5 papers
Statistical versus machine learning-based spatial interpolation of post-processed ensemble weather forecasts
Mária Lakatos
Statistical post-processing improves ensemble weather forecasts, but generating calibrated predictions at locations without observations remains challenging. This study compares st…
A Composite-Loss Graph Neural Network for the Multivariate Post-Processing of Ensemble Weather Forecasts
Mária Lakatos
Ensemble forecasting systems have advanced meteorology by providing probabilistic estimates of future states. Nonetheless, systematic biases often persist, making statistical post-…
Statistical post-processing of operational dual-resolution wind-speed ensemble forecasts
Sándor Baran, Mária Lakatos
Weather forecasting presents several challenges, including the chaotic nature of the atmosphere and the high computational demands of numerical weather prediction models. To achiev…
Machine learning-based probabilistic forecasting of solar irradiance in Chile
Sándor Baran, Julio C. Marín, Omar Cuevas +4
By the end of 2023, renewable sources cover 63.4% of the total electric power demand of Chile, and in line with the global trend, photovoltaic (PV) power shows the most dynamic inc…
Enhancing multivariate post-processed visibility predictions utilizing CAMS forecasts
Mária Lakatos, Sándor Baran
In our contemporary era, meteorological weather forecasts increasingly incorporate ensemble predictions of visibility - a parameter of great importance in aviation, maritime naviga…