24 citations · 62 across the 9 of their papers we have counts for
9 papers
Long-term foehn reconstruction combining unsupervised and supervised learning
Reto Stauffer, Achim Zeileis, Georg J. Mayr
Foehn winds, characterized by abrupt temperature increases and wind speed changes, significantly impact regions on the leeward side of mountain ranges, e.g., by spreading wildfires…
Spatio-seasonal risk assessment of upward lightning at tall objects using meteorological reanalysis data
Isabell Stucke, Deborah Morgenstern, Georg J. Mayr +5
This study investigates lightning at tall objects and evaluates the risk of upward lightning (UL) over the eastern Alps and its surrounding areas. While uncommon, UL poses a threat…
Upward lightning at wind turbines: Risk assessment from larger-scale meteorology
Isabell Stucke, Deborah Morgenstern, Thorsten Simon +5
Upward lightning (UL) has become an increasingly important threat to wind turbines as ever more of them are being installed for renewably producing electricity. The taller the wind…
Identifying Lightning Processes in ERA5 Soundings with Deep Learning
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr +1
Atmospheric environments favorable for lightning and convection are commonly represented by proxies or parameterizations based on expert knowledge such as CAPE, wind shears, charge…
Daily-Resolved Lightning Climatology of the Eastern Alpine Region at the Kilometer Scale
Thorsten Simon, Georg J. Mayr
Lightning flashes are rare albeit hazardous events. Despite this scarcity, generalized additive models (GAMs) succeed in producing a climatology of lightning occurrence for the eas…
Upward Lightning at the Gaisberg Tower: Initiation Mechanism and Flash Type and the Atmospheric Influence
Isabell Stucke, Deborah Morgenstern, Gerhard Diendorfer +5
Upward lightning is much rarer than downward lightning and requires tall (~m) structures to initiate. It may be either triggered by other lightning discharges or completely s…
Cholesky-based multivariate Gaussian regression
Thomas Muschinski, Georg J. Mayr, Thorsten Simon +2
Distributional regression is extended to Gaussian response vectors of dimension greater than two by parameterizing the covariance matrix of the response distribution using the…
Circular Regression Trees and Forests with an Application to Probabilistic Wind Direction Forecasting
Moritz N. Lang, Lisa Schlosser, Torsten Hothorn +3
While circular data occur in a wide range of scientific fields, the methodology for distributional modeling and probabilistic forecasting of circular response variables is rather l…
Bivariate Gaussian models for wind vectors in a distributional regression framework
Moritz N. Lang, Georg J. Mayr, Reto Stauffer +1
A new probabilistic post-processing method for wind vectors is presented in a distributional regression framework employing the bivariate Gaussian distribution. In contrast to prev…