Reliable and accurate probabilistic forecasting of wind speed is of vital importance for the
utilization of wind energy and operation of power systems. In this paper, a probabilistic …

Abstract Numerical Weather Prediction (NWP) is the key to precise wind power forecasting
(WPF), which can be enhanced by the NWP correction and scenario partition techniques …

This is the first of two papers that document the creation of the New European Wind Atlas
(NEWA). It describes the sensitivity analysis and evaluation procedures that formed the …

The most mature aspect of applying artificial intelligence (AI)/machine learning (ML) to
problems in the atmospheric sciences is likely post-processing of model output. This article …

Wind energy requires accurate forecasts for adequate integration into the electric grid
system. In addition, global atmospheric models are not able to simulate local winds in …

In water resources applications (eg, streamflow, rainfall‐runoff, urban water demand [UWD],
etc.), ensemble member selection and ensemble member weighting are two difficult yet …

Physics parameterizations in the Weather Research and Forecasting (WRF) Model are
systematically varied to investigate precipitation forecast performance over the complex …

The Weather Research and Forecasting (WRF) model has been successfully used in
weather prediction, but its ability to simulate precipitation over areas with complex …

The ability of a stochastically perturbed parameterization (SPP) approach to represent
uncertainties in the model component of the Canadian Global Ensemble Prediction System …

Bayesian model averaging (BMA) probability quantitative precipitation forecast (PQPF)
models were established by calibrating their parameters using 1–7-day ensemble forecasts …