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CONVECTIVE INTENSITIES AND LIFECYCLES – SOME QUESTIONS FOR GCSS

CONVECTIVE INTENSITIES AND LIFECYCLES – SOME QUESTIONS FOR GCSS. Tony Del Genio, GISS with help from Yonghua Chen, Joanna Futyan. IPCC AR4 coupled AOGCMs produce a wide variety of stratiform contributions to total tropical precipitation… . …and it matters. Dai (2006).

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CONVECTIVE INTENSITIES AND LIFECYCLES – SOME QUESTIONS FOR GCSS

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  1. CONVECTIVE INTENSITIES AND LIFECYCLES – SOME QUESTIONS FOR GCSS Tony Del Genio, GISS with help from Yonghua Chen, Joanna Futyan

  2. IPCC AR4 coupled AOGCMs produce a wide variety of stratiform contributions to total tropical precipitation… …and it matters Dai (2006)

  3. Two different ideas about how moist convection affects climate sensitivity ↑LW SW   “thermostat” “adaptive iris” (Zipser, 1977)

  4. Need to know 3 things: 1. Drop size distribution 2. Size-fallspeed relationships 3. Cumulus updraft speedThen: 1. Liquid mostly rains out, short-circuits much of SST dependence of anvil 2. Primary SST dependence is thicker anvil at higher SST due to higher level of neutral buoyancy 3. Clausius-Clapeyron ensures IWP asymptote to max at high SSTResult: ~neutral cloud feedback – more ice at top offsets less ice + liquid at bottom – but depends on updraft speed, mesoscale dynamics (Del Genio et al. 2005)

  5. “Shape of the CAPE”: Rising parcels more buoyant, but over smaller depth, over land than ocean →more vigorous updrafts over landBut other ideas (deeper PBL, more aerosol loading) ocean ocean | | | lightning threshold? land land (Lucas et al. 1996; Zipser and Lutz 1994)

  6. Diagnosis of growth of cumulus updraft kinetic energy with height from large-scale thermodynamic structure (Gregory, 2001) downward cumulus pressure gradient force dilution by entrainment buoyancy due to parcel T, q excess drag due to condensed water loading Let’s take it for a spin…

  7. Land-ocean difference in updraft speed diagnosedWeak increase in updraft speed with warming over land, even less over ocean - primarily due to upward shift in freezing level 0°C 2xCO2 0°C current

  8. Budget of vertical velocity variance for midlatitude deep convective cases – would be nice to see for all CRMs and different environments (Khairoutdinov and Randall 2002)

  9. SCMs underpredict downdraft mass fluxes in a summer midlatitude case study (i.e., those that even have downdrafts) – what can CRMs tell us about how to do better? CRMs SCMs (Xie et al., 2002)

  10. GCM ENSO anomalies weaker, more zonal than observed GCM precip. TRMM TMI precip. (Chen et al. 2006)

  11. GCM stratiform rain fraction much smaller than observed, responds in opposite way to El Niño MEAN ENSO (Chen et al. 2006)

  12. Convective lifecycle composite study – using cloud top T and size to define developing, mature, dissipating stages of systems (Futyan and Del Genio 2006)

  13. TRMM PR convective/stratiform partitioning and radar reflectivity profiles develop differently over land and ocean – do CRMs do this? (Futyan and Del Genio 2006)

  14. Almost all GCMs now detrain condensate but have no mesoscale anvil dynamics – how is this related to what we know about the parent convection? land ocean (Futyan and Del Genio 2006) (Houze 1989)

  15. Why not create an archive of GCSS case study results for analysis by the community, analogous to what GCM groups have done for IPCC AR4?

  16. Summary • Basic microphysics and thermodynamics suggests convective cloud feedback nearly neutral, but depends on cumulus updraft speed and mesoscale dynamics • Large-scale predictors for updraft speed capture land-ocean and even some regional differences in GCM – what about PBL depth and aerosols? • Slightly “stronger” thunderstorms in warming climate due to freezing level shift – is this consistent with CRMs? • How can CRMs guide GCM determinations of occurrence, characteristics of cumulus-scale downdrafts? • What can our knowledge of parent convection and grid-scale parameters tell us about the formation and evolution of mesoscale anvils? • How can we “entrain” a larger community into the analysis of CRMs and thereby gain more from all these case studies?

  17. ADDITIONAL SLIDES

  18. TRMM data (Del Genio et al. 2005)

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