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Journal of Advances in Modeling Earth Systems
Article . 2026 . Peer-reviewed
License: CC BY
Data sources: Crossref
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ZENODO
Article . 2026
License: CC BY
Data sources: ZENODO
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Global Kilometer‐Scale Climate Storylines Using Spectral Nudging

Authors: Amal John; Sebastian Beyer; Marylou Athanase; Antonio Sánchez‐Benítez; Helge F. Goessling; Akil Hossain; Razvan Aguridan; +16 Authors

Global Kilometer‐Scale Climate Storylines Using Spectral Nudging

Abstract

Abstract Effective climate adaptation benefits from detailed, actionable information on how specific extreme events are influenced by climate change. Here we present the first global, kilometer‐scale coupled modeling framework that enables counterfactual reconstructions of recent weather events, including extremes, in different climates. The system is built on the IFS–FESOM model and applies scale‐selective spectral nudging of the large‐scale atmospheric circulation to ERA5 while allowing atmospheric small‐scale dynamics and thermodynamic processes as well as the land surface, ocean, and sea ice to evolve freely across contrasting climate backgrounds. This enables the replay of recent events across different climate states, including the 1950s, present‐day conditions, and a +2 K warmer climate. We demonstrate the system's skill in reproducing the observed variability on daily and longer timescales during the period 2017–2024, particularly in the extratropics. Furthermore, we evaluate its performance using high‐quality observations, including data from the MOSAiC expedition. We further present climate change storylines for a European heatwave in July 2019 and a major European flooding event in September 2024, Storm Boris. We thereby demonstrate how the use of kilometer‐scale resolution captures local‐scale intensification with local granularity, including details missed by coarser models. This framework forms a core operational component of the EU's Destination Earth Climate Digital Twin, enabling scalable, high‐resolution, circulation‐constrained climate storylines for science and decision‐making.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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