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African Easterly Waves (AEWs) are prominent synoptic-scale weather systems of the West African Monsoon region and tropical Atlantic during boreal summer. These organized systems propagate from east to west and exert a substantial influence on the weather patterns in the area. AEWs are the primary source of heavy precipitation during the summer months in the region and serve as precursors for tropical cyclones. An investigation of AEWs from a potential vorticity (PV) standpoint offers a more comprehensive understanding of the dynamics of these meteorological systems. PV analysis is a valuable diagnostic tool to study the behavior of atmospheric waves and the interactions between convection and broader dynamical features due to its conservative properties. By examining AEWs through the lens of PV in a 3-D environment, key features of the waves and their correlation can be studied.This study presents a novel approach to the identification and tracking of 3-D PV features that are associated with AEWs. The identification algorithm has been motivated and developed supported by 3-D visual analysis tools. The identified structures and wave tracks are assigned low-dimensional descriptions, such as best-fit geometry, life-cycle stage, phase, and additional meteorological measures. These are generated over multiple decades to compute a climatology of these features. These descriptions provide a succinct and comprehensive data set that can be correlated with AEW-related tropical rainfall and tropical cyclone genesis., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

How well can we predict the weather? Questions about the limits of predictability pose an intriguing and societally highly relevant problem. The limit of predictability is directly related to the growth of forecast errors in scale and amplitude. Following seminal work by Ed Lorenz in the late 1960’s, many studies have taken a broad-brush view on the dynamics that underly the growth of forecast errors, namely that scale interactions occur as if the atmosphere behaved like homogenous and isotropic turbulence. Applying a quantitative potential-vorticity framework, new insight into the growth of forecast errors in the midlatitudes is gained. In a conceptual, multi-stage error-growth model, upper-tropospheric divergent outflow is identified as the most efficient process that projects uncertainties in the representation of moist processes onto the tropopause dynamics. Nonlinearities in the Rossby wave dynamics then dominates further growth, while the direct role of baroclinic instability is small, on average, in contrast to widely held previous ideas. Our improved mechanistic understanding of error growth finally suggests an avenue to identify forecasts situations in that the limits of predictability are already reached, i.e., in that no further improvements to state-of-the-art forecast systems would yield a measurable increase in forecast skill. Informing model evaluation about the closeness of forecasts to the intrinsic limit may be helpful in future strategies to examine model error., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Training agents to learn efficiently in multi-agent environments can benefit from the explicit modelling of other agent's beliefs, especially in complex limited-information games such as the Hanabi card game. However, generalization is also highly relevant to performance in these games, though model comparisons at large training timescales can be difficult. In this work, we address this by introducing a novel model trained using a sleep metaphor on a reduced complexity version of the Hanabi game. This sleep metaphor consists an altered training regiment, as well as an information-theoretic constraint on the agent's policy. Results from experimentation demonstrate improved performance through this sleep-metaphor method, and provide a promising motivation for using similar techniques in more complex methods that incorporate explicit models of other agent's beliefs.

Objectives: The Hamburg Open Online University (HOOU) [[link:https://www.hoou.de/projects/typ-2-diabetes-anonymer-risikotest*https://www.hoou.de/projects/typ-2-diabetes-anonymer-risikotest]] is a joint project of six publicly funded Hamburg[for full text, please go to the a.m. URL], Jahrestagung der Gesellschaft für Medizinische Ausbildung (GMA)