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Spatial Forecast Verification: Image Warping

Författare

  • Eric Gilleland
  • Linchao Chen
  • Michael DePersio
  • Giang Do
  • Kirsten L. Eilertson
  • Yin Jin
  • Emily L. Kang
  • Finn Lindgren
  • Johan Lindström
  • Richard L. Smith
  • Changming Xia

Summary, in English

In response to a growing need for more informative forecast verification in the

face of gridded verification sets, many new methods have been proposed. While

widely varying in their approaches, the new methods generally fall into two ma-

jor categories of filter and displacement, each of which can be further subdivided.

One of the displacement approaches, a field deformation approach known as image

warping, will be demonstrated here. Results for spatial verification of the spatial

forecast verification Inter-Comparison Project test cases are shown. An initial look

at space-time verification using the image warp is also discussed, with an applic-

ation to NCAR and NCEP 4-km WRF models cases from the 2005 NSSL/SPC

Spring Program. The approach is found to be very useful for obtaining guidance

about forecast performance. Both diagnostic and summary score information can

be gleaned. Initial findings for the space-time approach show that while the NCEP

model has better initial scores, the NCAR models require drastically less deform-

ation to achieve a much higher reduction in error. This is most likely a result of

the NCEP model’s highly over forecasting low-intensity precipitation spatially.

Publiceringsår

2010

Språk

Engelska

Publikation/Tidskrift/Serie

NCAR Technical Notes

Dokumenttyp

Rapport

Förlag

National Center for Atmospheric Research, Boulder, CO, USA

Ämne

  • Probability Theory and Statistics

Status

Published

Report number

NCAR/TN-482+STR

ISBN/ISSN/Övrigt

  • ISSN: 2153-2400
  • ISSN: 2153-2397