output
20102025
most citedStochastic Parameterization: Towards a new view of Weather and Climate Models

431 citations

33 papers

physics.ao-ph2025

Intercomparison of a High-Resolution Regional Climate Model Ensemble for Catchment-Scale Water Cycle Processes under Human Influence

J. L. Roque, F. Da Silva Lopes, J. A. Giles +8

Understanding regional hydroclimatic variability and its drivers is essential for anticipating the impacts of climate change on water resources and sustainability. Yet, considerabl…

physics.ao-ph2025★ 1 cited

The Impact of Non-Orographic Gravity Waves on Transport and Mixing: Effects of Oblique Propagation and Coupling to Turbulence

Tridib Banerjee, Sebastian Borchert, Young-Ha Kim +7

Gravity waves (GWs) are a fundamental driver of circulation, tracer transport, and mixing in the middle and upper atmosphere, but their treatment in global circulation models remai…

physics.ins-det2025

The QTF-Backbone: Proposal for a Nationwide Optical Fibre Backbone in Germany for Quantum Technology and Time and Frequency Metrology

Tara Cubel Liebisch, Peter Kaufmann, Harald Schnatz +166

The recent breakthroughs in the distribution of quantum information and high-precision time and frequency (T&F) signals over long-haul optical fibre networks have transformative po…

cs.ET2025★ 1 cited

Status and Future Prospects of the Standardization Framework Industry 4.0: A European Perspective

Olga Meyer, Marvin Boell, Christoph Legat

The rapid development of Industry 4.0 technologies requires robust and comprehensive standardization to ensure interoperability, safety and efficiency in the Industry of the Future…

physics.flu-dyn2024★ 4 cited

Transition to turbulence in the wide-gap spherical Couette system

Ankit Barik, Santiago A. Triana, Michael Hoff +1

The spherical Couette system consists of two differentially rotating concentric spheres with a fluid filled in between. We study a regime where the outer sphere is rotating rapidly…

stat.ME2024★ 2 cited

Generating Synthetic Rainfall Fields by R-vine Copulas Applied to Seamless Probabilistic Predictions

Peter Schaumann, Martin Rempel, Ulrich Blahak +1

Many post-processing methods improve forecasts at individual locations but remove their correlation structure, which is crucial for predicting larger-scale events like total precip…