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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.
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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.
March 2003 Results • Average % Risk: 59% • 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 bi-weekly 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_index.nh> • <http://www.longpaddock.qld.gov.au/SeasonalClimateOutlook/SouthernOscillationIndex/SOIDataFiles/>