Tropical Cloud Variability

I’ve moved to WordPress.  This post can now be found at Tropical Cloud Variability

########################
While investigating an entirely different topic, I ran across the June 25, 2005 presentation by Joel Norris of the Scripps Institute of Oceanography titled “Multidecadal Tropical Cloud Variability in Observations and GCMs”. It highlights the capabilities (or lack thereof) of GCMs at reproducing cloud cover variability. The presentation was made during the 5th International Conference on the Global Energy and Water Cycle in Costa Mesa, CA.
http://meteora.ucsd.edu/~jnorris/presentations/GEWEX2005web.pdf

I was surprised to find that, when I Googled the title in quotes, there were only two responses.

The conclusions read:
############
Conclusions
•Between 1957-1976 and 1977-1996…
observed upper-level cloud cover increased over the central equatorial Pacific
decreased over the adjacent subtropics
decreased over the western tropical Pacific
•Physically consistent changes occur in precipitation and surface atmospheric circulation.
•These changes are much larger than the expected linear response to the observed increase in Niño3.4 SST.

Conclusions
•CCSM3 AMIP simulations largely reproduce the observed central Pacific upper-level cloud changes, albeit with relatively weaker magnitude.
•CCSM3, CM2.0, and CM2.1 IPCC 20thCentury runs do not reproduce the observed cloud changes.
•Interdecadal cloud variability in the CCSM3 and CM2.0 control runs is much weaker than the observed interdecadal cloud change.
•Interdecadal cloud variability in the CM2.1 control run has more realistic amplitude (but interannual SST variability is too high).

Conclusions
•The CCSM3, CM2.0, and CM2.1 20th Century simulations (if believable) suggest that the observed tropical cloud changes are not a climate response to anthropogenic forcing.
•Multidecadal tropical cloud variability is too weak in CCSM3 and CM2.0.

############

Correct simulation of cloud cover variability at various altitudes by GCMs should be a critical area of focus. Without it, GCMs can’t properly estimate the impacts of anthropogenic and natural forcings on global and regional climate.