Posters
Come meet the poster presenters to ask them questions and discuss their work
We would like to invite you to come and see the posters at our upcoming conference. The posters will showcase a diverse range of research topics, and will give delegates an opportunity to engage with the authors and learn more about their work. Whether you are a seasoned researcher or simply curious about the latest developments in your field, we believe that the posters will offer something of interest to everyone. So please join us at the conference and take advantage of this opportunity to learn and engage with your peers in industry and the academic community.
PO398: Advancing wind energy services through operational km-scale climate projections
Francesc Roura-Adserias, Research engineer, Barcelona Supercomputing Center
Abstract
Amid climate change, reliable climate information specifically tailored to the renewable energy sector is essential for the advancement of the future low-carbon economy. Local climate insights at the global scale are key for supporting informed decisions, such as identifying optimal sites for renewable deployment to ensure efficient long-term operation. Nonetheless, state-of-the-art climate data sources, such as CMIP or CORDEX, remain constrained by long update cycles, relatively coarse spatial resolutions and a lack of outputs specifically tailored to support the adaptation needs of climate-dependent sectors. Within the Climate Adaptation Digital Twin (Climate DT) from the Destination Earth (DestinE) initiative, a suite of km-scale atmosphere-ocean coupled simulations has been produced using three state-of-the-art global climate models (GCMs). The Climate DT aims to operationalise the production of climate projections, prioritising accessibility, interactivity and timely availability of the data (i.e., sub-annual updates), while targeting specific climate-dependent sectors. Furthermore, the enhanced resolution of km-scale simulations allows to obtain local estimates of the interannual variability and trends of near-term (i.e., next 30 years) wind resources, removing the reliance on extrapolated trends from historical data. Km-scale simulations provide a notably improved representation of key wind energy metrics in regions with complex topography. Evaluation against global reanalysis products (e.g., ERA5) shows that km-scale simulations capture wind spatiotemporal variability effectively, with reduced biases compared to their coarse-resolution counterparts. We present a novel open-sourced Python tool, Energy Indicators, co-developed with stakeholders from the wind energy sector. It provides essential metrics for the wind energy sector at an unprecedented (5-10 km) horizontal resolution. These include, among others, high and low wind events, capacity factors for various turbine types, and demand metrics such as heating and cooling degree days.
No recording available for this poster.
