Convective Systems in the 2006 West African Monsoon: A Radar Study

1. Nick Guy MS Research SJSU PhD Research CSU 17 February 2009 Convective Systems in the 2006 West African Monsoon:A Radar Study

2. AfricanMonsoonMultidisciplinaryAnalyses Cooperative international project Science Objectives: Improve understanding of WAM Create strategy for monitoring and prediction of WAM Relate underlying science to socioeconomic issues NASAAMMA Collaboration with AMMA Primary Scientific Interests Relationship between AEWs and tropical cyclogenesis in the Atlantic basin role of the Saharan Air Layer (SAL) in modulating the intensity of the waves and tropical cyclone growth

3. MCS • Definition for this study • Organized t-storms with contiguous precipitation region with horizontal scale >100 km

4. SLMCS • Linear organization and propagation • Large impact of thermodynamic and dynamic structure of environment • High prevalence of this type throughout season for MIT and NPOL radar sites • Large contributor of precipitation totals in some areas • Large trailing stratiform region

5. African Precipitation • Northward progression of rainfall • Banded structure Observational Data GCM GCM

6. 200 Pressure (mb)‏ African Easterly Jet ITCZ (Monsoon Rain)‏ 600 Sahara Warm Dry Air Cool Gulf of Guinea SSTs EQ 10 N 20 N 30 N Latitude West African Monsoon • Seasonally dependent thermally-induced low over African continent • Migration northward during boreal summer Ferreira (2007)

7. WAM Characteristics I • Two distinct phases (Sultan and Janicot 2003b) • Preonset – migration of southwesterly winds and ITF past 15˚N • Onset - abrupt northward shift of the ITCZ from 5˚N to 10˚N • Time-frame: April – October precipitation • Results in 99% of annual rainfall (Shinoda et al. 1999) • mid-June – September generally defines WAM period

8. WAM Characteristics II • MCSs account for estimated 80-90% of annual rainfall in Sahel (Mathon et al. 2002) • Convective portion of total rainfall: average of 65% in tropics (Schumacher and Houze 2006) • Convective portion of total area : average of 10% in tropics (Houze 1993) • Formation of MCSs (largest contributor of rainfall) is highly correlated to AEWs • SLMCS - AEJ coupling (Ferreira et al. 2009)

9. Section 2 Radar Data Analysis

10. Radar Locations • MIT – Niamey, Niger (13.49ºN, 2.17ºE) • C-band Doppler radar • Operated 5 July – 27 September 2006 • ~11250 scans for analysis • 37 MCS-scale events observed • TOGA – Praia, São Tiago (14.92ºN, 23.48ºW)‏ • C-band Doppler radar • Operated 15 August – 16 September 2006 • ~4300 scans for analysis • 6 MCS-scale events observed • NPOL – Dakar, Senegal (14.66ºN, 17.10ºW)‏ • S-band, dual polarized Doppler radar • Operated 19 August – September 30 2006 • ~3500 scans for analysis • 12 MCS-scale events observed

13. Data & System Classification • Data Resolution • MIT & TOGA : 10-minute • NPOL : 15 minute • Rmax = 150 km (130 km used for data analysis) • Feature classification structure based on a simplified version of that used by Rickenbach and Rutledge (1998) • Sub-MCS and MCS-scale events • Visual inspection - subjective

14. MIT Radar Data Quality Control • GVS software package employed for QC • Removal of non-meteorological data • Maximize meteorological echo retained • Algorithm based on a modified approach developed by Rosenfeld et al. (1995) • Generally favorable results from the QC operation • Attenuation correction for MIT site (Russell and Williams 2009) [GATE correction used for data set] • Comparison to TRMM PR showed good agreement – bias adjusted in radar data

15. Rainfall Estimation & Analysis Section 3

16. Convective-Stratiform Map SLMCS event plotted in terms of convective-stratiform components SLMCS event plotted in terms of reflectivity

17. Z-R Relationships • MIT • Z = 364R1.36 (Sauvageot and Lacaux 1995) • NPOL • Z = 368R1.24 (Nzeukou et al. 2004) • TOGA • Z = 230R1.25 (Hudlow 1979) • Global used, may use newer Conv-Strat components in future, caveat: does not exist for TOGA

18. Rainrate Timeseries

19. MCS Contributions to Seasonal Totals

20. MCS Statistics Precipitation Area Coverage

21. Sub-MCS Statistics Precipitation Area Coverage

22. Diurnal Composites MCS-scale systems Sub- MCS-scale systems Note the difference in vertical scales  MCS component dominates total

23. TRMM Diurnal Signal

24. Vertical Structure

25. Current Research Avenues • Include additional radar data • Dialogue with French group (RONSARD C-band and XPORT X-band radar) • TRMM data integration • Rainfall, OLR, and lightning flash density climatology • Vertical reflectivity profiles • Conv/Strat compositions • Aerosol (MODIS) and Lightning (WWLLN & TRMM) data integration • Reanalysis fields • Focus on disturbances that become TCs • Case study comparison • 7 (Zipser et. al 2008) or 8 (NHC, NOAA) waves – 5 of which possibly seed TCs • Add WRF modeling component – TBD after initial results

26. TRMM Climatology June August July September

27. 2006 WAM vs. Climatology

29. NPOL TOGA MIT WWLLN Lightning Distribution

30. Wave 5 Case Study

31. NPOL TOGA MIT MODIS Aerosol Distribution

32. Acknowledgements • Drs. Steve Rutledge, Rob Cifelli, Tom Rickenbach, Tim Lang • Bart Kelley, Jason Pippitt, Dave Wolfe at GSFC • Paul Kucera, Earle Williams, and Brian Russell • CEAS Fellowship for making this possible