arXiv subjects

Urs Beyerle

Publications and source records attributed to Urs Beyerle.

3 recordsLinked to original sources

arXiv2026

Statistical Noise and Missing Forcing Limit Estimates of Earth's Feedback from Prescribed Sea-Surface Temperature Simulations

Earth's feedback parameter measures how the Earth system responds to forcing and is inversely proportional to climate sensitivity. Sea-surface temperature (SST) patterns can modulate the value of the feedback parameter. Differences between observed and simulated SSTs have raised the question how the observed SSTs evolution impacts the global feedback. The standard method for estimating this effect uses observed SSTs prescribed to an atmospheric model with fixed pre-industrial atmospheric forcing. This method makes two assumptions: first, that the observed SSTs capture all relevant effects from the forcing, so that prescribing a time-varying forcing is unnecessary; second, that the temporal variations in the feedback parameter are driven by the evolving SST pattern and can be estimated via moving-window regressions. We test these assumptions by running controlled experiments in which SSTs from fully-coupled historical simulations are prescribed to an atmospheric model. We find that the prescribed-SST experiments fail to capture the coupled feedback evolution. This is explained by two effects: First, the absence of prescribed atmospheric forcing, and second, statistical noise arising from the computation of moving-window regressions. We find no evidence of any significant relationship between evolving SST patterns and changes in the feedback time series in a 4000-year pre-industrial control simulation. Any trends in the feedback parameter detected on timescales shorter than ~100 years are indistinguishable from statistical noise, making their attribution to the evolving SST pattern extremely difficult. Our results imply that prescribed SST simulations offer limited potential for inferring temporal changes in Earth's parameter over the observational period.

physics.ao-ph↗

arXiv2026

Omega-blocks with spatially compounding extremes over Europe are highly sensitive to remote atmospheric drivers

Omega-blocks can trigger spatially compounding heat-precipitation extremes with severe societal impacts, as seen in September 2023 when a heatwave over France coincided with devastating floods in the Iberian Peninsula and Greece. Although blocking in general has been linked to moist processes in upstream warm conveyor belts (WCBs), it has remained unexplored whether and how upstream WCB activity influences the evolution of omega-blocks and downstream flood-heat-flood impacts. Here, we show that already five days ahead, small differences in the upstream evolution - particularly in WCB outflow regions - distinguish cases that later produce extreme compound events over Europe from weaker ones, even though their large-scale anomalies initially appear similar. We illustrate the distinct evolution in remote locations by analyzing storylines simulated in a fully coupled climate model. Using ensemble boosting, we generate hundreds of physically plausible simulations of omega-prone situations. Lagrangian air parcel tracking reveals that variations in WCB outflow areas can explain differences in upstream precursors and downstream effects over Europe. Our results highlight ensemble boosting as a powerful approach to systematically track dynamical differences along model-based event storylines, important for understanding and anticipating compound extremes striking multiple regions simultaneously.

physics.ao-ph↗

arXiv2025

Climate2Energy: a framework to consistently include climate change into energy system modeling

Supply and demand in future energy systems depend on the weather. We therefore need to quantify how climate change and variability impact energy systems. Here, we present Climate2Energy (C2E), a framework to consistently convert climate model outputs into energy system model inputs, covering all relevant types of renewable generation and demand for heating and cooling. C2E performs bias correction, uses established open-source tools where possible, and provides outputs tailored to energy system models. Moreover, C2E introduces a new hydropower model based on river discharge. We analyze dedicated hourly CESM2 Climate Model Simulations under the SSP3-7.0 scenario in Europe, covering climate variability through multiple realizations. We find large reductions in heating demand (-10% to -50%) and Southern European hydropower potentials (-10% to -40%) and increases in cooling demand (>100%). Based on stochastic optimizations with AnyMOD, we confirm that energy systems are highly sensitive to climate conditions, particularly on the demand side.

physics.soc-ph↗