UCSC-SOE-08-25: Bayesian modeling of wind and sea surface temperature from the Portuguese coast

Ricardo T. Lemos, Bruno Sansó and F.D. Santos
12/08/2008 09:00 AM
Applied Mathematics & Statistics
In this work we revisit a recent analysis that pointed to an overall relaxation of the Portuguese coastal upwelling system, between 1941 and 2000, and apply more elaborate statistical techniques to assess that evidence. Our goal is to fit a model for environmental variables that accommodates seasonal cycles, long term trends, short term fluctuations with some degree of autocorrelation, and cross correlations between measuring sites and variables. Reference cell coding is used to investigate similarities in behavior among sites. We employ a Bayesian approach with a purposely developed Markov chain Monte Carlo method to explore the posterior distribution of the parameters. Our results substantiate most previous findings and provide new insight on the relationship between wind and sea surface temperature off the Portuguese coast.

UCSC-SOE-08-25