Mapping rainfall fields and their ENSO variation in data-sparse tropical South-West Pacific Ocean Region

Rainfall fields for the data-sparse tropical south-west Pacific Ocean region have been mapped by partial thin-plate smoothing spline surface modelling applied to island rainfall measurements, enhanced by the use of satellite observations of outgoing longwave radiation (OLR) as a regression covariate. The aim is to obtain spatially realistic rainfall maps, especially in the data-sparse areas between island groups, through a fully objective and statistically valid method that includes error estimates. The method has been applied to the region 4°N–24°S, 168°E–154°W. The rainfall data set initially comprised 57 stations, most with 40 year records. As a first step, a regression of annual OLR and rainfall for atolls only was formed and used to eliminate ‘outlier’ rainfall stations, all of which are on mountainous islands and thus are probably influenced orographically. The maps clearly show the spatial patterns and seasonal behaviour of the region's key meteorological features, namely, the South Pacific Convergence Zone (SPCZ), the southern edge of the Inter-tropical Convergence Zone (ITCZ), and the wedge shaped region of divergent easterlies lying between them. To identify ENSO variations, maps of 3-month seasonal rainfall were constructed from composites of eight El Nino (negative SOI) episodes and nine La Nina (positive SOI) episodes. These maps are relatively rough in appearance, but nevertheless they show the evolution of the spatial patterns through each composite episode and the strong and symmetrically opposite differences between them. Marked variations in the strength and position of the SPCZ are evident and the isohyets in the equatorial dry zone exhibit east–west shifts of nearly 3000 km relative to the average field. The rainfall variation at a particular location may be understood in terms of competition of influence among the changing features of the pattern, rather than as a simple linear function of the SOI. © 1998 Royal Meteorological Society

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