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Stephen Lavin
,
Jay Hobgood
, and
Paul Kramer

Abstract

Traditionally, spatial distributions of continuous climatological variables have been displayed using isolines. The placement of isolines involves an assumption about the gradient of the variable being mapped. Because of the numerical value associated with an isoline, a degree of precision is associated with this type of map that may not be justified. Dot-density shading offers an alternative technique for displaying these spatial distributions. The continuous nature of the dot-density display makes it an effective means of thematically depicting variations in the magnitudes of climatological variables. This is demonstrated by maps of various climatological variables for Colorado and from an experimental global climate model.

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Stephen J. Lavin
and
Randall S. Cerveny

Abstract

Gridded matrices of climatic data can be mapped by computer with a variety of symbolization methods, all of which have some shortcomings. A new mapping procedure, dot-density shading, is herein proposed as an alternative mapping form. Dot-density shading produces continuous-appearing dot patterns whose density is proportional to the data. Significant algorithms are those for computing dot numerosity and quasi-random dot placement. A number of application including data error detection and anomaly recognition are discussed.

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