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Composite Analyses of Tropical Convective Systems Prior to Tropical Cyclogenesis

Composite Analyses of Tropical Convective Systems Prior to Tropical Cyclogenesis. Chip Helms Cyclone Research Group 9 September 2013. Motivatio n. Questions. Why do viable systems fail to develop?

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Composite Analyses of Tropical Convective Systems Prior to Tropical Cyclogenesis

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  1. Composite Analyses of Tropical Convective Systems Prior to Tropical Cyclogenesis Chip Helms Cyclone Research Group 9 September 2013

  2. Motivation Questions • Why do viable systems fail to develop? • Why do some marginal systems develop despite the presence of inhibiting factors such as dry air, high shear, or low SSTs?

  3. Motivation Hypotheses • Why do viable systems fail to develop? • Insufficient vorticity generation and excess vorticity destruction at low and mid-levels due to conditions hostile to sustained deep convection and vorticity preservation • Why do some marginal systems develop despite the presence of inhibiting factors? • These systems develop as a result of external features acting to enhance low and mid-level vorticity generation

  4. Motivation Method Motivation • Two general approaches to studying genesis • Case Studies • Detailed analyses, may not be representative • Composite Studies • Represenative features, loss of detail • Solution: Composite on homogeneous subset • Select cases with similar structures • Make subset selections using phase space

  5. Methodology Phase Space

  6. Methodology Idealized Example Mean Vλ Idealization Deficit +

  7. Methodology Planned Variable Changes • ‘Idealization Deficit’ to ‘Vortex Idealization’ • Still measures of how close the wind field is to purely tangential cyclonic flow • Old: 0% = Cyc, 100% = Irrot, 200% = Anti • New: -100% = Anti, 0% = Irrot, 100% = Cyc • Still need to find a good moisture metric • 500-300 hPa RH > 70% coverage?

  8. Methodology Moving Beyond NHC INVESTs • Using INVEST files introduces a selection bias and reduces potential data ranges • Only NHC basins from 2005 onwards • Biased by system impact potential • Vortex detection and tracking algorithm • Based on NCEP Vortex Tracker (Marchok 2002) • 850 hPa, 700 hPa, and 500 hPa idealization • Surface pressure gradient, 850 hPa tangential velocity

  9. Methodology Example Vortex Identification 700 Ideal (3°) 500 Ideal (5°) MSLP grad. (5°) 850 Vλ(3°) 850 Ideal

  10. Methodology Example Vortex Identification 700 Ideal (3°) 500 Ideal (5°) MSLP grad. (5°) 850 Vλ(3°) 850 Ideal

  11. Methodology Tracking Algorithm • Approximate steering flow • Average of 850 hPa and 500 hPa mean wind • Implied motion must be within 60° of steering flow • Search distance • Steering wind speed? • Previous motion? • Allow system to jump any direction by up to 2° • System must last for 24 hours

  12. Future Work Future Work • Finish implementing tracking algorithm • QC tracking algorithm • Finalize phase space variables • Decide on moisture metric • Examine composites • e.g. DevvsNon-dev • Apply composite values to equations • Vorticity tendency, PV tendency • Use continuity and hydrostatic to better understand mid-level vorticity generation as a function of upper level temperature anomaly (and by extension moisture)

  13. Future Work Future Work • What is the best way to measure dry air? • 500-300 hPa RH >70% coverage over area • Radius at which azimuthal mean RH drops below 70% • RH in vicinity of 500 hPavorticity max? • Something else?

  14. END

  15. EXTRA SLIDES

  16. Motivation Genesis Process Hypothesis Shear Hydrostatic response to heating profile results in PV convergenceand positive(?) feedback due to thermal wind balance Tropopause Latent Heat Release Convergence and ascent along wave Concentration of background vorticity produces low-level vortex 500 hPa Mid-Level Vortex +PV Cooling (Melting, Evaporation, Radiation?) Deep convection fuels formation of stratiformsheilddownshear Deep convection forms along convergence line Low-Level Vortex Surface Wave Axis

  17. Results Year: 2010 N=516, Red=15

  18. Results Year: 2010 N=107, Red=6

  19. Results Year: 2010 N=25, Red=6

  20. Results Year: 2010 N=45, Red=6

  21. Results Year: 2010 N=16, Red=4

  22. REMOVED SLIDES

  23. Prior Work Theory Simpson et al. (1997) and Ritchie and Holland (1997) Concentration term Stratiform Latent Heating Mergers of PV anomalies add PV while averaging thermal properties MCS Stretching term New PV Anomaly Out of balance with thermal structure Warm anomaly growth not detailed by theory, but would be accomplished by forced subsidence or increased LHR + PV Anomaly + Evaporative Cooling Forced Convergence Forced Ascent and Evaporative Cooling Act to cool sub-cloud layer

  24. Motivation Issues with Traditional Composites • Mid-level features will appear weaker • High variability in system tilt • Vertically-aligned systems tend to be stronger • Composites will favor upright systems

  25. Methodology Methodology/Data • Locate center at 850 and 500 hPa 1) Maximum Vλ (0.5° search grid) 2) Minimum Difference of Vλand V (0.25°) 3) Minimum Difference of Vλ and V (0.10°) • Datasets: CFSRv2, HURDAT2+INVESTs • Convenient for testing methodology • CFSR: Uniform in time • Complete with all the selection bias caveats of the INVEST files

  26. Motivation Genesis Process Hypothesis Tropopause 500 hPa Surface

  27. Motivation Genesis Process Hypothesis Tropopause Vort. Max 500 hPa Surface

  28. Motivation Genesis Process Hypothesis Tropopause 500 hPa Surface

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