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Integrating ensemble information into calibrated probabilistic weather forecasts workshop on information integration position paper.
| Content Provider | CiteSeerX |
|---|---|
| Author | Gneiting, Tilmann Mass, Clifford F. Raftery, Adrian E. |
| Abstract | Weather forecasting has historically been a deterministic enterprise, in which a single forecast is given without uncertainty information. The one exception has been the “probability of precipitation”, but no uncertainty information is typically provided about other weather quantities such as temperature, humidity, wind, snow or amount of rain. Probability information is important for decision-makers who are affected by weather, in industries such as farming, tourism, transportation and the military, as well as ordinary people planning events and activities. In response to this need, a recent National Research Council report recommends a massive reorientation of national weather forecasting efforts toward probabilistic forecasting (National Research Council 2006). Operationally, probabilistic weather prediction is based on ensemble methods (Gneiting and Raftery 2005). An ensemble forecast comprises multiple (typically between 5 and 100) runs of numerical weather prediction models, which differ in the initial conditions being used and/or the parameterized representation of the atmosphere, thereby addressing the major sources of forecast uncertainty. Realizing the full potential of an ensemble forecast requires postprocessing of the model |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Ensemble Information Information Integration Position Paper Calibrated Probabilistic Weather Forecast Workshop Ensemble Forecast Uncertainty Information Ordinary People Parameterized Representation Single Forecast Numerical Weather Prediction Model Probabilistic Weather Prediction National Research Council Deterministic Enterprise Probability Information Recent National Research Council Report Massive Reorientation Probabilistic Forecasting Forecast Uncertainty National Weather Weather Quantity Full Potential Major Source Weather Forecasting Initial Condition Ensemble Method |
| Content Type | Text |
