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• Explain the basis for NWP ensemble prediction, and what we mean when we say that the atmosphere is chaotic (i.e. sensitive to initial conditions).
• Describe the variety of methods used to generate the ensemble members of an ensemble prediction system, including perturbation of initial conditions, boundary conditions, and model configurations.
• Understand the basic statistical concepts and methods used in the development of ensemble products, including probability distributions and their middleness, variability, and shape characteristics.
• Recognize and interpret the variety of ensemble forecast products, including spatial and point forecast graphics, and including those that account for flow regimes (RMOP) and reveal NWP model bias and errors.
• Interpret ensemble verification products, and apply them in using ensemble forecasts.

December 2020 - The lesson was updated to current internet standards (mp4/html5), with no changes to content.

July 2014: This lesson presents the theoretical basis for ensemble prediction systems (EPS) and the derived products that come from them. For winter and summer case examples, see this lesson's less detailed companion, "Introduction to Ensemble Prediction".

Training since this lesson's publication has incorporated operational forecast EPS applications where appropriate. Examples are in "NWP Training Series Course 2: Using and adding value to NWP in the forecast process", and other lessons on practical applications of EPS (e.g. "Ensemble Applications in Winter").