the land surface, coupled LAM simulations reveal that the atmospheric impacts of irrigation mainly consist in a cooling and moistening over irrigated areas and a stabilization of the ABL. Partial recycling of atmospheric moisture is identified at the scale of the Peninsula, with increases in precipitation in mountainous regions surrounding the intensely irrigated Ebro Valley. The atmospheric processes at play are analysed in more details by comparing the ICOLMDZOR LAM to point-based observations (surface measurements and radio-soundings) from the Land Surface Interactions with the Atmosphere over the Iberian Semi-Arid Environment (LIAISE) campaign, held in the Ebro valley in July 2021. In a sensitivity experiment with increased water availability for irrigation, surface fluxes are found to be greatly improved compared to observations. In comparison to Meso-NH simulations at 2-kilometre resolution, surface variables in the ICOLMDZOR grid cell for the irrigated observation site match the average of Meso-NH grid cells it contains. This suggests that the modelling approach for irrigation and surface fluxes used in ICOLMDZOR is sufficient to represent grid-cell average impacts at the surface. However, although the cooling and moistening effects of irrigation are found to extend vertically into the ABL, ICOLMDZOR does not achieve as good performance in ABL representation as in surface variables. This is likely attributed partly to a lack of sub-grid heterogeneities, in surface fluxes, but also in wind speed and direction, and to advection terms that do not perfectly reflect observed weather conditions of the campaign.
Overall, this PhD work presents a first use-case of the new ICOLMDZOR LAM for the study of land-surface interactions at the regional and climatic scales, with visible impacts of irrigation on river discharge, precipitation, surface variables and ABL development. Several biases of the ICOLMDZOR LAM over the region were also identified and partly corrected, and possible improvements are presented for upcoming regional climate modelling studies.
Mobility and urban road transport CO₂ emissions at high resolution from Floating Car Data
28/11/2025 14:00
Road transport is a direct source of CO2 emissions, accounting for 11% of global total GHGs, with approximately twothirds of these emissions being generated in urban areas (International Energy Agency). These emissions areaccompanied by harmful air pollutants, posing significant health risks, especially to city inhabitants. Traditional “top-down”emission inventory methods rely on fuel sales data and disaggregation techniques, leading to considerable spatial andtemporal uncertainties.
In contrast, “bottom-up” approaches, based on vehicle counts per road segment combined withemission factors, enable high-resolution estimates useful for environmental modeling and local policy assessment.However, conventional traffic monitoring systems (e.g., inductive loops, cameras, manual counts…) are costly and limitedin spatial coverage. The recent proliferation of vehicle geolocation data provides a new opportunity to reconstruct roadtraffic at lower cost, especially in unmonitored areas.
This PhD thesis aims to leverage such data to estimate urban trafficand associated emissions of CO2 and other co-emitted pollutants at high spatiotemporal resolution. The first chapterdevelops a Machine Learning method to estimate hourly traffic flow and occupancy per road segment in Paris, using onlyopen data traffic monitoring. This work spans the period 2018-2022 and highlights the impact of COVID-19 on mobilitybehavior.
The second chapter applies speed-dependent emission factors from the Computer Program to CalculateEmissions from Road Transport (COPERT) to estimate emissions of CO2, NOx, and PM. The analysis includes theinfluence of fleet modernization and the growing share of Sport Utility Vehicles (SUVs). The third chapter, conductedduring a research stay at the University of California Irvine, extends the bottom-up approach to 457 U.S. cities using streetlevel Floating Car Data (FCD) from TomTom and accessed through the Kayrros company. Since FCD only covers asample of vehicles, the signal is adjusted using statistics from the Federal Highway Administration. The data’s speeddistribution enables the use of the MOtor Vehicle Emission Simulator (MOVES) model for emissions estimation. The roleof traffic congestion and population density is also explored. The fourth chapter focuses on Europe, where validation datafor traffic volume is less accessible. We compile open traffic datasets from 36 major cities and publish a standardizeddataset of annual average daily traffic volumes to support further research. The fifth chapter evaluates the extent to whichprivate FCD data (here from NEXQT company) can replicate the real traffic volumes.
Firstly, our aim is to reconstruct thedaily traffic volumes reported in the previous chapter in 28 major European cities. We examine the performance of locallytrained Machine Learning models before generalizing to broader zones and discuss the limitations of using FCD for thistask. Finally, we compare the performance of classical tabular machine learning models with Graph Neural Networks(GNN) for hourly flow prediction in Paris, Berlin, Madrid and Zurich. This work enhances the quantification of urban CO2 emissions from road transport by leveraging large-scale, heterogeneous geolocation data, providing new insights forspatiotemporal emission monitoring, policy evaluation, and the transition toward more sustainable urban mobility.
Modèles simplifiés de climat : approche thermodynamique et approche dynamique.
26/11/2025 14:00
En Français
Les modèles de climat possèdent des paramètres mal contraints calibrés sur les observations du climat du présent. La justesse de l’extrapolation des résultats pour des climats du passé ou du futur n’est pas garantie. Dans l’atmosphère, modéliser directement la dynamique avec les valeurs moléculaires bien connues des coefficients de viscosité et de diffusion, est impossible avec les capacités numériques actuelles, et très certainement, futures. Il y a donc besoin d’explorer des voies alternatives. Le but cette thèse est de créer des modèles simples de climat, plus robustes, sans paramètres ajustables mal contraints .
L’hypothèse de maximisation de la production d’entropie (MEP) sous contraintes permet de calculer un champ de variables thermodynamiques (températures, précipitations, humidité…). Dans une première partie, j’utilise MEP dans un modèle radiatif-convectif, pour calculer des précipitations. Je montre que le modèle minimal pour calculer une humidité relative satisfaisante avec MEP, doit inclure la convection profonde avec un panache nuageux.
Les log-lattices sont un outil mathématique permettant de résoudre des équations aux dérivées partielles à toutes les échelles spatiales, à coût numérique réduit. Dans une deuxième partie, j’étudie les lois d’échelle dans les équations de Rayleigh-Bénard en rotation, projetées sur des log-lattices. Je retrouve le régime ultime quasi-géostrophique.
In English
Climate models have unconstrained parameters tuned on present climate observations. The accuracy of results for past or future climate extrapolation is not guaranteed. In the atmosphere, directly modelling the dynamics with well-known molecular viscous or diffusion coefficient values is impossible with today, and certainly not future, numerical capacities. Therefore, exploring alternative ways is needed. This thesis aims to create simple, more robust climate models with no poorly constrained adjustable parameters.
The maximum entropy production hypothesis (MEP) under constraints enables the computation of thermodynamic variable fields (temperature, precipitation, humidity…). In the first part, I use MEP in a radiative-convective model to compute precipitation. I show that the minimum model computing a satisfying relative humidity with MEP must include deep convection with a cloud plume model.
Log-lattices are a mathematical tool for solving partial differential equations at all spatial scales, at reduced numerical cost. In a second part, I study scaling laws in rotating Rayleigh-Bénard equations, projected on log-lattices. I find the quasi-geostrophic ultimate regime.
