Computer Science – Information Theory
Scientific paper
Nov 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004georl..3122201t&link_type=abstract
Geophysical Research Letters, Volume 31, Issue 22, CiteID L22201
Computer Science
Information Theory
12
Global Change: Climate Dynamics (3309), Meteorology And Atmospheric Dynamics: Precipitation (1854), Meteorology And Atmospheric Dynamics: Ocean/Atmosphere Interactions (0312, 4504), Oceanography: Physical: El Nino, Hydrology: Stochastic Processes
Scientific paper
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.
Kleeman Richard
Tang Youmin
Tippett Michael K.
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