Coastal hazards research has long focused on extreme events at the storm scale and, more recently, on long-term effects of climate change, typically projected for 2100 under sea level rise. In contrast, changes at seasonal, multi-year, and multi-decadal scales have received less attention. Yet these timescales are key for deploying effective adaptation strategies, though their prediction remains a challenge. This is mainly because (1) links between coastal hazards and large-scale climate patterns are still poorly understood in many regions, and (2) the predictability of these climate modes at seasonal to decadal scales is limited. This PhD aims to address point (1) using satellite-derived products along the southwest coast of France and, more broadly, the Atlantic coast of Europe, as part of the PSGAR CORALI & PC IRICOT projects (PEPR IRIMA).

Natural climate variability modes (e.g., ENSO, NAO, AMO) explain part of the variability of coastal hazards (shoreline erosion, etc.) and coastal indicators (water level, salinity, wave height, etc.) at these scales. While these links are well known on the Pacific coasts (ENSO; Vos et al., 2023), they are less understood along the Atlantic coast of Europe despite some pioneering work (Jalon-Rojas & Castelle, 2021; Castelle et al., 2022), where several teleconnection patterns coexist. Most studies have focused on winter, although summer hazards also occur, such as marine heatwaves, droughts, and rip currents causing mass rescues and fatal drownings. This PhD will explore links between climate variability and multiple coastal indicators in both winter and summer, leveraging satellite remote sensing that offers unique, long-term, large-scale data (shoreline position, sea surface temperature, sea surface height) from southwest France to the wider Atlantic coast of Europe.

The doctoral candidate will compile existing databases and create new ones documenting multi-decadal coastal evolution from satellite data. Shoreline time series will be extracted using Shoreliner (Bergsma et al., 2024) from Sentinel-2 and Landsat imagery across metropolitan France, along with water level and inter-tidal topography data. Sea surface temperature and height will be obtained from Sentinel-3 and SWOT missions, possibly extended to the TRISHNA thermal mission, as well as reprocessed satellite altimetry based coastal sea level data (Leclercq et al., 2025). Data uncertainties will be assessed using field data and combined with numerical hindcasts (ERA5, MARC, ...) and monitoring datasets (SNO Dynalit, COAST-HF) to produce spatially and temporally continuous time series of key coastal indicators. These will be compared with dominant climate variability modes in the North Atlantic (NAO, EA, SCAND, WEPA, etc.) and beyond (ENSO), with a focus on their influence on wave climatology, especially in the Bay of Biscay. Following Castelle et al. (2017) for winter waves, ad hoc climate indices will be reverse-engineered from the satellite-derived products. The candidate may also develop simple impact models based on combinations of different climate indices.

The PhD student will be co-supervised by Bruno Castelle and Isabel Jalon-Rojas within the METHYS-EPOC team, and will have access to all computing resources at the University of Bordeaux as well as the CNES HPC for the processing of the satellite data. Funding for missions, conferences, and publications is secured. The candidate will also collaborate with EPOC climate scientists studying seasonal-to-decadal predictability of the identified climate modes. The influence of natural variability on coastal risks will be investigated at the European Atlantic scale, strengthening collaborations with institutions such as the University of Plymouth.

Cited references:
Bergsma et al. (2024) Shoreliner: A Sub-Pixel Coastal Waterline Extraction Pipeline for Multi-Spectral Satellite Optical Imagery, https://doi.org/10.3390/rs16152795
Castelle et al. (2017) A new climate index controlling winter wave activity along the Atlantic coast of Europe: The West Europe Pressure Anomaly, https://doi.org/10.1002/2016GL072379
Castelle et al. (2022) Primary drivers of multidecadal spatial and temporal patterns of shoreline change derived from optical satellite imagery, https://doi.org/10.1016/j.geomorph.2022.108360
Jalon-Rojas and Castelle (2021) Climate Control of Multidecadal Variability in River Discharge and Precipitation in Western Europe, https://doi.org/10.3390/w13030257
Leclercq et al. (2025) Spatio-temporal changes in interannual sea level along the world coastlines, https://doi.org/10.1016/j.gloplacha.2025.104972 ;
Vos et al. (2023) Pacific shoreline erosion and accretion patterns controlled by El Niño/Southern Oscillation, https://doi.org/10.1038/s41561-022-01117-8

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For more Information about the topics and the co-financial partner (found by the lab!); contact Directeur de thèse - bruno.castelle@u-bordeaux.fr

Then, prepare a resume, a recent transcript and a reference letter from your M2 supervisor/ engineering school director and you will be ready to apply online before March 13th, 2026 Midnight Paris time!

• Master’s degree in Oceanography, Climate Science, Environmental Science, or a related field 
• Strong foundation in physical oceanography, coastal processes, or atmospheric science
• Background in climate variability and teleconnection patterns  - Technical Skills: 
• Remote sensing and satellite data analysis (e.g., Sentinel, SWOT) 
• Strong programming skills for data processing and analysis (Python, MATLAB). 
• Strong statistical and data analysis skills, including time series analysis -  Attributes: 
• Ability to synthesize large datasets from different sources 
• Good scientific writing and communication skills. 
• Self-motivated, organized, and capable of working independently and collaboratively.