EMS Annual Meeting Abstracts
Vol. 23, EMS2026-804, 2026, updated on 22 Jun 2026
https://doi.org/10.5194/ems2026-804
EMS Annual Meeting 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Tuesday, 08 Sep, 12:30–12:45 (CEST)| Room Media Arena (Media Plaza)
Bridging Seasonal Climate Predictions and Impact Models for Operational Risk Assessment in Labor Markets
Tobias Geiger1, Fabiana Castino1, Peter Paul Dimke2, Alex Stomper2, and Frank Kreienkamp1
Tobias Geiger et al.
  • 1Regional Climate Office Potsdam, Deutscher Wetterdienst (DWD), Potsdam, Germany
  • 2Institute of Financial Economics, Humboldt University, Berlin, Germany

The landscape of disaster risk management is undergoing a significant transformation, driven by two increasingly complementary approaches: Impact-Based Forecasting (IBF) and seasonal forecasts. While traditional forecasting focuses solely on weather predictions, IBF integrates hazard information—such as extreme temperature patterns—with socioeconomic exposure and vulnerability information, enabling quantitative risk assessments in areas as diverse as public health and infrastructure resilience. On the other side, seasonal forecasts spanning several months provide stakeholders with probabilistic predictions that enable forward-thinking adaptation planning well before conditions materialize.

A three-step conceptual framework illustrates the progression from prediction to actionable advice: 1) seasonal climate prediction, 2) impact modeling, and 3) actionable impact-based forecasting. While significant advances have been made in the first two steps separately, a critical gap remains in operational systems that systematically connect seasonal forecasts with impact models to enable the third step. To address this challenge, we utilize DWD’s operationally available seasonal heat predictions to develop heat-related impact-based forecasting prototypes. In particular, we showcase how the temperature-dependence of the demand for German short-work labor compensation (Kurzarbeitergeld) can be translated into regionally-resolved impact forecasts. We further discuss the forecast’s prediction skill as an important contribution for the relevance of such a service. In summary, this work helps bridge the strategic gap between traditional seasonal forecasts and impact-oriented services, contributing to the development of operational, reproducible workflows that connect probabilistic climate forecasts to warning systems and decision-making processes. This research received funding by the Federal Ministry of Research, Technology and Space (BMFTR) via the funding line “climate protection and finance”.

How to cite: Geiger, T., Castino, F., Dimke, P. P., Stomper, A., and Kreienkamp, F.: Bridging Seasonal Climate Predictions and Impact Models for Operational Risk Assessment in Labor Markets, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-804, https://doi.org/10.5194/ems2026-804, 2026.