All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 113 9 2
PDF Downloads 33 26 5

On Objective Analysis of Continuous and Discontinuous Parameters

S. PennAir Force Cambridge Research Laboratories, Bedford, Mass.

Search for other papers by S. Penn in
Current site
Google Scholar
PubMed
Close
,
B. KunkelAir Force Cambridge Research Laboratories, Bedford, Mass.

Search for other papers by B. Kunkel in
Current site
Google Scholar
PubMed
Close
, and
W. D. MountSperry Rand Research Center, Sudbury, Mass.

Search for other papers by W. D. Mount in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The problem of analyzing continuous and discontinuous meteorological surface parameters is investigated. Peculiarities of fitting mathematically a first and second degree surface to observational data are investigated from the standpoint of transforming and constraining the observed values and of the influence of observations as a function of distance. For two data density fields a comparison of results is made between the mathematical surfaces and a simplified procedure of selecting the nearest observation. Verification is based upon observed station values which are withheld from the surface fitting procedures. A significant improvement is derived by transforming the variables to ensure closer fitting in a particular range of the variable. For the area of influence under consideration, no appreciable differences were obtained by the incorporation of a distance weighting factor. It was found necessary to restrain the mathematical surfaces to ensure physical reality. Although the more complex mathematical surface does fit the large-scale nonlinear variations more accurately, its sensitivity to the distribution of data and smaller-scale fluctuations produced errors which were larger than those obtained using a linear surface.

Abstract

The problem of analyzing continuous and discontinuous meteorological surface parameters is investigated. Peculiarities of fitting mathematically a first and second degree surface to observational data are investigated from the standpoint of transforming and constraining the observed values and of the influence of observations as a function of distance. For two data density fields a comparison of results is made between the mathematical surfaces and a simplified procedure of selecting the nearest observation. Verification is based upon observed station values which are withheld from the surface fitting procedures. A significant improvement is derived by transforming the variables to ensure closer fitting in a particular range of the variable. For the area of influence under consideration, no appreciable differences were obtained by the incorporation of a distance weighting factor. It was found necessary to restrain the mathematical surfaces to ensure physical reality. Although the more complex mathematical surface does fit the large-scale nonlinear variations more accurately, its sensitivity to the distribution of data and smaller-scale fluctuations produced errors which were larger than those obtained using a linear surface.

Save