Thèse Contraindre les Projections des Extrêmes de Précipitations Pertinents pour les Inondations dans un Climat en Réchauffement Grâce aux Observations et à la Modélisation Climatique à l'Échelle H/F - Doctorat.Gouv.Fr

Établissement : Université de Toulouse École doctorale : SDU2E - Sciences de l'Univers, de l'Environnement et de l'Espace Laboratoire de recherche : CECI - Climat, Environnement, Couplages et Incertitudes / CERFACS Direction de la thèse : Margot BADOR ORCID 0000000339766946 Début de la thèse : 2027-09-01 Date limite de candidature : 2026-11-23T23:59:59 Sub-daily extreme precipitation, such as intense rainfall occurring over a few hours, is a major driver of flash flooding and other damaging impacts. Yet, despite its societal importance, our understanding of how these extremes are changing globally remains limited. The International Panel on Climate Change Sixth Assessment Report highlights a lack of systematic analysis of long-term changes in sub-daily extreme precipitation at the global scale, largely because observations are sparse, unevenly distributed, and often too short to robustly detect changes. Regional studies assessing future changes generally point towards an intensification of sub-daily rainfall extremes, but there is still low confidence in an overall global increase.
A major challenge is that conventional global climate models cannot explicitly represent the processes of the atmospheric convection responsible for short-duration precipitation extremes. Kilometre-scale, convection-permitting climate models substantially improve the representation of these processes and can provide more realistic simulation of intense rainfall, particularly over complex terrain. However, such simulations remain computationally demanding and are currently available only for selected regions. At the same time, their evaluation is difficult because high-quality observations of sub-daily precipitation are themselves highly limited geographically and uncertain. As a result, there is currently no straightforward way to obtain a consistent global picture of how sub-daily precipitation extremes may change in a warming climate.
This PhD will address this gap by bringing together and exploiting the rapidly growing range of available climate simulations of sub-daily precipitation. The project will compile and assess kilometre-scale convection-permitting simulations from international modelling initiatives, national modelling centres, and research groups worldwide, together with available observational datasets from various sources, including in-situ measurements, gridded products, satellite observations, and reanalyses. A key component will be to characterise observational uncertainty and develop approaches to reconcile different datasets, providing robust benchmarks for evaluating climate simulations for sub-daily precipitation extremes. The project will then combine observational constraints, kilometre-scale simulations, and other available climate information to develop a consistent global assessment of projected changes in sub-daily precipitation extremes at specified levels of global warming. The analysis will also investigate the physical drivers of these changes across diverse regions, helping to understand regional differences and assess the robustness of projected responses. Particular attention will be given to regions where observational and modelling information is currently limited, helping to reduce geographical gaps in knowledge.
The project will provide the student with training at the interface of kilometre-scale climate modelling, precipitation observations, and climate impacts, as well as experience working with large and heterogeneous climate datasets. An important part of the research will involve identifying and accessing existing simulations and observations, requiring interaction with modelling centres and research groups worldwide and providing opportunities to develop international scientific collaborations. The PhD will be jointly supervised between CECI (CERFACS/CNRS/IRD) in Toulouse, France, and the Climate Change Research Centre at UNSW Sydney, Australia, providing an international research environment and exposure to leading research networks in climate extremes, observations, and high-resolution climate modelling. Despite their importance for impacts such as flash flooding, our understanding of how sub-daily extreme precipitation is changing globally remains limited. The International Panel on Climate Change (IPCC) Sixth Assessment Report highlights a lack of systematic analysis of long-term trends in sub-daily extreme precipitation at the global scale, primarily because observations have sparse spatial coverage and are often too short to robustly quantify past changes (Seneviratne et al., 2021). Nevertheless, studies from regions across almost all continents generally indicate an intensification of sub-daily extreme precipitation, although there remains low confidence in an overall increase at the global scale (Seneviratne et al., 2021). This contrast between growing regional evidence and the lack of a consistent global assessment highlights the need to bring together the diverse observational and modelling information currently available to better characterise changes in sub-daily precipitation extremes.
Sub-daily extreme precipitation remains one of the most challenging variables to simulate for climate models. Capturing short-duration precipitation extremes requires the realistic representation of processes across a wide range of scales, from large-scale circulation controlling event occurrence to local convective processes and their interaction with complex terrain (Khodayar et al., 2016). Consequently, biases can arise from deficiencies in representing processes ranging from synoptic-scale dynamics to the local conversion of atmospheric forcing into precipitation (Oldham-Dorrington et al., 2025). A long-standing limitation of current regional climate models is that they produce precipitation that is too frequent and too widespread, while underestimating the intensity of the most extreme events (Lucas-Picher et al., 2021). These biases are closely linked to the parameterisation of deep convection, which becomes necessary at grid spacings of tens of kilometres and fundamentally limits the representation of convective processes (Prein et al., 2015). As a result, the simulation of sub-daily precipitation has become a strong scientific motivation for the transition towards kilometre-scale, convection-permitting climate modelling.
Kilometre-scale simulations explicitly represent deep convection and substantially improve the representation of short-duration, high-intensity precipitation, particularly over complex terrain (Ban et al., 2021; Bador et al. 2025). Kilometre-scale climate models therefore offer an exciting opportunity to robustly assess how the most extreme precipitation may change in a warming climate. However, these simulations remain computationally demanding and are available only over limited regions, while their evaluation is itself challenging because observations of sub-daily precipitation are sparse and uncertain, particularly in remote regions and over complex terrain (Pritchard et al., 2023). There is therefore currently no straightforward way to obtain a consistent global picture of projected changes in sub-daily precipitation extremes: global Earth System Models do not resolve relevant processes, while kilometre-scale simulations provide detailed information only over selected regions. Bridging this gap requires combining information from observations, kilometre-scale simulations, and other available sources of climate information, while accounting explicitly for their respective uncertainties and limitations.
The PhD will aim to improve our understanding and projection of changes in sub-daily precipitation extremes at the global scale, with a particular focus on events relevant to flooding and other societal impacts. Building on existing expertise in precipitation observations, extremes, and high-resolution climate modelling, the project will bring together information from a wide range of sources, including observational datasets and kilometre-scale regional climate simulations. A key objective will be to assess the strengths, uncertainties, and complementarity of these different sources and develop approaches to combine them to provide robust estimates of global changes in sub-daily precipitation at specific global warming levels. In doing so, the project will address a major gap in current climate projections: conventional Earth System Models cannot explicitly resolve sub-daily precipitation processes and therefore cannot directly provide a consistent global picture of future changes in sub-daily precipitation extremes. Particular attention will be given to regions where observational and modelling information is currently limited, helping to reduce current geographical inequities in climate knowledge by improving our understanding and projection of sub-daily precipitation extremes in underrepresented regions. The project will leverage existing sources of information on sub-daily precipitation and its future changes globally, capitalising on the rapidly growing body of available simulations to identify robust responses of sub-daily precipitation extremes to climate change. The project will collect and systematically assess available sources, including kilometre-scale climate simulations from international initiatives (e.g. CORDEX FPS-Convection over Europe and CORDEX SHEP over Australasia), national modelling centres, and individual research groups, alongside in situ and gridded datasets, satellite observations, reanalyses and hybrid products.
A central component of the PhD will be to characterise and account for uncertainties across observational datasets, building on the PhD supervisors' strong expertise in daily and sub-daily precipitation extremes (Bador et al., 2020; Alexander et al., 2025). The project will assess the strengths and limitations of different observational sources and develop approaches to reconcile and combine them into robust benchmarks for model evaluation (Isphording et al., 2024), particularly in regions with sparse observations and complex terrain, where the selection of appropriate models can be critical for increasing confidence in future changes (Nguyen et al., 2023).
Finally, these complementary sources of information will be combined to develop a consistent global assessment of changes in sub-daily precipitation extremes at specified global warming levels. The project will investigate how regional kilometre-scale simulations, observational constraints, and other available modelling information can be integrated to fill gaps in the global picture and provide robust estimates of future changes. The physical drivers of the projected regional changes will also be investigated, helping to identify common mechanisms and sources of regional variability and assess the robustness of changes. Particular attention will be given to extremes relevant to societal impacts, such as flash flooding and risks to human security and urban infrastructure.

We are seeking a highly motivated candidate with a strong interest in climate science, precipitation extremes, and the challenges of understanding climate changes. A background in atmospheric science, climate science, meteorology, environmental science, or a related discipline is desirable. Good programming skills, particularly in Python, is highly desirable. Given the international nature of the project, the candidate should also demonstrate good scientific communication skills, independence, curiosity, and enthusiasm for collaborative research.

Application link : https://edd-projets.utoulouse.fr/