In the fields of forecasting and prediction, forecasting skill or prediction skill is any measure of the accuracy and/or degree of association of prediction to an observation or estimate of the actual value of what is being predicted (formally, the predictand); it may be quantified as a skill score.
In meteorology, more specifically in weather forecasting, skill measures the superiority of a forecast over a simple historical baseline of past observations. The same forecast methodology can result in different skill scores at different places, or even in the same place for different seasons (e.g., spring weather might be driven by erratic local conditions, whereas winter cold snaps might correlate with observable polar winds). Weather forecast skill is often presented in the form of seasonal geographical maps.
Forecasting skill for single-value forecasts (i.e., time series of a scalar quantity) is commonly represented in terms of metrics such as correlation, root mean squared error, mean absolute error, relative mean absolute error, bias, and the Brier score, among others. A number of scores associated with the concept of entropy in information theory are also being used.
The term 'forecast skill' may also be used qualitatively, in which case it could either refer to forecast performance according to a single metric or to the overall forecast performance based on multiple metrics.
Probabilistic forecast skill scores may use metrics such as the Ranked Probabilistic Skill Score (RPSS) or the Continuous RPSS (CRPSS), among others. Categorical skill metrics such as the False Alarm Ratio (FAR), the Probability of Detection (POD), the Critical Success Index (CSI), and Equitable Threat Score (ETS) are also relevant for some forecasting applications. Skill is often, but not exclusively, expressed as the relative representation that compares the performance of a particular forecast prediction to that of a reference, benchmark prediction—a formulation called a 'Skill Score'.
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Ensemble forecasting is a method used in or within numerical weather prediction. Instead of making a single forecast of the most likely weather, a set (or ensemble) of forecasts is produced. This set of forecasts aims to give an indication of the range of possible future states of the atmosphere. Ensemble forecasting is a form of Monte Carlo analysis.
Weather forecasting is the application of science and technology to predict the conditions of the atmosphere for a given location and time. People have attempted to predict the weather informally for millennia and formally since the 19th century. Weather forecasts are made by collecting quantitative data about the current state of the atmosphere, land, and ocean and using meteorology to project how the atmosphere will change at a given place.
Meteorology is a branch of the atmospheric sciences (which include atmospheric chemistry and physics) with a major focus on weather forecasting. The study of meteorology dates back millennia, though significant progress in meteorology did not begin until the 18th century. The 19th century saw modest progress in the field after weather observation networks were formed across broad regions. Prior attempts at prediction of weather depended on historical data.
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