Atelier national sur les nuages polaires

24/06/2025 09:00

SIRTA / ICEO : Journée Scientifique 2025

24/06/2025 09:00

Evénement de clôture projet FAIR-EASE

12/06/2025 09:00

The art of climate model evaluation : example of ENSO

18/07/2023 11:00

Climate models help us understand the complexity of Earth’s climate, forecast the next seasons and predict the influence of anthropogenic forcings. It is therefore important to evaluate the performance of these models relative to observational datasets, to build confidence and to improve them.

Sea level extremes and compounding marine heatwaves in coastal Indonesia

18/07/2023 11:00

Low-lying island nations like Indonesia are vulnerable to sea level Height EXtremes (HEXs). When compounded by marine heatwaves, HEXs have larger ecological and societal impact. Here we combine observations with model simulations, to investigate the HEXs and Compound Height-Heat Extremes (CHHEXs) along the Indian Ocean coast of Indonesia in recent decades.

Forests in the Earth System

04/07/2023 11:00

Séminaire du LGENS par Benjamin Quesada (Universidad del Rosario).

Local and remote sources of Arctic air pollution

09/09/2022 10:00

The Arctic region is warming faster than any other region on Earth due to the effect of greenhouse gases, notably CO₂, and short-lived climate forcers of anthropogenic origin, such as black carbon (BC). Over the last 20-30 years, remote anthropogenic emissions over mid-latitude regions have been decreasing. Anthropogenic emissions within the Arctic are also contributing and might increase in the future and further affect Arctic air pollution and climate. Natural emissions, such as sea-spray aerosols, also might increase due to on-going climate change. However, the processes and sources influencing Arctic aerosols and trace gases are poorly quantified, especially in wintertime.

In this thesis, quasi-hemispheric and regional simulations are performed using the Weather Research Forecast model, coupled with chemistry (WRF-Chem). The model is used to investigate atmospheric composition over the wider Arctic and during two field campaigns, one in northern Alaska at Barrow, Utqiaġvik in January and February 2014 and the second in Fairbanks, central Alaska in November and December 2019 during the French pre-ALPACA (Alaskan Layered Pollution And Chemical Analysis) campaign.

First, modelled inorganic and sea-spray (SSA) aerosols are evaluated at remote Arctic sites during wintertime. Then, the model is improved with respect to SSA treatments, following evaluation against Barrow field campaign data, and their contribution to the total aerosol burden within the Arctic region is quantified. A series of sensitivity runs are performed over northern Alaska, revealing model uncertainties in processes influencing SSA in the Arctic such as the presence of sea-ice and open leads. Second, a sensitivity analysis is performed to investigate processes and sources influencing wintertime BC over the wider Arctic and over northern Alaska, with a focus on removal treatments and regional emissions. Variations in model sensitivity to wet and dry deposition are found across the Arctic and could explain model biases. Over northern Alaska, regional emissions from petroleum extraction are found to make an important contribution to observed BC.

Model results are also sensitive to planetary boundary layer parameterisation schemes. Third, the improved version of the model is used to investigate the contribution of regional and local sources on air pollution in the Fairbanks area in winter 2019. Using up-to-date emissions, the model performs better in winter 2019 than in winter 2014, when compared to observations at background sites across Alaska. Underestimations in modelled BC and sulphate aerosols can be partly explained by lacking local and regional anthropogenic emissions. In the case of sulphate, additional secondary aerosol formation mechanisms under dark/cold conditions also need to be considered.

Approches statistiques multivariées pour l'ajustement des biais des simulations climatiques et l'analyse des événements composés

23/09/2022 10:00

Le climat est un système complexe qui est le résultat de multiples interactions entre ses différentes composantes et ses multiples variables. Cette thèse a pour but d’évaluer si et comment l’utilisation d’approches statistiques multivariées pour l’étude des simulations climatiques peut contribuer à une compréhension plus approfondie du changement climatique et des événements climatiques à forts impacts sur la société. Pour répondre à ces questions, je propose et applique de nouveaux outils statistiques multivariés pour, d’une part, la correction de biais des simulations climatiques, et d’autre part, l’étude des changements de probabilités d’événements conjoints à forts impacts. Le travail s’articule autour de trois objectifs : (i) comparer des méthodes de correction de biais multivariés (MBC) déjà existantes, (ii) développer une nouvelle méthode MBC pour l’ajustement des dépendances spatiales des simulations climatiques, (iii) évaluer la période d’émergence des probabilités d’événements conjoints et quantifier la contribution des propriétés univariées et multivariées aux changements de ces probabilités.

La comparaison de méthodes de correction de biais a permis d’une part d’informer les utilisateurs de leurs avantages et leurs inconvénients mais aussi d’identifier des pistes de développements pour de nouvelles méthodes. Une nouvelle méthode, basée sur une technique de Machine Learning appelée réseaux adverses génératifs (CycleGAN), a été développée. Elle donne des résultats satisfaisants, montrant ainsi le potentiel des techniques de Machine Learning pour la correction de biais multivariés. L’évaluation de la période d’émergence des probabilités d’événements conjoints, ainsi que la quantification de la contribution des propriétés univariées et multivariées aux changements de ces probabilités se révèlent être une procédure pertinente pour améliorer la compréhension de tels phénomènes climatiques. Il est trouvé que la non-stationnarité de la structure de dépendance inter-variable dans un contexte de changement climatique peut jouer un rôle important dans les probabilités futures d’événements conjoints.

Les travaux réalisés dans cette thèse ouvrent des perspectives pertinentes en termes méthodologiques mais participent aussi à une amélioration de la compréhension du climat et de ses évolutions en fournissant des outils statistiques adaptés à la nature intrinsèquement multivariée du système climatique.

Ocean ventilation at the mesoscale

18/07/2022 14:00

Within the Earth’s climate system, the ocean is engaged as a huge reservoir of important properties such as heat and carbon, predominantly resulting from exchanges with the atmosphere on timescales from hours to millennia. Such large volume of storage in the ocean interior thus questions the mechanisms of water property transport and distribution, leading to the concept of ocean ventilation, a process that connects ocean surface waters with the interior. Commonly associated with an increase in density of surface waters, ventilation is typically interpreted as a downward transfer of water masses due to stability and other fine-scale processes. Understanding the dynamics and thermodynamics of water mass formation, ventilation and dissipation, is therefore one of the key scientific challenges confronting the entire climate community.

In this thesis, several processes related to ventilation have been discussed and a specific attention has been given to the mesoscale whose typical length is less than 100 km and timescale spans on the order of a month. The largest proportion of mesoscale kinetic energy is contained by coherent vortices, known as mesoscale eddies, which are nearly geostrophic and can have the vertical extent down to the thermocline. Aimed at a combination between the ventilation theory and mesoscale dynamics, the first part of this thesis has been devoted to a revisit to the theory of subduction at the bottom of mixed layer that quantifies long-term (permanent) transport of surface water masses into the main thermocline. Interpreted as a transient state in the subduction process, mode waters are a specific type of water mass homogeneous in properties (i.e., characterized by low potential vorticity) and residing between the seasonal and main thermoclines.

Such transiency of mode waters is associated with their formation mechanism largely due to surface buoyancy forcing that is season-dependent. The second part of this thesis is thus related to an algorithm development to detect more precisely than other available methods the surface mixed layers and mode waters from several profiling databases. By co-locating mode waters with mesoscale eddies identified from the satellite altimetry, it is possible to quantify 1) the percentage of mode waters carried by eddies in an Eulerian sense, and 2) anomalies of temperature, salinity and others transported within eddies in a Lagrangian framework. Accordingly, a revisit to global mode water distribution has been provided, in terms of their dynamics and thermodynamics at the mesoscale. The South Atlantic Subtropical Mode Water has been considered as a special example and brought into details in the last chapter, since it not only forms according to the typical baroclinity at the western boundary, but also develops due to a large amount of inter-basin transport carried by anticyclonic Agulhas Rings shedding from the Indian Ocean.

Apart from the thermohaline perspective of ocean circulation and ventilation, i.e., surface convection and its significance on mode water formation and renewal, this thesis also provides an assessment on the wind-driven aspect and a combination of these two components. In specific, we extended the Ekman dynamics to allow for an influence from geostrophic motions and self-advection. A brief discussion on diapycnal and more complex physics of ventilation at the mesoscale is also presented.