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Chapter 2 - Weather Forecasting: What Sets The Forecast Skill Horizon?


Determinism (a unique dependence of future states on the current state) makes weather forecasts possible, while chaos (the sensitivity of such dependence on minor details of the initial state) strictly bounds predictability. In particular, the predictability of the spatiotemporal position of finer-scale weather features is lost first, while the position and phase of larger-scale waves retain some predictability until up to 15 days lead time. Because the atmosphere is influenced by high-energy ocean, land, and ice processes that often act on relatively slow timescales, the predictability of continental- and larger-scale variability in a coupled system is further extended. A discussion of several underlying theoretical concepts is followed by a review of their application in numerical weather prediction (NWP) practice. Beyond tracking the location of low-frequency and large-scale motions that for most users may have little direct influence, sub-seasonal to seasonal (S2S) predictions may also exploit climatic predictability in the frequency or other statistics of high-impact weather such as hurricanes or tornadoes (long after their trackable predictability is lost), conditioned on some still-trackable large-scale features. Weather prediction techniques used for the extraction of useful information from low-skill forecasts, including spatiotemporal or ensemble averaging of NWP forecasts, are also reviewed with an eye toward their adaptation and refinement for S2S timescales.

Article / Publication Data
Available Metadata
Accepted On
October 16, 2018
Fiscal Year
Peer Reviewed
Publication Name
Sub-seasonal To Seasonal Prediction The Gap Between Weather and Climate Forecasting
Published On
October 26, 2018
Publisher Name
El Siever
Page Range


Not available


Authors who have authored or contributed to this publication.