cpt.UCLA

Our work is motivated by two observations

‣ our understanding of cloud feedbacks is zonally symmetric.

‣ all pbl parameterizations strive to well represent the mixed layer limit (at the right time).

http://www.atmos.ucla.edu/~brianpm/ucla_cpt.html

Bjorn Stevens, Yunyan Zhang, Brian Medeiros

how earth-like are the aqua-planets?

‣ Motivation

‣ Methodology - the experiments

‣ Some results

GFDL AM2

NCAR CAM3

‣ A few extra CAM3 figures

‣ Discussion topics & the future

aqua planet - what & why

simplified framework to help isolate feedbacks

‣ full 3D GCM with dynamics and physics

‣ prescribed SST‣ no land or sea-ice‣ perpetual equinox solar conditions (no seasons)‣ gives a zonally symmetric configuration to compare with simple

models

useful for model intercomparison

‣ Is aqua planet sensitivity similar to full GCM?

‣ Do different GCMs have similar aqua planets?

start with full model (dynamics + physics)

remove zonal asymmetry (land + sea-ice)

prescribe SST (APE analytic expressions: “aqua,” “flat,” “qobs”)

Warm SST by ≈ 2 K

‣ Where to have SST = 0?‣ Preserve ∂ySST (or do as

good as we can)

“AQUA” SST sin∝ 2(α11ϕ)“FLAT” SST sin∝ 4(α22ϕ)

APE SSTs

SST + 2

warming equatorward of ~60 latitude

‣ maximum SST = 29 C (at equator)

‣ match gradient at a single latitude

‣ minimize RMS difference

result is a modifed cess perturbation in the tropics and midlatitudes

high latitude SST remains at 0 C

“QOBS” SST = 0.5( “AQUA” + “FLAT” )

aqua planet +2K

‣ NCAR CAM3 & GFDL AM2 were run in the three APE configurations for 3.5 years each

‣ +2K runs were performed for all three APE SST profiles

‣ An additional “Cess” experiment was included with the full GCM (land & sea-ice)

CAM3 global sensitivity‣ aqua planets slightly less

sensitive than “cess”

‣ “Cess” has largest sensitivity, and smallest albedo changes

‣ climate sensitivity parameter: ratio of change in surface temperature to change in direct radiative forcing (dominated by change in OLR).

‣ cloud feedback parameter: ratio of change in total cloud forcing to direct radiative forcing.

‣ CAM cloud feedback is negative in all configurations

AM2 global sensitivity

‣ “Cess” has largest sensitivity, and smallest albedo changes (again)

‣ AM2 cloud feedback is positive in “Cess,” but negative in aqua planets (only globally)

‣ albedo change due almost entirely to cloud albedo for aqua planets, but not “Cess”

CAM3 tropical (30-30) sensitivity

AM2 tropical (30-30) sensitivity

compare global cloud response

‣ Very similar TOA radiative changes

‣ AM2 global cloud feedback changes sign in aqua planet

‣ “qobs” consistently most similar to full GCM

compare tropical cloud response

TOA radiative forcing larger in CAM

‣ CAM radiative forcing similar to global forcing

‣ AM2 forcing about half global value

Cloud feedback opposite sign between models

intra-GCM tropical cloud feedback consistent in sign and magnitude

CAM3 clouds

‣ Aqua planets have larger changes in cloud fraction

‣ total & low cloud fraction change is consistent among configurations

‣ “qobs” is most CAM-like

AM2 clouds

‣ Tropics (30S-30N) show decrease in total cloud

‣ only “cess” shows increase in high clouds.

‣ Tropical total and low cloud changes have same sign among runs.

“qobs” cloud fractions

aqua planet convective precipitation

‣ very similar double ITCZ in QOBS

‣ change in +2 case is quite similar

‣ other configurations are also very alike, with exception of “aqua” (single ITCZ in AM2)

CAM vertical motion

‣ seasonal effects make “cess” look weakest

‣ wider SST maximum makes wider spaced ITCZs and weaker circulation

‣ double ITCZ in “qobs” and “flat” (and equatorial subsidence)

CAM liquid water

‣ more intense circulation in “aqua” and “qobs” (area of convection/susidence)

‣ warmer climate produces more cirrus in convective regions and more stratus in subsidence

‣ warmer climate has less mid-level cloud

‣ Aqua planet configuration does seem to have similar climate sensitivity as full GCM

‣ qualitatively captures response in omega space

‣ discriminates between AM and CAM cloud feedbacks

‣ reasonable predictor of low cloud response

‣ Caveats (how big, how long, how right?) more work...

‣ A laboratory for investigating climate feedbacks?

summary