Data Analysis
Climate variability
 Airsea interaction
 Airland interaction
 Local responses
Climate predictability

Methodology
Predictive signals
The linear modelling approach is based on
identification of joint modes of variability linking predictor and
predictand variables.
 A subset of CCA pairs representing two fields
is used to build a regression model (Von Storch, 1995) to estimate the
anomalies of predictand (SLP, geopotential height at 500 hPa) from the
anomalies of the predictor (May SST, November air surface temperature).
 The performance of the model is sensitively
dependent on the number of EOFs and CCA pairs used in the regression
model.
 Here, the CCA based models have been been
trained for the interval 19611986 and were independently tested in the
interval 19872001. Both models use 4 CCA modes derived from 6 EOFs from
the paired fields.
Results
 November/DJFM model
 May/DJFM model

EOF
CCA
POP
MICOM 