Derrière les étoiles ou différentes façons de voir un soleil

28/03/2025 12:30

Projets du GIEC et liens avec les prises de décision en matière de climat

24/03/2025 16:30

Arts et sciences face au changement climatique et à la transition écologique

24/03/2025 09:00

Signature géodésique et gravimétrique des variations de l’hydrologie continentale

24/09/2021 12:00

Les redistributions des masses d’eau au sein de et entre l’atmosphère, les océans et les réservoirs hydrologiques continentaux induisent des déformations de la croûte terrestre et des variations spatio-temporelles de gravité mesurables par les techniques de géodésie, aujourd’hui devenues suffisamment précises. L’hydrogéodésie est donc aujourd’hui en plein développement.

Publication du 6e rapport du GIEC : quoi de neuf ?

17/09/2021 00:00

Lancement de la nouvelle saison du séminaire « Changement Climatique : Sciences, Sociétés, Politique » co-organisé par le Centre Alexandre-Koyré (EHESS-CNRS) et l’ENS (CERES). Un vendredi sur deux de 14 h à 17h, du 17 septembre 2021 au 21 janvier 2022 à l’École Normale Supérieure.

Developing A Satellite-Based Dataset of Convective Mass Flux: Validations and Applications to Convective Dynamics Studies and Evaluation of GCM

16/09/2021 11:00

Most current GCM cumulus parameterization schemes are based on the concept of convective mass flux. Yet, no global observations of this critical parameter exist at this time. To fill the vacuum, we developed a novel, satellite-based method to retrieve convective mass flux.

Modelling and assessing agrivoltaics as a solution to the climate-water-energy-food nexus in the context of climate change in the Euro-Mediterranean region

27/11/2025 14:00

Climate change in the Euro-Mediterranean (EUROMED) region exacerbates agricultural challenges by increasing land vulnerability and reducing water availability. In response to these pressures, agrivoltaics (AVs), which combines photovoltaic (PV) energy production with agriculture on the same land, offers a promising solution within the water-energy-food-ecosystem (WEFE) nexus. AVs can enhance agricultural resilience, reduce water consumption, promote renewable energy and reduce land-use conflicts. By creating partial shading, AVs alleviates thermal stress and limits soil water evaporation, enhancing crop microclimate. However, AV performance is highly dependent on climate, crop type, and geographical context, requiring modeling tools capable of assessing AV performance at regional scales. Yet, current literature mostly focuses on site-specific models, lacking a broader, holistic approach. To address this gap, we develop a novel regional-scale AV modeling framework by integrating a PV module with the ORCHIDEE (Organizing Carbon and Hydrology In Dynamic Ecosystems) land surface model. The AV model modifies solar radiation and wind speed from regional climate models, which -along with other meteorological inputs- are fed into ORCHIDEE to simulate energy, water, carbon and nitrogen fluxes at the land surface. By prescribing agricultural soil parameters, this integrated approach enables to explore AV impacts within the WEFE nexus under both current and future climate conditions. In the first part of this project, we apply the AV model using reanalysis climate data to assess AV performance under current climate conditions in two contrasting regions: the Iberian Peninsula and the Netherlands. In the drier Iberian Peninsula, AVs offers substantial benefits, particularly under drought conditions. These include improved yields, food security, and water and land use efficiency, alongside clean energy production. Simulations with varying nitrogen fertilizer levels indicate that AVs can enhance nitrogen use efficiency and maintain or increase productivity of conventional systems, while reducing green house gas emissions. In contrast, in the Netherlands -where precipitation is more abundant and solar radiation is lower- AVs tends to reduce crop yields, with limited resource efficiency gains. This contrast suggests an heterogeneous potential for AV deployment in the EUROMED region, which spans arid to temperate zones. To further explore this, the second part of the study applies the model to the entire EUROMED basin using EURO-CORDEX climate projections under RCP 8.5. This enables an evaluation of AV systems as a climate adaptation strategy within the WEFE nexus. Results show that AV benefits are strongly influenced by regional climate trajectories and water availability trends. Southern, drought-prone areas are especially well-suited for AVs, with high potential to reduce water stress and sustain agricultural productivity under warming conditions. In northern, wetter regions, the benefits are less evident, emphasizing the need for targeted deployment.

Drivers of low‑level cloud seasonality over sea ice and Greenland: Insights from 13 years of spaceborne lidar observations,

20/10/2025 09:30

Arctic clouds play a critical role on the sea-ice and Greenland Ice-sheet by modulating the energy received at the surface. The surface cloud radiative effect (CRE) results from two competitive effects: a shortwave cooling effect, the umbrella effect, and a longwave warming effect, the blanket effect. When considering both the Greenland ice-sheet and the sea-ice, the CRE is dominated by the longwave component and lead to a net warming effect at the surface, except for a short period in summer. As a result, they may limit sea-ice growth during winter, trigger melt events in spring or delay the freeze-up of both sea-ice and the Greenland Ice-sheet during fall. This thesis investigates the drivers of low-level clouds seasonality over the sea-ice and the GrIS, which remain poorly understood, and the associated effect on the surface radiative budget, using 13 years of space-based active cloud remote sensing by CALIPSO.

We distill three key results that clarify the seasonal controls on Arctic low-level clouds and their surface radiative impact:

(i) The steep spatially homogeneous increase of low-level optically thick clouds over the sea-ice in spring was attributed to the increase of lower troposphere temperature. While moisture transport from mid-latitudes is already sufficient to trigger the transition earlier in spring, the steep transition of temperature, from ∼−20°C in March to ∼−13oC in May, favors the formation of more liquid-containing clouds (optically thick) against ice clouds (optically thin).

(ii) From winter to spring, we reveal a weak but statistically significant control of surface pressure on the radiative effect of clouds over the Arctic sea-ice. This weak control is likely to explain the regional patterns of surface cloud radiative warming for a given period: minimum in April over the Beaufort Sea and maximum in winter-early spring over the Barents Sea.

(iii) Using a machine learning approach, we demonstrate that the surface cloud radiative warming increase of +10W/m² in September compared to July over the Greenland west coast is attributed to frequent « polar low » circulation in the Baffin Sea, advecting clouds over the coast. This maximum occurs still in a period considered as the melt season, over a region representing 22% of the total mass loss of the ice-sheet over the last two decades.

These results suggest that space-based active cloud observations over the sea-ice and the GrIS provide strong observation constraints, helping to overcome past limitations due to the scarcity of Arctic cloud measurements. Future studies should exploit new missions such as EarthCARE to better understand the drivers of Arctic cloud seasonality and radiative effects in summer for instance.

From coherent structures to convective storms: statistical, observational and modelling approaches to turbulent flows

15/10/2025 10:00

The understanding of climate change and its impacts has significantly advanced in recent decades, revealing the formidable challenges it poses to humanity. In particular, it is now well established that the continued anthropogenic emissions of greenhouse gases are not only driving an increase in global mean temperature but also amplifying the frequency and intensity of extreme weather events such as heatwaves and heavy precipitation. However, some aspects remain poorly understood, such as the influence of climate change on complex weather phenomena like convective storms, which can produce significant hazards, including floods, hail, lightning, and severe winds. This knowledge gap arises mainly from the multiscale, multivariate, and nonlinear nature of such phenomena, which involve intricate interactions among atmospheric variables. These processes are governed by turbulence, characterised by highly disordered fluid motions that present major challenges for both theoretical understanding and numerical modeling. In particular, turbulent flows require a very large number of degrees of freedom to be comprehensively accounted for in computer simulations, which is far beyond the capabilities of current computational resources in realistic environmental or industrial settings. As a result, numerical models use subgrid-scale modelling strategies with many adjustable parameters to represent unresolved processes, which introduces uncertainties.

This thesis addresses these challenges by focusing in particular on the analysis and modelling of coherent structures—organized, recurrent flow patterns such as eddies that emerge from the apparent disorder and provide a more tractable view of turbulence. Special emphasis is placed on convective storms in the context of climate change. First, we show how high-dimensional atmospheric data can be simplified through statistical approaches that extract recurring patterns. Specifically, a generative probabilistic model originally developed for topic modeling in text analysis is adapted to decompose maps of atmospheric variables into spatial patterns that can be identified as atmospheric coherent structures. Second, we examine the challenges in studying convective storms and their evolution with climate change, outlining the limitations of available observations and numerical models. In particular, an initial climatology of derechos, a severe type of convective storm, is constructed for France using multiple observational datasets. We also analyse historical changes in atmospheric environments associated with such events with a methodology that accounts for the conditioning role of the large-scale atmospheric configuration. Finally, a modelling approach for turbulence based on the dynamics of coherent structures is proposed. This approach accounts for the intermittent nature of energy dissipation and leverages the sparsity of coherent structures to limit computational costs. Such strategy could provide more efficient and accurate alternatives to current subgrid-scale models of turbulence, with potential application for atmospheric convection and climate models.