Satellite Data Used to Constrain Cloud Physics
Parameterization in Climate Models
R. Bennartz1, A. Lauer2, and J.-L. Brenguier3
1University
iRAM (Khairoutdinov & Kogan)
iRAM (integral constraint method)
of Wisconsin, 2IPRC, 3Meteo-France
Observations (UWisc)
Cloud schemes in climate models should
be dependent on the model resolution.
Such schemes are often empirically tuned
so that simulations agree with observed top
of the atmosphere radiative fluxes. This
introduces large model uncertainties as it is
unclear whether tuning based on current
conditions will still be valid in global
warming scenarios.
Monthly mean liquid water path from iRAM for October 2006
obtained with the original (un-tuned) autoconversion scheme
(left) and with the integral constraint method (middle) in
comparison with satellite observations (right). Shown are the
horizontal resolutions 2°x2°, 1°x1°, 0.5°x0.5°, and 0.25°x0.25°
(from top to bottom).
We have developed a method to constrain
the formation of precipitation (both
autoconversion and accretion) in warm
clouds as parameterized in climate models.
Using satellite observations, the method
explicitly determines the scale-dependency
and
thus
eliminates
autoconversion
efficiency as a free tuning parameter. The
cloud liquid water path at different
horizontal resolutions is much closer to
observations
in
IPRC
Regional
Atmospheric Model (iRAM) model runs
using this constraint than in runs using the
conventional approach.