| Project Detail |
Charting the climate-induced coastal shift
As the climate emergency looms, the Intergovernmental Panel on Climate Change’s Sixth Assessment Report underscores the vulnerability of coastal areas. While progress has been made in quantifying climate-related coastal risks, uncertainties persist. With the support of the Marie Sklodowska-Curie Actions programme, the TransClima project seeks to identify transitional climate regions and neo-climate regions as climate patterns shift, with a focus on the SSP5-8.5 scenario. The project will use cutting-edge machine learning techniques to create a probabilistic framework for waves and sea levels in the face of extra-tropical and tropical cyclones. By prioritising socio-economic and ecological factors, it aims to offer recommendations for coastal risk assessment in these evolving regions. Overall, the project redefines climate risk assessment by offering a fresh perspective.
The most recent report of the IPCC-AR6 indicates that coastal areas are at risk under the climate emergency that the planet faces, and now more than ever, adaptation is an urgent need. Although remarkable efforts have been made to quantify future changes in the primary climate-related drivers of coastal flooding and erosion risk (waves, sea level rise, and storm surges), these are not yet fully understood. Due to the displacement poleward of Tropical and Extratropical Cyclones in a changing climate, the ocean waves and total sea levels that they induce could hit regions they did not affect before. For the purposes of this proposal, these new regions that will be exposed to new weather conditions are called Transitional Climate Regions (TCR) and Neo-Climate Regions (NCR). Even though these transitional climate regions have been highlighted as critical for ecosystem conservation, they are far from being identified and not even close to becoming part of the coastal risk agenda. This project aims to detect TCR and NCR in the projected scenario SSP5-8.5 by proposing a probabilistic framework of waves and total sea level, under prevailing and extreme conditions (extratropical and tropical cyclones) in coastal areas. These regions are prioritized under socioeconomic and ecological criteria for establishing recommendations. The project, instead of proposing new datasets, proposes a cutting-edge spatiotemporal exploration of coastal hazards by using Machine Learning approaches and a new mindset for climate risk. Once climate and exposure regions are identified, the developing guidelines for coastal risk assessment in these areas will be established. |
