An Empirical Model Using Eigenvectors to Calculate the Temporal and Spatial Variations of the St. Louis Heat Island

John F. Clarke Environmental Protection Agency, National Environmental Research Center, Research Triangle Park, N. C. 27711

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James T. Peterson Environmental Protection Agency, National Environmental Research Center, Research Triangle Park, N. C. 27711

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Abstract

Eigenvectors, or empirical orthogonal functions, have been used to study the relationship between the St. Louis heat island and land use and meteorological parameters. The data used in this study consisted of observations of nocturnal surface air temperature over St. Louis on 17 occasions during winter, spring, and summer of 1952–53. The spatial distribution of the heat island was shown to he primarily a function of land use, but meteorological variables, especially wind direction, also influenced the heat island patterns. The magnitude of the heat island had a significant positive correlation with the vertical temperature gradient outside the city. An empirical model is developed for St. Louis to study the heat island that would result from hypothetical land-patterns and meteorological conditions. Examples are presented for two such land-use distributions.

Abstract

Eigenvectors, or empirical orthogonal functions, have been used to study the relationship between the St. Louis heat island and land use and meteorological parameters. The data used in this study consisted of observations of nocturnal surface air temperature over St. Louis on 17 occasions during winter, spring, and summer of 1952–53. The spatial distribution of the heat island was shown to he primarily a function of land use, but meteorological variables, especially wind direction, also influenced the heat island patterns. The magnitude of the heat island had a significant positive correlation with the vertical temperature gradient outside the city. An empirical model is developed for St. Louis to study the heat island that would result from hypothetical land-patterns and meteorological conditions. Examples are presented for two such land-use distributions.

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