Ensemble approach to weather forecasting

Using Weather Ensemble Predictions in Electricity Demand Forecasting

Weather forecasts are an important input to many electricity demand forecasting models. This study investigates the use of weather ensemble predictions in electricity demand forecasting for lead times from one to 10 days ahead. A weather ensemble prediction consists of 51 scenarios for a weather variable. We use these scenarios to produce 51 scenarios for the weather-related component of electr...

A new approach to wind turbine power generation forecasting, using weather radar data based on Hidden Markov Model

The wind is one of the most important and affecting phenomena and is known as one of the significant clean resources of energy. Apart from other atmospheric parameters, the wind has complex behavior and intermittent characteristics. Local phenomena can be accompanied by the wind, which is strong, non-predicted, and damaging.  Weather radars are capable of detecting and displaying storm-related ...

Ensemble forecasting

Numerical weather prediction models as well as the atmosphere itself can be viewed as nonlinear dynamical systems in which the evolution depends sensitively on the initial conditions. The fact that estimates of the current state are inaccurate and that numerical models have inadequacies, leads to forecast errors that grow with increasing forecast lead time. The growth of errors depends on the f...

Long-range Weather Forecasting

Forecasting Space Weather

Forecasting space weather events presents the ultimate challenge to a space physics model. Not only should physical constraints be satisfied, but also practical issues such as timeliness, accuracy, and reliability must be adequately addressed. To address these needs, modern space weather forecasters and users rely on a great variety of space weather models, ranging from simple regressions and e...