Subseasonal Variability of Hurricane Activity

1. Subseasonal Variability of Hurricane Activity Kathy Pegion Center for Ocean-Land-Atmosphere Studies Philip Pegion (CPC), Tim DelSole (COLA), & Mihai Sirbu (COLA)

2. Counts of Atlantic TS and Hurricanes every 6 hrs Tropical cyclones tend to cluster in time and space on subseasonal timescales. Is this predictable? Can it be forecasted with a dynamical model?

3. Courtesy of the Clivar MJOWG

4. Issued: 9/15 Week 2 Outlook – Valid: Sep 23 – 29, 2008 1. An increased chance for tropical cyclogenesis for the eastern Pacific, western Gulf Of Mexico and western Caribbean.The favorable phase of the MJO increases the threat for tropical development during the period. Confidence: Moderate 2. An increased chance for above-average rainfall for the eastern Pacific, southern Mexico and parts of Central America.The enhanced phase of the MJO is expected to result in wet conditions during the period. Confidence: Moderate 3. An increased chance for below-average rainfall for the equatorial Indian Ocean and western Indonesia.The suppressed phase of the MJO is expected to result in dry conditions during the period. Confidence: Moderate 4. An increased chance for above-average rainfall stretching from Southeast Asia into the western Pacific. The enhanced phase of the MJO is expected to result in wet conditions during the period. Confidence: Moderate 5. An increased chance for tropical cyclogenesis for the South China Sea and the far western Pacific. The favorable phase of the MJO increases the threat for tropical development during the period. Confidence: Moderate SEE TEXT NOTATION: Conditions are expected to begin to become more favorable for tropical cyclogenesis across the deep tropical Atlantic Ocean late during the period but development is more likely during week 3. Courtesy of the CPC from the Global Tropical Benefits/Hazards Website (http://www.cpc.noaa.gov/products/precip/CWlink/ghazards/ghaz.shtml) Please note:Confidence estimates are subjective in nature and are not based on an objective scheme. The estimates are given to provide additional information to the user.

5. Questions Can the relationship between MJO and tropical cyclone activity be captured using common hurricane indices (eg. SGP and GPI)? How well does the CFS simulate the relationship? Can forecasts of these indices by the CFS be used to predict where tropical cyclone formation is more/less likely on 1-4 week timescales?

6. Hurricane Indices Seasonal Genesis Parameter (Gray 1979) SGP=vorticity*coriolis*shear*thermal energy*moist stability *RH Genesis Potential Index (Emanuel and Nolan 2004) GPI=absolute vorticity*RH * Potential Intensity * shear

7. Data NCEP Reanalysis-2 1979-2007 CFS03 (T62L64) 52-year simulation Filtering 1. Five-day running mean applied to fields prior to calculating SGP or GPI 2. ENSO removed from fields prior to calculating SGP or GPI using linear regression with Nino 3.4

8. Climatology and Standard Deviation of SGP & GPI NCEP Reanalysis-2 All tropical storm formations from the Hurricane Best Track Database 1979-2007

9. Western Pacific Phase 7 Phase 6 Phase 5 Phase 8 RMM2 W. Hemisphere & Africa Maritime Continent Phase 1 Phase 4 Phase 2 Phase 3 RMM1 Indian Ocean MJO Index Real-time Multivariate MJO Index (Wheeler and Hendon 2004) (obtained from Matt Wheeler, BMRC; 1975-2000) Based on combined EOFs of U200, U850, and OLR First two PC timeseries (RMM1 & RMM2) represent the MJO amplitude and phase SQRT(RMM12+RMM22) > 1

10. Composite OLR (W/m2) anomalies (Jun-Nov) Observed CFS03 • Large-scale region of enhanced/suppressed convection • Eastward propagation • Note enhanced/supressed convection in Central America & Atlantic

11. Composite anomalies (Jun-Nov) Based on observed RMM Obs OLR R2 SGP R2 GPI • SGP & GPI vary with phase of MJO • SGP & GPI are very similar

12. Composite SGP & GPI anomalies (Jun-Nov) Reanalysis-2 (1979-2007) SGP GPI Location of tropical storm formations from Hurricane Best Track Database 1979-2007 obtained from Unisys • Actual formations are generally consistent with regions of +/- SGP/GPI anomalies

13. Quantifying the Relationship H0: P(Hur Index | MJO Phase) = P(Hur Index) Hurricane Index: GPI or SGP Terciles MJO Phase : 8 phases + null phase Mutual Information

14. P(MJO phase) No/Weak MJO MJO Phase

15. P(Hur Index) Each Tercile = 33% SGP GPI 33% (Jun-Nov) 33% (Jun-Nov) 67% (Jun-Nov) 67% (Jun-Nov) 15

16. P(GPI, MJO Phase) 33 %ile > GPI < 66%ile GPI <= 33%ile GPI >= 66%ile Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 6 Phase 7 Phase 8

17. Mutual Information between Hurricane Index and MJO SGP GPI 17

18. CFS NCEP/R2 SGP Climatology (Jun-Nov) SGP Standard Deviation

19. NCEP/R2 CFS03/T62 Composite SGP (Jun-Nov) CFS is generally able to capture the overall behavior of the relationship between the MJO and SGP

20. NCEP/R2 CFS03/T62 ERA40 20

21. P(MJO phase) No/Weak MJO MJO Phase

22. P(Hur Index) Each Tercile = 33% CFS SGP R2 SGP 33% (Jun-Nov) 33% (Jun-Nov) 67% (Jun-Nov) 67% (Jun-Nov) 22

23. P(Hur Index) Each Tercile = 33% CFS GPI R2 GPI 33% (Jun-Nov) 33% (Jun-Nov) 67% (Jun-Nov) 67% (Jun-Nov) 23

24. Mutual Information between SGP and MJO R2 SGP CFS SGP 24

25. Mutual Information between GPI and MJO R2 GPI CFS GPI 25

26. Conclusions SGP & GPI indices capture the relationship between MJO and tropical cyclone development. The CFS is generally able to capture the relationship Mutual information between SGP and MJO shows a significant relationship in the eastern Pacific. Mutual information between GPI and MJO shows a significant relationship throughout the domain.

27. Issued: 9/15 Week 2 Outlook – Valid: Sep 23 – 29, 2008 1. An increased chance for tropical cyclogenesis for the eastern Pacific, western Gulf Of Mexico and western Caribbean.The favorable phase of the MJO increases the threat for tropical development during the period. Confidence: Moderate 2. An increased chance for above-average rainfall for the eastern Pacific, southern Mexico and parts of Central America.The enhanced phase of the MJO is expected to result in wet conditions during the period. Confidence: Moderate 3. An increased chance for below-average rainfall for the equatorial Indian Ocean and western Indonesia.The suppressed phase of the MJO is expected to result in dry conditions during the period. Confidence: Moderate 4. An increased chance for above-average rainfall stretching from Southeast Asia into the western Pacific. The enhanced phase of the MJO is expected to result in wet conditions during the period. Confidence: Moderate 5. An increased chance for tropical cyclogenesis for the South China Sea and the far western Pacific. The favorable phase of the MJO increases the threat for tropical development during the period. Confidence: Moderate SEE TEXT NOTATION: Conditions are expected to begin to become more favorable for tropical cyclogenesis across the deep tropical Atlantic Ocean late during the period but development is more likely during week 3. Courtesy of CPC from the Global Tropical Benefits/Hazards Website (http://www.cpc.noaa.gov/products/precip/CWlink/ghazards/ghaz.shtml) Please note:Confidence estimates are subjective in nature and are not based on an objective scheme. The estimates are given to provide additional information to the user.

28. Caveats & Future Work Indices: maybe the hurricane indices and/or the MJO index are not the right one, also test different variables. So far, we have only quantified one piece of the problem. Have not quantified P ( TC | Hur Index), P(TC | MJO). What we really want to know is: H0: P(TC | Hur Index & MJO) = P(TC) 3. What is the prediction skill of SGP and GPI and are CFS forecasts of these quantities useful tools for contributing to the GTH product?

29. Correlations between CFS forecasts and NCEP/R2 (Aug-Oct 2005-2007) Full Fields of SGP, not anomalies, no MJO filter Week-2 Week-1 Week-3 Week-4