CLINT aims to create an Artificial Intelligence framework employing Machine Learning techniques to analyze extensive climate datasets, thereby enhancing Climate Science capabilities in detecting, understanding, and attributing Extreme Events (EEs). These events encompass tropical cyclones, heatwaves, warm nights, droughts, and floods. The CLINT AI framework goes beyond mere analysis by also evaluating the impacts of EEs on various socio-economic sectors. This assessment spans historical, forecasted, and projected climate conditions, addressing diverse spatial scales from regional to local levels.
The innovation lies in developing specialized AI-enhanced Climate Services tailored to specific sectors. These services not only quantify the effects of EEs but also provide insights into their implications for different industries. The ultimate goal is to operationalize these services into Web Processing Services adhering to the latest open data and software standards outlined by Climate Services Information Systems. Additionally, a Demonstrator will be created, serving as a practical tool to facilitate the integration of project outcomes into the workflows of both public and private entities. This approach aims to advance research and the development of Climate Services.
By integrating advanced AI methodologies, CLINT endeavors to significantly improve the efficiency of Climate Services. The framework's adaptability to different spatial scales, comprehensive analysis of EEs, and sector-specific applications contribute to a more nuanced understanding of climate dynamics. Through the operationalization of services into accessible formats, CLINT aims to foster wider adoption by stakeholders, fostering collaboration between research institutions and entities involved in Climate Services development.
