Projektbeschreibung
Ein neues Supermodell für die Klimavorhersage
Dienste zur Klimavorhersage sind unabdingbar, um die Bevölkerung auf mögliche Ereignisse vorzubereiten und in Bereitschaft zu halten. Noch entscheidender sind diese Dienste im Hinblick auf die Vermeidung möglicher Naturkatastrophen. Allerdings werden die derzeitigen Systeme durch systematische Fehler in den Modellen beeinträchtigt, was ihre Fähigkeit zur effizienten Vorhersage von Klimaänderungen deutlich einschränkt und den Prozess sehr kostspielig macht. Das vom Europäischen Forschungsrat finanzierte Projekt TOSCP soll eine Lösung bieten. Es wird das im Rahmen des ebenfalls vom Europäischen Forschungsrat finanzierten Projekts STERCP entwickelte Supermodell für eine effizientere und kostengünstigere Klimavorhersage nutzen. Dabei kommen neuartige Daten- und Assimilierungssysteme zum Einsatz, um den Dienst zu optimieren.
Ziel
TOSCP will proof-of-concept a radically new approach to climate prediction based on supermodelling. Climate prediction promises reliable information on climate and its extremes for the coming seasons and years. This information is critical to providing climate services that are needed to build a resilient and sustainable society. Unfortunately, predicting climate in the extra-tropics remains a major challenge. Model systematic error is the major limitation. In the North Atlantic-European sector it leads to the strong under representation of the predictable dynamics, compared to unpredictable atmospheric weather patterns. The current approach to account for such errors is to perform a vast number of independent simulations with different models. This is computationally expensive and impractical in an operational context. The supermodel approach developed in the ERC-STERCP project is aptly suited to improve climate prediction. A supermodel combines a set of different models in runtime so that the individual model errors compensate so as to produce a superior model. The approach is extremely effective in mitigating long-standing model errors, and can control the ratio between predictable and unpredictable dynamics. TOSCP will reconfigure a supermodel developed in the STERCP project for climate prediction. The supermodel is based on three state-of-the-art climate models. We will develop new ensemble generation and data assimilation schemes. We aim to demonstrate that supermodel climate predictions greatly outperform the standard approach to climate prediction that is currently used for climate services. Dialogue with users and providers of climate
services will ensure the development of an optimal configuration of the new prediction system and its use in operational climate services. This will set the stage for the wider exploitation of supermodel climate prediction, leading to improved climate services for the benefit of society.
Programm/Programme
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Thema/Themen
Aufforderung zur Vorschlagseinreichung
(öffnet in neuem Fenster) ERC-2022-POC2
Andere Projekte für diesen Aufruf anzeigenFinanzierungsplan
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsGastgebende Einrichtung
5020 Bergen
Norwegen