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An attempt to predict the anomalies in the monthly mean sea level pressure field a month ahead
Author(s) -
Colgate M. G.
Publication year - 1975
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.49710142810
Subject(s) - anomaly (physics) , surface pressure , northern hemisphere , climatology , geology , linear regression , variance (accounting) , surface (topology) , mathematics , meteorology , statistics , environmental science , geography , physics , geometry , accounting , condensed matter physics , business
Abstract This article investigates an eigenvector technique for predicting monthly surface pressure anomalies over a network of grid points covering most of the Northern Hemisphere from the previous months' surface pressure anomalies. Eigenvector analyses on archival monthly surface pressure anomalies enabled the anomalies to be represented by natural components whose coefficients were used as predictors in linear regression models for estimating the next month's surface pressure anomaly at each of the grid points. The results show that most of the predictive value was provided by about the first ten natural components accounting for the highest proportion of monthly surface pressure variance. They gave weak, but significant, predictions even after allowing for long period climatic trends, and for persistence of surface pressure anomalies from one month to the next. Further investigation was carried out to discover the nature of the relationships, and these results are also presented.