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Simple tropical models and their relationship to GCMs

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Title: Simple tropical models and their relationship to GCMs


1
Simple tropical models and their relationship to
GCMs
  • Adam Sobel, Columbia
  • Chris Bretherton, U. Washington

2
  • All aspects of tropical climate depend on tightly
    coupled feedbacks between convection, clouds,
    radiation, SST, surface fluxes
  • In characterizing feedbacks, useful to look at
    local relationships between different physical
    variables (scatter plots) takes out geography
  • Observed relationships can be used to constrain
    models of all sorts
  • In GCMs, relationships can be diagnosed and
    compared to obs, and to other GCMs
  • In simple models, relationships can be put in via
    bulk parameters, and sensitivity relatively
    easily understood may help to interpret GCM
    biases?

3
E.g. water vapor path vs. precip,from satellite
microwave
4
Normalizing to saturated WVP (mass-weighted
column mean RH) gives better fit
5
Sensitive test for GCMsCCM3.6
too much rain at low wvp (shallow cloud regions?)
6
Longwave cloud forcing (TOA),CCM3.6
7
Shortwave not as good -gtcoupled model errors
8
Simple models
  • Neelin-Zeng Quasi-equilibrium tropical
    circulation model (QTCM)
  • Single baroclinic mode for temperature, moisture,
    wind, barotropic mode for wind
  • Betts-Miller type convection
  • Underlying construction (single mode etc.)
    similar to models by Raymond, Emanuel, others
  • QTCM is good bridge between GCMs, simple models
  • We work with further reductions of QTCM (assumed
    symmetries etc.)

9
Idealized Walker circulation (Bretherton Sobel
2002)
  • 1-dimensional (longitude) domain, sinusoidal SST,
    no rotation
  • Temperature assumed constant in x, but unknown
  • QTCM vertical structures
  • Convective scheme hard adjustment or strict
    quasi-equilibrium
  • Convective greenhouse feedback on radiative
    cooling RRclr rP, r0.2
  • Fixed surface wind speed exchange coeff.

10
Equations
  • u is baroclinic, has sign of upper trop. wind

In convective regions, qT. Gross moist
stability MMs Mq. Aq is constant coef. P
diagnosed from moist static energy plus (1).
11
System is very sensitive to cloud-radiative
feedback parameter
12
And also gross moist stability (Neelin Held
1987 Yu et al. 1998 Raymond 2000). r modifies
effective GMS
vertical motions efficiently
inefficiently export/import energy Radiative
cooling larger smaller
13
Same system with ocean mixed layer (Sobel 2003
Peters Bretherton 2004)
  • set SWCFLWCF (both linear in precip as before)
  • Finite conv adj time P(q-T)/?
  • Forcing is background sfc rad ocean heat xport
    divergence, linear in x
  • Now size of convective region much less dependent
    on r, because SWCF counteracts LWCF by cooling
    the surface but other parts of the solution,
    such as SST in convective region, are sensitive
    to r
  • For large r can get instability to coupled
    oscillations on intraseasonal/subannual time
    scale (Sobel Gildor 2004)

14
Insights
  • In these models, moisture is key horizontally
    varying fields. Controls precip, and through
    that, CRF.
  • Key parameters are gross moist stability, and the
    constants relating WVP and CRF to precip

15
How is this relevant to biases in GCMs?
  • Sensitivity to parameters such as r, GMS,
    convective time scale (WVP vs. precip) in simple
    models is relatively straightforward to
    understand. These same parameters can be
    diagnosed from GCMs. We can thus place the GCM
    in the parameter space of the simple model, which
    might if the simple model has enough of the
    right stuff in it - give us some insight into why
    the GCM behaves as it does. Would be especially
    interesting to compare these parameters in
    several different GCMs.
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