National security and energy agencies, private businesses such as wind turbine manufacturers and other related organizations need timely, accurate weather and air quality predictions, but also a quantification of their uncertainty. For national security and air quality, reliable uncertainty quantification is central to cost-effective decision-making, for adopting efficient strategies on the ground to protect the public health, and to mitigate the harmful effects of contaminants released either accidentally or deliberately in the atmosphere.
NCAR’s National Security Applications Program (NSAP) has extensive experience with advanced ensemble approaches to generate three-dimensional probabilistic predictions, which include systems based on multi-physics and/or multi-model and/or multi-boundary conditions approaches.
A recent advance in this focus area is the ability to generate accurate point-based predictions and reliable uncertainty quantification at a fraction of the computational cost of traditional ensemble methods, called the Analog Ensemble (AnEn), which has been successfully applied for a range of applications. For example, in a test performed for 0-72 hour predictions of wind power at a wind farm in Italy, the AnEn outperformed a power prediction based on the European Center for Medium range Weather Forecasting (ECMWF) ensemble wind predictions, a worldwide leader in operational forecasting. And, the AnEn computational cost was about one fourth of what was required to generate the ECMWF ensemble.
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Uncertainty Quantification and Probabilistic Forecasting