4 papers · 1 filter
Quantile Regression, Variational Autoencoders, and Diffusion Models for Uncertainty Quantification: A Spatial Analysis of Sub-seasonal Wind Speed Prediction
Ganglin Tian, Anastase Alexandre Charantonis, Camille Le Coz +2
This study aims to improve the spatial representation of uncertainties when regressing surface wind speeds from large-scale atmospheric predictors for sub-seasonal forecasting. Sub…
Improving sub-seasonal wind-speed forecasts in Europe with a non-linear model
Ganglin Tian, Camille Le Coz, Anastase Alexandre Charantonis +3
Sub-seasonal wind speed forecasts provide valuable guidance for wind power system planning and operations, yet the forecast skills of surface winds decrease sharply after two weeks…
Generating ensembles of spatially-coherent in-situ forecasts using flow matching
David Landry, Claire Monteleoni, Anastase Charantonis
We propose a machine-learning-based methodology for in-situ weather forecast postprocessing that is both spatially coherent and multivariate. Compared to previous work, our Flow MA…
ORCAst: Operational High-Resolution Current Forecasts
Pierre Garcia, Inès Larroche, Amélie Pesnec +6
We present ORCAst, a multi-stage, multi-arm network for Operational high-Resolution Current forecAsts over one week. Producing real-time nowcasts and forecasts of ocean surface cur…