Non-zero mean Gaussian process prior wind field models

Dan Cornford

Research output: Preprint or Working paperTechnical report

Abstract

This report outlines the derivation and application of a non-zero mean, polynomial-exponential covariance function based Gaussian process which forms the prior wind field model used in 'autonomous' disambiguation. It is principally used since the non-zero mean permits the computation of realistic local wind vector prior probabilities which are required when applying the scaled-likelihood trick, as the marginals of the full wind field prior. As the full prior is multi-variate normal, these marginals are very simple to compute.
Original languageEnglish
Place of PublicationBirmingham
PublisherAston University
Number of pages16
ISBN (Print)NCRG/98/020
Publication statusPublished - 1998

Keywords

  • polynomial-exponential covariance function
  • Gaussian process
  • local wind vector
  • multi-variate

Fingerprint

Dive into the research topics of 'Non-zero mean Gaussian process prior wind field models'. Together they form a unique fingerprint.

Cite this