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Variability of Tropical Intraseasonal Convective Anomalies and their Statistical Forecast Skill

This study examines the variability of Tropical Intraseasonal Convective Anomalies (TICA) and their statistical forecast skill. It investigates the seasonal frequency of TICA occurrences, their dependence on ENSO phase, differences in characteristics, frequency of major TICA events, and forecast skill. The study also compares forecast skill between different TICA types and its dependence on ENSO phases.

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Variability of Tropical Intraseasonal Convective Anomalies and their Statistical Forecast Skill

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  1. Variability of Tropical Intraseasonal Convective Anomalies and their Statistical Forecast Skill Charles Jones, Leila M. V. Carvalho, Wayne Higgins, Duane Waliser and Jae-K Schemm • Objectives • What is the seasonal frequency of TICA occurrences? • How does the TICA frequency depend on ENSO phase? • Are there differences between TICA characteristics? • What is the seasonal frequency of major TICA events? • What is the forecast skill of TICA events? • Are there significant differences in the forecast skill of different TICA types • Does the forecast skill depend on ENSO phases?

  2. Equatorial Eastward EE • Wang and Rui (1990) • Synoptic climatology of TICA • OLR 1975-1985 (1978 missing) • 5˚x5˚ Latitude/longitude • Life span longer 4 pentads; minimum OLRA ≤ -25 W m-2 • Tracking done with minimum OLRA Large diversity of TICA occurrences Equatorial Northeast/Southeastward N(S)E Equatorial Northward EN

  3. MASCOTTE • Data • OLR and Zonal wind (U) at 200 hPa and 850 hPa • Pentads January 1979 – December 2002; 5˚x5˚ lat/lon • Filtering • For each gridpoint, fit harmonic analysis and remove components with T≥ 100 days • One pass of 1-2-1 filter • OLR is further smoothed with weighted spatial filter • OLRA Screening For each pentad, contiguous regions with OLRA ≤ -10 Wm-2 are identified The minimum within the region ≤ -15 Wm-2 OLRA regions are tracked in time with MASCOTTE -10 Wm-2 t - - t +1 Maximum spatial correlation between OLRA regions in successive images - • TICA Events • Duration T ≥ 4 pentads • Minimum OLRA during life cycle ≤ -25 W m-2 • Eastward propagation and end eastward of 50˚E Carvalho, L. M. V., and C. Jones, 2001: A Satellite Method to Identify Structural Properties of Mesoscale Convective Systems based on Maximum Spatial Correlation Tracking Technique (MASCOTTE). Journal of Applied Meteorology, 40, 1683-1701.

  4. Properties of TICA events • Date and duration (T) • Lat/lon of center of gravity (-10 Wm-2, -15 Wm-2) and minimum OLRA • Number of clusters OLRA ≤ -15 Wm-2 • Minimum OLRA and OLRA variance • Fraction of the contiguous OLRA region intercepting 5 key regions (Rk,t k=1,5) For each pentad (t) Intersection Ratio in region K and time t t +1 t Cumulative Intersection Ratio in region K Significant Interaction in region K: k≥ 1

  5. TICA trajectories Total: 110 IND (19) ISO (53) MJO (38)

  6. What is the seasonal Frequency of TICA events?

  7. What is the seasonal Frequency of TICA events? How does the TICA occurrence depend on the ENSO phase?

  8. Major MJO Zonal Displacement ≥ Median Value in the quarter and Minimum OLRA ≤ Median Value in the quarter What is the frequency of major MJO events? 34.21% * * Increased wind speed is the rectification effect calculated according to Shinoda and Hendon (2002)

  9. TICA Statistical Forecast Skill • Model Development • Extended Winter (17 Nov – 15 May) and Summer (16 May – 16 Nov) Seasons • OLRA U200 and U850 Anomalies • Develop Combined EOF analysis: U850 Retain First Two EOF Modes Space A = U200 OLRA Time • Fit multiple linear regression:  = 1,10 1979 1980 1990 1999 2000 Training Forecast 22 years of forecasts Training Forecast

  10. Winter Validation

  11. Winter Validation All pentads in the winter season

  12. Conclusions • Eastward propagating TICA exhibits a large degree of variability. • Frequency of one or more ≥ 0.9 (JFM, AMJ, OND) • Neutral and Warm ENSO phases • TICA statistical forecast skill • Useful skill extends to about 5 pentads over most of Indian and western Pacific • MJO has slightly higher forecast skill than ISO

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