La météo en Antarctique. Observer l’actuel - Prévoir l’avenir

12/05/2022 16:30

Face à l'anthropocène : quels regards adopter pour accompagner l'orientation et l'action ?

25/04/2022 17:30

Comprendre le 6e rapport du GIEC - 3e volet

21/04/2022 18:00

Weathering everywhere? Exploring water pathways from a very steep mountain catchment to upland hills

28/11/2025 13:00

Séminaire de l’UMR METIS-IPSL.

Marché Carbone : où va l’Europe ?

21/11/2025 14:00

Nouvelle séance du séminaire « Changement Climatique : Sciences, Sociétés, Politique » co-organisé par le Centre Alexandre Koyré et l’École Normale Supérieure (CERES).

Calibration / Validation du radar et du lidar de la mission EarthCARE

17/11/2025 11:30

Séminaire organisé par le LATMOS.

Oceanic infrasound as a tracer of middle atmosphere dynamics: evaluating atmospheric model performance and data assimilation for numerical weather prediction

25/11/2025 14:00

This thesis explores a new way to improve weather forecasts in the middle atmosphere (10-100 kilometers), where current models lack sufficient data. To this end, we use infrasound, low-frequency sound waves recorded worldwide by an international network of sensors. Infrasound can be considered as tracers of the atmospheric state through which they propagate. A method was developed to compare oceanic infrasound observations with numerical simulations. Based on this method, we present assessments of weather model performances, including during extreme atmospheric events. Finally, a data assimilation approach was implemented to correct atmospheric models using oceanic infrasound observations. First results of synthetic atmospheric state corrections are demonstrated.

 

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Cette thèse explore une nouvelle manière d’améliorer les prévisions météorologiques dans la moyenne atmosphère (10-100 kilomètres), là où les modèles actuels manquent de données. Dans ce but, nous utilisons des infrasons, des ondes sonores basses fréquences, enregistrées partout sur Terre par un réseau international de capteurs. Les infrasons peuvent être vus comme des traceurs de l’état de l’atmosphère dans laquelle ils se propagent. Une méthode permettant de comparer des observations d’infrasons d’origine océanique à des simulations numériques a été développée. à partir de cette méthode, nous présentons des évaluations sur les performances des modèles météorologiques, notamment pendant des événements atmosphériques extrêmes. Enfin, une approche permettant de corriger les modèles d’atmosphère à partir d’observation d’infrasons océaniques a été implémentée à partir de méthodes d’assimilations de données. Des premiers résultats de correction d’états atmosphériques synthétiques sont présentés.

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.