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A multiple model assessment of seasonal climate forecast skill for applications

Lavers, David; Luo, Lifeng; Wood, Eric F.. 2009 A multiple model assessment of seasonal climate forecast skill for applications. Geophysical Research Letters, 36, L23711. 6, pp. 10.1029/2009GL041365

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Abstract/Summary

Skilful seasonal climate forecasts have potential to affect decision making in agriculture, health and water management. Organizations such as the National Oceanic and Atmospheric Administration (NOAA) are currently planning to move towards a climate services paradigm, which will rest heavily on skilful forecasts at seasonal (1 to 9 months) timescales from coupled atmosphere-land-ocean models. We present a careful analysis of the predictive skill of temperature and precipitation from eight seasonal climate forecast models with the joint distribution of observations and forecasts. Using the correlation coefficient, a shift in the conditional distribution of the observations given a forecast can be detected, which determines the usefulness of the forecast for applications. Results suggest there is a deficiency of skill in the forecasts beyond month-1, with precipitation having a more pronounced drop in skill than temperature. At long lead times only the equatorial Pacific Ocean exhibits significant skill. This could have an influence on the planned use of seasonal forecasts in climate services and these results may also be seen as a benchmark of current climate prediction capability using (dynamic) couple models.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.1029/2009GL041365
Programmes: CEH Topics & Objectives 2009 onwards > Water > WA Topic 3 - Science for Water Management > WA - 3.1 - Develop next generation methods for river flow frequency estimation and forecasting
CEH Sections: Harding (to 31.07.11)
ISSN: 0094-8276
NORA Subject Terms: Meteorology and Climatology
Atmospheric Sciences
Date made live: 12 Oct 2010 12:20
URI: http://nora.nerc.ac.uk/id/eprint/11239

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