From Seasonal Forecasts to Impact-Based Insights: The Copernicus Forecast Module for Operational Climate Risk Analysis

The increasing frequency and severity of weather and climate extremes have intensified the demand for risk-oriented forecasting frameworks capable of informing decision-making processes across sectors. While seasonal climate predictions offer valuable lead time for preparedness and planning, their operational integration into impact-based risk assessments remains limited. Impact-based forecasting (IBF), which quantifies risk by combining hazard metrics with information on exposure and vulnerability, has emerged as a promising approach to address this need. However, systematic and scalable methods to link seasonal forecasts with IBF frameworks remain underdeveloped.

To address this challenge, we present the Copernicus Forecast Module within CLIMADA, an open-source platform for climate risk analysis. This module provides an operational bridge between seasonal climate predictions and impact assessment by automating the entire workflow, from data acquisition through to impact and risk estimation. By integrating with the Copernicus Climate Data Store (CDS), it enables the systematic processing of seasonal forecasts into standardized climate hazard objects, focusing particularly on heat-related indices such as heatwave intensity and tropical nights.

The module’s design prioritizes stakeholder needs through a flexible and scalable architecture that accommodates various data sources and supports the customization of risk assessments to specific regional contexts and user requirements. Its automated workflow significantly reduces technical barriers between climate predictions and impact analysis, allowing civil protection agencies, urban planners, and other stakeholders to focus on applying sector-specific impact models and developing targeted adaptation strategies.

As part of our presentation, we will showcase the module and demonstrate live impact estimations for attendees, providing a practical illustration of how to move from seasonal forecast data to impact assessment. This hands-on example aims to highlight the module's potential to enhance early warning systems, inform climate adaptation planning, and support anticipatory action.