A Comparison of Interpolation Methods for Sparse Data: Application to Wind and Concentration Fields
In order to produce gridded fields of pollutant concentration data and surface wind data for use in an air quality model, a number of techniques for interpolating sparse data values are compared. The techniques are compared using three data sets. One is an idealized concentration distribution to which the exact solution is known, the second is a potential flow field, while the third consists of surface ozone concentrations measured in the Los Angeles Basin on a particular day. The results of the study indicate that fitting a second-degree polynomial to each subregion (triangle) in the plane with each data point weighted according to its distance from the subregion provides a good compromise between accuracy and computational cost.
© 1979 American Meteorological Society. Manuscript received 1 December 1978, in final form 23 February 1979. Portions of this work were supported by the California Air Resources Board under Contract A5-046-87, and by the Department of Energy under Institutional Grant EY-76-G-03-1305.
Published - 1GOOjam1979.pdf