Measuring the potential utility of seasonal climate predictions

Michael K. Tippett, Richard Kleeman, Youmin Tang

Research output: Contribution to journalArticlepeer-review

Abstract

Variation of sea surface temperature (SST) on seasonal-to-interannual time-scales leads to changes in seasonal weather statistics and seasonal climate anomalies. Relative entropy, an information theory measure of utility, is used to quantify the impact of SST variations on seasonal precipitation compared to natural variability. An ensemble of general circulation model (GCM) simulations is used to estimate this quantity in three regions where tropical SST has a large impact on precipitation: South Florida, the Nordeste of Brazil and Kenya. We find the yearly variation of relative entropy is strongly correlated with shifts in ensemble mean precipitation and weakly correlated with ensemble variance. Relative entropy is also found to be related to measures of the ability of the GCM to reproduce observations.

Original languageEnglish (US)
Pages (from-to)1-4
Number of pages4
JournalGeophysical Research Letters
Volume31
Issue number22
DOIs
StatePublished - Nov 28 2004

Keywords

  • 1620 Global Change: Climate dynamics (3309)
  • 1869 Hydrology: Stochastic processes
  • 3339 Meteorology and Atmospheric Dynamics: Ocean/atmosphere interactions (0312, 4504)
  • 3354 Meteorology and Atmospheric Dynamics: Precipitation (1854)
  • 4522 Oceanography: Physical: El Nino

ASJC Scopus subject areas

  • Geophysics
  • Earth and Planetary Sciences(all)

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