Open AccessReconstruction of Monthly Mean 700-mb Heights from Surface Data by Reverse Specification
Author(s) -
William H. Klein,
Ying Dai
Publication year - 1998
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/1520-0442-11.8.2136
Subject(s) - anomaly (physics) , climatology , northern hemisphere , mean squared error , mathematics , variance (accounting) , mean radiant temperature , function (biology) , standard deviation , root mean square , stability (learning theory) , linear regression , correlation coefficient , statistics , geology , climate change , physics , oceanography , accounting , condensed matter physics , evolutionary biology , quantum mechanics , machine learning , computer science , business , biology
This paper demonstrates an objective method of computing monthly mean 700-mb height anomalies (H) at 108 grid points in the Western Hemisphere for a 40-yr period as a function of concurrent anomalies of monthly mean sea level pressure (P), at the same 108 points used for H, and monthly mean surface air temperature (T) averaged over 112 areas in North America. The authors applied a forward stepwise program to derive linear multiple regression equations that explained 81% of the variance of H by means of only 3.5 variables, averaged over all months and grid points. The stability of these equations held up well on 6 yr of independent data in terms of explained variance, root-mean-square error, and the spatial anomaly correlation coefficient. Therefore, it seems feasible to reconstruct maps of H for the first half of the twentieth century as a function of data on P and T only.