Climatic Pattern Analysis of Three- and Seven-Day Summer Rainfall in the Central United States: Some Methodological Considerations and a Regionalization

Abstract

This paper presents the results of climatic pattern analyses of three- and seven-day summer (May?August) rainfall totals for the central United States. A range of eigenvectorial methods is applied to 1949?80 data for a regularly spaced network of 402 stations that extends from the Rocky to the Appalachian Mountains and from the Gulf Coast to the Canadian border. The major objectives are to quantitatively assess the sensitivity of eigenvectorial results to several parameters that have hitherto been the subject of considerable qualitative concern, and to identify the potential applications of those results. The entire domain variance fractions cumulatively explained by a) the first 10 correlation-based unrotated Principal Components (PCs) and b) the 10 orthogonally rotated (VARIMAX criterion) PCs derived from them are identical for the same data. They vary between 35?47 percent depending on the data time scale and form, being higher for seven- than three-day totals and further enhanced when those totals are square-root (especially) and log10 transformed. The (highly contrasting) sets of unrotated and VARIMAX PC spatial loading patterns are invariant with respect to data time scale and form. They receive strong statistical support from analyses performed on subsets of the data, their covariance- and cross-products-based equivalents, counterpart common factor patterns, and (for VARIMAX) an obliquely rotated (Hanis?Kaiser Case II B?B criterion) PC analysis. The unrotated PC loading patterns very closely resemble the set that Buell claimed would tend to characterize a domain of the present rectangular shape, irrespective of the meteorological parameter treated. They receive little physical support from analyses performed separately for subareas of the domain or from comparison with the interstation correlation matrix from which they are derived. The VARIMAX PC loading patterns, in contrast, derive strong physical support from those verifications. Each of these patterns emphasizes a relatively strong anomaly in a different part of the domain; they collectively yield a regionalization of the domain into 10 subareas within which three- and seven-day summer rainfall tends to be spatially coherent. The regionalization is suggested to be of considerable potential utility for crop-yield modeling, short-range weather prediction, and research into climatic variation and change.