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Tropical Convection: A Product of Convergence

Tropical Convection: A Product of Convergence. But What Drives Convergence?. ONE THEORY: CISK Conditional Instability of the Second Kind A Positive Feedback Mechanism . . . . CISK: Convergence Driven by LH Release Aloft. Is this the Whole Story?. Other Process…. Barotropic Instability

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Tropical Convection: A Product of Convergence

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  1. Tropical Convection: A Product of Convergence

  2. But What Drives Convergence? • ONE THEORY: CISK • Conditional Instability of the Second Kind • A Positive Feedback Mechanism . . .

  3. CISK: Convergence Driven by LH Release Aloft Is this the Whole Story?

  4. Other Process…. • Barotropic Instability • Sea Surface Temperature Gradients (Lindzen and Nigam) *All processes play a role to some extent*

  5. But how do they compare? General Circulation: Conv driven by upper-level Div Local Circulation: Conv driven by SST gradient

  6. Basic Hypothesis: -Momentum Balance of Hadley circulation aloft does not account for total low-level moisture Convergence -SST directly influence Convection apart from thermodynamic properties -Variation or Gradient in SST pattern important for Convection In Tropics Small Changes Large Influence

  7. Environment of Tropical Ocean

  8. Basic Approach/Methodology • ATS capped at 700mb (height of inversion) • Inversion decouples upper ATS from below • No influence from LHR in cumulus towers (CISK) • Convergence in lower layer driven by SST Gradient Pressure Gradient • Well Mixed BL SST and gradients correlated in vertical • Model Eddy (anomalous) surface flow • Zonally averaged flow well represented by Hadley Circulation • Compare model with observational data (FGGE) in order to determine relative importance of low-level forcing in eddy convergence

  9. Model Development Vertical Temp structure of BL linear function of SST: Flow in Boundary Layer Incompressible: Given Temp & Density Pressure via Hydrostatic Eq

  10. Momentum Equations: Balance of PGF, Coriolis, Friction Zonal Component: Coriolis PGF Turbulent Stress (friction) Meridional Component

  11. Compute Eddy SLP from Observed temperature using:

  12. Initial Results :

  13. Major Approximation/Error: -Lindzen & Nigam assume top of Boundary Layer (taken to be 700mb or 3km) is flat and does not vary in time -Convection occurs instantaneously -These simplifications are later revised in order to Get realistic flow pattern in the model (back-pressure effect)

  14. Back-Pressure adjustment -In original model, BL (700mb sfc) is a rigid sfc that can’t be modified -In reality, vertical motion above SFC LOW raises the top of the BL (700mb sfc) and this adiabatic expansion acts to cool the lower tropopause raises pressure Negative feedback -This cooling is eventually dampened by ample LHR ; But it takes time for convective clouds to develop (~30mins)

  15. 2 Major New Variables Introduced: = Deviation of 700mb layer from flat 3km sfc Proportional to uptake of mass via convergence Proportional to cooling of tropopause * If large cooling offsets warm SST Convergence suppressed = Time Scale ~ Cloud development time Represents adjustment time of ATS to reach steady state *If small, LHR quickly compensates cooling from h’ Convergence excessive

  16. Revised Equations in Model • Allows for modulation of 700mb sfc with upward vertical motion variation in top of BL

  17. Note new variables directly proportional to each other: time scale conv/div

  18. New Solutions • If tau=30s looks like old model (excessive convergence) • If tau=3hrs Weak to no convergence (Big back-pressure) • If tau=30mins resembles flow from real data

  19. Solution with tau=30mins :

  20. Both Gradients Important Forcing from Meridional -Represents ITCZ better Forcing from Zonal -Represents SPCZ better

  21. Criticisms/Notes Questionable parameterizations -3km can be considered too high for mean Boundary Layer -Time Adjustment of 30 mins chosen b/c it looks the ‘nicest’ (No theoretical Justification) Poor Results for NH Winter -Boundary Layer is shallower -Greater influence from motions aloft Are Results repeatable -How does model compare against other reanalysis and data sets (future work) *Conceptual Problem*

  22. Inherent Ambiguity: What drives what?Low level vs. Upper Level SST gradient Pressure gradient Low-level flow (Lindzen Nigam) Deep Convection/LHR Pressure gradient Low-level flow (Gill & others) *Different Forcing can yield similar results *Each Mechanism only valid given assumptions made

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