7 citations · 9 across the 2 of their papers we have counts for
2 papers
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…
astro-ph.SR2023★ 7 cited
A study of the capabilities for inferring atmospheric information from high-spatial-resolution simulations
C. Quintero Noda, E. Khomenko, M. Collados +8
In this work, we study the accuracy that can be achieved when inferring the atmospheric information from realistic numerical magneto-hydrodynamic simulations that reproduce the spa…