Members in ensemble forecasts differ due to the representations of initial uncertainties and
model uncertainties. The inclusion of stochastic schemes to represent model uncertainties …

Although the partial differential equations that describe the physical climate system are
deterministic, there is an important reason why the computational representations of these …

This paper has been written to mark 25 years of operational medium‐range ensemble
forecasting. The origins of the ECMWF Ensemble Prediction System are outlined, including …

HarmonEPS is the limited-area, short-range, convection-permitting ensemble prediction
system developed and maintained by the HIRLAM consortium as part of the shared ALADIN …

Abstract The Stochastically Perturbed Parametrisations scheme (SPP) represents model
uncertainty in numerical weather prediction by introducing stochastic perturbations into the …

Kilometer-scale models allow for an explicit simulation of deep convective overturning but
many subgrid processes that are crucial for convective initiation are still poorly represented …

The 2021 Nobel prize for physics was awarded to two climate scientists, Syukuro Manabe
and Klaus Hasselmann, and the physicist Giorgio Parisi. While at first sight the work of Parisi …

High-resolution, limited-area forecasting is strongly affected by errors in the initial
atmospheric state, lateral boundary conditions (LBCs), and physical parameterizations used …

Stochastic parametrisations can be used in weather and climate models to improve the
representation of unpredictable unresolved processes. When compared with a deterministic …

While chaos ensures that probabilistic weather forecasts cannot always be “sharp,” it is
important for users and developers that they are reliable. For example, they should not be …