- Locality is important: make use of local region.
- Data, especially observed SST data, is imprecise due to the range
of processing steps carried out. (And resolution scale effects are
superimposed on this.)
- Nonlinear mapping - here, multilayer perceptron -
caters for complex decision surfaces.
- To validate results, we take the data as consisting of:
(i) learning set; (ii) validation set; and (iii) missing values,
- We use as a preprocessing phase the redundant B3
spline à trous
wavelet transform. Hence: wavelet nonlinear regression.
- Neighborhood information is accounted for (i) in inputs to
multilayer perceptron mapping, and in (ii) resolution scale, which is based
on low-pass filtering.
- Currents and heating may exist on different scales: how
important is a multiscale analysis?
- In fact, we look at how an OGCM model reconstruction can be
checked against the observed data at a range of different resolution scales.