4 papers
AIFS-SUBS: Extending Data-Driven Forecasting to Sub-Seasonal Timescales
Jakob Schloer, Steffen Tietsche, Christopher D. Roberts +6
Data-driven models now rival numerical weather prediction in the medium range, but extending them to sub-seasonal lead times raises challenges absent at shorter horizons. Errors ac…
Ensemble size effects on conditional reliability estimates: slope attenuation bias and correction methods
Jonas Spaeth, Christopher D. Roberts
The goal of ensemble forecasting is to maximise sharpness subject to reliability. Marginal reliability means that, over all cases, the ensemble is statistically consistent with rea…
Ensemble-size-dependence of deep-learning post-processing methods that minimize an (un)fair score: motivating examples and a proof-of-concept solution
Christopher David Roberts
Fair scores reward ensemble forecast members that behave like samples from the same distribution as the verifying observations. They are therefore an attractive choice as loss func…
AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score
Simon Lang, Mihai Alexe, Mariana C. A. Clare +15
Over the last three decades, ensemble forecasts have become an integral part of forecasting the weather. They provide users with more complete information than single forecasts as…