#xfc — Public Fediverse posts

#StoreDot: #Polestar lädt Prototyp in 10 Minuten auf

https://www.golem.de/news/storedot-polestar-laedt-prototyp-in-10-minuten-auf-2404-184678.html

#Elektromobilität #eAuto #XFC

Title: Postprocessing of Ensemble Weather Forecasts Using Permutation-invariant Neural Networks.

Statistical postprocessing is used to translate ensembles of raw numerical
weather forecasts into reliable probabilistic forecast distributions. In this
study, we examine the use of permutation-invariant neural networks for this
task. In contrast to previous approache [...]

Authors: Kevin Höhlein, Benedikt Schulz, Rüdiger Westermann, Sebastian Lerch

Link: http://arxiv.org/abs/2309.04452

Title: Towards replacing precipitation ensemble predictions systems using machine learning.

Precipitation forecasts are less accurate compared to other meteorological
fields because several key processes affecting precipitation distribution and
intensity occur below the resolved scale of global weather prediction models.
This requires to use higher resolution simulations. To generate an uncertainty
predictio [...]

Authors: Rüdiger Brecht, Alex Bihlo

Link: http://arxiv.org/abs/2304.10251

Title: M-ENIAC: A machine learning recreation of the first successful numerical weather forecasts.

In 1950 the first successful numerical weather forecast was obtained by
solving the barotropic vorticity equation using the Electronic Numerical
Integrator and Computer (ENIAC), which marked the beginning of the age of
numerical weather prediction. Here, we ask the question of how these numerical
forecasts woul [...]

Authors: Rüdiger Brecht, Alex Bihlo

Link: http://arxiv.org/abs/2304.09070

Title: Potential quantum advantage for simulation of fluid dynamics.

Numerical simulation of turbulent fluid dynamics needs to either parameterize
turbulence-which introduces large uncertainties-or explicitly resolve the
smallest scales-which is prohibitively expensive. Here we provide evidence
through analytic bound [...]

Authors: Xiangyu Li, Xiaolong Yin, Nathan Wiebe, Jaehun Chun, Gregory K. Schenter, Margaret S. Cheung, Johannes Mülmenstädt

Link: http://arxiv.org/abs/2303.16550

Title: Computing the ensemble spread from deterministic weather predictions using conditional generative adversarial networks.

Ensemble prediction systems are an invaluable tool for weather forecasting.
Practically, ensemble predictions are obtained by running several perturbations
of the deterministic control forecast. However, ensemble prediction is
associated with a high computational cost and often invol [...]

Authors: Rüdiger Brecht, Alex Bihlo

Link: http://arxiv.org/abs/2205.09182

Title: Transitions of zonal flows in a two-layer quasi-geostrophic ocean model.

We consider a 2-layer quasi-geostrophic ocean model where the upper layer is
forced by a steady Kolmogorov wind stress in a periodic channel domain, which
allows to mathematically study the nonlinear development of the resulting flow.
The model supports a steady parallel shear flow as a [...]

Authors: Mickael D. Chekroun, Henk Dijkstra, Taylan Şengül, Shouhong Wang

Link: http://arxiv.org/abs/2110.05195

Title: Visualization of Model Parameter Sensitivity along Trajectories in Numerical Weather Predictions.

Numerical weather prediction models rely on parameterizations for
subgrid-scale processes, e.g., for cloud microphysics. These parameterizations
are a well-known source of uncertainty in weather forecasts that can be
quantified [...]

Authors: Christoph Neuhauser, Maicon Hieronymus, Michael Kern, Marc Rautenhaus, Annika Oertel, Rüdiger Westermann

Link: http://arxiv.org/abs/2205.02268

Title: Perspectives on the importance of complex systems in understanding ourclimate and climate change -- The Nobel Prize in Physics 2021.

The Nobel Prize in Physics 2021 was awarded to Syukuro Manabe, Klaus
Hasselmann, and Giorgio Parisi for their 'groundbreaking contributions to our
understanding of complex systems' including major advances in the understanding [...]

Authors: Shraddha Gupta, Nikolaos Mastrantonas, Cristina Masoller, Jürgen Kurths

Link: http://arxiv.org/abs/2203.03331

Title: ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models.

Numerical simulations of Earth's weather and climate require substantial
amounts of computation. This has led to a growing interest in replacing
subroutines that explicitly compute physical processes with approximate machine
learning (ML) [...]

Authors: Salva Rühling Cachay, Venkatesh Ramesh, Jason N. S. Cole, Howard Barker, David Rolnick

Link: http://arxiv.org/abs/2111.14671

Title: Definition, detection, and tracking of persistent structures in atmospheric flows.

Long-lived flow patterns in the atmosphere such as weather fronts,
mid-latitude blockings or tropical cyclones often induce extreme weather
conditions. As [...]

Authors: Johannes von Lindheim, Abhishek Harikrishnan, Tom Dörffel, Rupert Klein, Péter Koltai, Natalia Mikula, Annette Müller, Peter Névir, George Pacey, Robert Polzin, Nikki Vercauteren

Link: http://arxiv.org/abs/2111.13645

Title: Identifying the atmospheric drivers of drought and heat using a smoothed deep learning approach.

Europe was hit by several, disastrous heat and drought events in recent
summers. Besides thermodynamic influences, such hot and dry extremes are driven
by certain atmospheric situations including anticyclonic conditions. Effects of
climate change on atmospheric circulations ar [...]

Authors: Magdalena Mittermeier, Maximilian Weigert, David Rügamer

Link: http://arxiv.org/abs/2111.05303

Title: The climatic interdependence of extreme-rainfall events around the globe.

The identification of regions of similar climatological behavior can be
utilized for the discovery of spatial relationships over long-range scales,
including teleconnections. In this regard, the global picture of the
interdependence patterns of extreme rainfall events (EREs) still needs to be
further explored. To [...]

Authors: Zhen Su, Henning Meyerhenke, Jürgen Kurths

Link: http://arxiv.org/abs/2111.03471