Forecast Accuracy & Climate Measures

← Back to Domain-Specific Families

Abstractions about evaluating predictions and climate data, including forecast-skill and error measures like directional symmetry and mean absolute scaled error, and climate-record adjustment through homogenization.

5 abstractions in this family — domain-specific abstractions that sit near one another in structural-signature space (k-means over structural-signature embeddings). Each is shown with its short description.

• Directional symmetry (time series) — A forecast-accuracy statistic equal to the percentage of successive periods in which predicted and observed changes have the same sign.
• Forecast skill — A measure of predictive performance relative to observations and, in skill-score form, relative to a declared reference forecast.
• Homogenization (climate) — The detection and adjustment of non-climatic discontinuities in climate records so their remaining variation better represents weather and climate.
• Mean absolute scaled error — A scale-free forecast-accuracy measure dividing mean absolute forecast error by the in-sample mean absolute error of a specified naive benchmark.
• Meteorological intelligence — Decision-relevant characterization or prediction of atmospheric conditions produced by gathering, analyzing and disseminating weather and climate information.