Laplacian smoothing splines with generalized cross validation for objective analysis of meteorological data
By: by Richard Franke
Contributors: Naval Postgraduate School (U.S.)
Publisher: Naval Postgraduate School
Published: 1985
Place of publication: Monterey, California
Language: eng
Number of pages: 33
Subjects: Interpolation; Weather forecasting; Spline theory
Description: The use of Laplacian smoothing splines (LSS) with generalized cross validation (GCV) to choose the smoothing parameter for the objective analysis problem is investigated. Simulated 500 mb pressure height fields are approximated from first-quess data with spatially correlated errors and observed values having independent errors. It is found that GCV does not allow LSS to adapt to variations in individual realizations, and that specification of a single suitable parameter value for all realizations leads to smaller rms error overall. While the tests were performed in the context of data from a meteorology problem, it is expected the results carry over to data from other sources. A comparison shows that significantly better approximations can be obtained using LSS applied in a unified manner to both first-guess and observed values rather than in a correction to first-guess scheme (as in Optimum Interpolation) when the first-guess error has low spatial correlation.
Notes: Title from cover.

"Prepared for: Naval Environmental Prediction Research Facility"--Cover.

"August 1985"--Cover.

"Technical report for period October 1984 - March 1985"--Cover.

"NPS-53-85-0008"--Cover.

DTIC Identifiers: Smoothing (Mathematics), PE61153N.

Author(s) key words: Objective analysis, optimum interpolation, generalized cross validation, Laplacian smoothing splines.

Includes bibliographical references (p. 17-18)

"Approved for public release; distribution unlimited"--Cover.

Technical report; 1985.

aq/aq cc:9116 09/03/98