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Spatial Forecast Verification: Image Warping

Gilleland, Eric ; Chen, Linchao ; DePersio, Michael ; Do, Giang ; Eilertson, Kirsten L. ; Jin, Yin ; Kang, Emily L. ; Lindgren, Finn LU ; Lindström, Johan LU orcid and Smith, Richard L. , et al. (2010) In NCAR Technical Notes
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; and (Less)
organization
publishing date
type
Book/Report
publication status
published
subject
in
NCAR Technical Notes
pages
23 pages
publisher
National Center for Atmospheric Research, Boulder, CO, USA
report number
NCAR/TN-482+STR
ISSN
2153-2400
2153-2397
language
English
LU publication?
yes
id
a959bd13-de5a-450b-9edc-7e36778f3d7f (old id 4730147)
alternative location
http://nldr.library.ucar.edu/repository/assets/technotes/TECH-NOTE-000-000-000-850.pdf
date added to LUP
2016-04-01 10:39:58
date last changed
2018-11-21 19:49:21
@techreport{a959bd13-de5a-450b-9edc-7e36778f3d7f,
  abstract     = {{In response to a growing need for more informative forecast verification in the<br/><br>
face of gridded verification sets, many new methods have been proposed. While<br/><br>
widely varying in their approaches, the new methods generally fall into two ma-<br/><br>
jor categories of filter and displacement, each of which can be further subdivided.<br/><br>
One of the displacement approaches, a field deformation approach known as image<br/><br>
warping, will be demonstrated here. Results for spatial verification of the spatial<br/><br>
forecast verification Inter-Comparison Project test cases are shown. An initial look<br/><br>
at space-time verification using the image warp is also discussed, with an applic-<br/><br>
ation to NCAR and NCEP 4-km WRF models cases from the 2005 NSSL/SPC<br/><br>
Spring Program. The approach is found to be very useful for obtaining guidance<br/><br>
about forecast performance. Both diagnostic and summary score information can<br/><br>
be gleaned. Initial findings for the space-time approach show that while the NCEP<br/><br>
model has better initial scores, the NCAR models require drastically less deform-<br/><br>
ation to achieve a much higher reduction in error. This is most likely a result of<br/><br>
the NCEP model’s highly over forecasting low-intensity precipitation spatially.}},
  author       = {{Gilleland, Eric and Chen, Linchao and DePersio, Michael and Do, Giang and Eilertson, Kirsten L. and Jin, Yin and Kang, Emily L. and Lindgren, Finn and Lindström, Johan and Smith, Richard L. and Xia, Changming}},
  institution  = {{National Center for Atmospheric Research, Boulder, CO, USA}},
  issn         = {{2153-2400}},
  language     = {{eng}},
  number       = {{NCAR/TN-482+STR}},
  series       = {{NCAR Technical Notes}},
  title        = {{Spatial Forecast Verification: Image Warping}},
  url          = {{http://nldr.library.ucar.edu/repository/assets/technotes/TECH-NOTE-000-000-000-850.pdf}},
  year         = {{2010}},
}