A Diagnostic Risk Assessment
for Pattern Flips
Kevin Lipton
Gordon Strassberg
April 29, 2003
Overview of Discussion
• Definition of Pattern Flip as used in this
study.
• Data collection and methodology.
• Formulation of the diagnostic risk index.
• March 2003 results.
• Conclusions and future research.
What is a “pattern flip?”
• In this study, a significant change in the
longwave pattern (500 mb Heights) over
North America.
• Each segment of the flip remained in place
for more than 2 weeks, in order to reflect
in monthly indices.
Example of Pattern Flip
• Oct 1989 VS Nov 1989: 500 mb Height
Anomalies
Data Collection and Methodology
• Months/Years of pattern flips were determined
•
•
by memory and then verified with NCEP
Reanalysis Data.
Monthly values of several atmospheric
indices/teleconnection patterns of known
importance to N. American weather were used.
NAO, PNA, SOI, and EP were the relevant
indices.
Data Collection and Methodology
• NAO, PNA, EP monthly values from the
CPC website.
• SOI data obtained from Long Paddock
(Australian Gov’t Service).
• Data examined for the month preceding
the flip AND the month of the flip itself.
Formulation of the Diagnostic Index
• Most obvious elements to use were
monthly sign changes in certain indices
before/during the pattern flip.
• SOI, NAO, and EP all changed signs in
50% or more of the cold season cases
(Nov-Mar).
Procedure Error
• SOI sign changes were weighted most
heavily since it appeared to be the most
frequent change of sign.
• However, after adding several more cases,
this was no longer accurate.
• Heavy weighting of SOI may be overdone.
Formulation of the Diagnostic Index
• Data review showed significance in the
sum of the NAO+PNA+EP values for the
month preceding the flip.
Final Risk Index Weighting
•
•
•
•
•
SOI sign change 35%
NAO/PNA/EP sum 30%
Any 2 indices change sign 15%
NAO sign change 10%
EP sign change 10%
• If “yes” to above, full weighting applied; if “no”
then 0 weighting applied.
Cold Season Results
Month/
Year
SOI Sign
Change
35%
NAO/PNA/EP Sum
“-” 30%
2 Ind.
Change Sign
15%
NAO Sign
Change 10%
EP Sign
Change
10%
Risk
%
Dec 84
Y
1.4
Y
Y
Y
70
Nov 89
Y
-1.2
Y
Y
Y
100
Jan 90
N
-1.9
Y
Y
Y
65
Mar 92
N
0.6
N
N
N
0
Jan 93
N
-1.8
N
N
N
30
Jan 96
Y
-1.1
Y
N
Y
90
March 2003 Results
• Average % Risk: 59%
Month/
Year
SOI
Sign
Change
35%
NAO/P
NA/EP
Sum “” 30%
2 Ind.
Change
Sign
15%
NAO
EP Sign Risk %
Sign
Change
Change 10%
10%
Mar 03
N
-2.9
Y
Y
Y
65
• Mar 2003 Risk: 65% (Above Average)
More Results
• Several “stable” months (no flip) were
tested using the diagnostic index.
• The average risk of a flip for those 4
months was only 34%.
Conclusions
• Atmospheric Indices can be used to
diagnose the risk of a pattern flip in past
months.
• There is a clear difference in this index
between months that had a pattern flip
and months that did not.
Future Research
• Develop Prognostic Index for assessing the risk
of pattern flips
– Decrease the temporal scale and use weekly or biweekly data and apply a similar risk assessment
study.
– Include other known indices (SST Anomalies, QBO,
MJO, PDO).
– Develop technique for Different Types of Pattern
Changes/Flips (I.E. Ridge E/Trough W/vice versa).
References
• <ftp://ftpprd.ncep.noaa.gov/pub/cpc/wd52dg/data/indices/tele_inde
x.nh>
• <http://www.longpaddock.qld.gov.au/SeasonalClimateOutlook/Sout
hernOscillationIndex/SOIDataFiles/>