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

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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 t... 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 t...

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