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Published bySharlene Carmella Ford Modified over 9 years ago
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Tropical Convection: A Product of Convergence
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But What Drives Convergence? ONE THEORY: CISK Conditional Instability of the Second Kind A Positive Feedback Mechanism... ONE THEORY: CISK Conditional Instability of the Second Kind A Positive Feedback Mechanism...
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CISK: Convergence Driven by LH Release Aloft Is this the Whole Story?
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Other Process…. Barotropic Instability Sea Surface Temperature Gradients (Lindzen and Nigam) *All processes play a role to some extent* Barotropic Instability Sea Surface Temperature Gradients (Lindzen and Nigam) *All processes play a role to some extent*
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But how do they compare? General Circulation: Conv driven by upper-level Div Local Circulation: Conv driven by SST gradient General Circulation: Conv driven by upper-level Div Local Circulation: Conv driven by SST gradient
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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 -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
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Environment of Tropical Ocean
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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 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
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Model Development Vertical Temp structure of BL linear function of SST: Flow in Boundary Layer Incompressible: Given Temp & Density Pressure via Hydrostatic Eq Vertical Temp structure of BL linear function of SST: Flow in Boundary Layer Incompressible: Given Temp & Density Pressure via Hydrostatic Eq
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Momentum Equations: Balance of PGF, Coriolis, Friction Zonal Component: Coriolis PGF Turbulent Stress (friction) Meridional Component Zonal Component: Coriolis PGF Turbulent Stress (friction) Meridional Component
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Compute Eddy SLP from Observed temperature using:
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Initial Results :
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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) -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)
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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) -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)
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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 = 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
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Revised Equations in Model -Allows for modulation of 700mb sfc with upward vertical motion variation in top of BL -Allows for modulation of 700mb sfc with upward vertical motion variation in top of BL
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Note new variables directly proportional to each other: time scale conv/div
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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 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
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Solution with tau=30mins :
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Both Gradients Important Forcing from Meridional -Represents ITCZ better Forcing from Zonal -Represents SPCZ better Forcing from Meridional -Represents ITCZ better Forcing from Zonal -Represents SPCZ better
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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* 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*
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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 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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