1 citations · 1 across the 2 of their papers we have counts for
3 papers
HourGlass: A probabilistic data-driven temporal downscaler for global and regional weather forecasting
Magnus Sikora Ingstad, Mariana C. A. Clare, Olav Ersland +16
Many forecast applications require high frequency temporal resolution, yet most state-of-the-art data-driven weather forecasting systems operate at 6-hourly resolution. Although di…
Evaluation of forecasts by a global data-driven weather model with and without probabilistic post-processing at Norwegian stations
John Bjørnar Bremnes, Thomas N. Nipen, Ivar A. Seierstad
During the last two years, tremendous progress in global data-driven weather models trained on numerical weather prediction (NWP) re-analysis data has been made. The most recent mo…
Statistical Postprocessing for Weather Forecasts -- Review, Challenges and Avenues in a Big Data World
Stéphane Vannitsem, John Bjørnar Bremnes, Jonathan Demaeyer +21
Statistical postprocessing techniques are nowadays key components of the forecasting suites in many National Meteorological Services (NMS), with for most of them, the objective of…