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Why is measuring the cloud feedback hard? Monday, June 10, 13
Why is measuring the cloud feedback hard?
Monday, June 10, 13
Why is measuring the cloud feedback hard?
C. Zhou1, M.D. Zelinka2, A. E. Dessler1, P. Yang1
1Department of Atmospheric SciencesTexas A&M University
2PCMDILawrence Livermore National Lab
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∆Rall-sky = ∆RT +∆Rq +∆Ralbedo +∆Rcloud+∆F
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∆Rall-sky = ∆RT +∆Rq +∆Ralbedo +∆Rcloud+∆F
“CERES method”:∆Rcloud = ∆Rall-sky - ∆RT + ∆Rq + ∆Ralbedo + ∆FDessler, 2010, 2013
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∆Rcl
oud
∆Ts
Regress ∆Rcloud vs. ∆Ts
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∆Rcl
oud
∆Ts
Regress ∆Rcloud vs. ∆Ts
Slope = feedback(W/m2/K)
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∆Rcl
oud
∆Ts
Regress ∆Rcloud vs. ∆Ts
Slope = feedback(W/m2/K)
∆Ts is from ENSO
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Dessler 2013 J. Climate
adju
sted
CE
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ata
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cloud feedback = ~0.5±0.75 W/m2/K
Dessler 2013 J. Climate
adju
sted
CE
RE
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ata
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∆Rall-sky = ∆RT +∆Rq +∆Ralbedo +∆Rcloud+∆F
2000
-201
1
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∆Rall-sky = ∆RT +∆Rq +∆Ralbedo +∆Rcloud+∆F
Dessler, J. Climate, 2013
2000
-201
1
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Why is there scatter?
• Bad data• Clouds are not controlled by Ts
• The effect of clouds is a net difference of two large, canceling terms
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Why is there scatter?
• Bad CERES data• Clouds are not controlled by Ts
• The effect of clouds is a net difference of two large, canceling terms
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Why is there scatter?
• Bad CERES data• Clouds are not controlled by Ts
• The effect of clouds is a net difference of two large, canceling terms
If what controls clouds correlates with Ts, then you’ll see a correlationIf not, then the cloud feedback is zero
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Why is there scatter?
• Bad CERES data• Clouds are not controlled by Ts
• The effect of clouds is a net difference of two large, canceling terms
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∆Rall-sky = ∆RT +∆Rq +∆Ralbedo +∆Rcloud+∆F
“CERES method”:∆Rcloud = ∆Rall-sky - ∆RT + ∆Rq + ∆Ralbedo + ∆FDessler, 2010, 2012
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∆Rall-sky = ∆RT +∆Rq +∆Ralbedo +∆Rcloud+∆F
“MODIS method”:direct observations of clouds + radiative transfer calculations
“CERES method”:∆Rcloud = ∆Rall-sky - ∆RT + ∆Rq + ∆Ralbedo + ∆FDessler, 2010, 2012
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MODIS method
• MODIS cloud measurements• Calculate the changes as Ts changes• apply Zelinka radiative transfer calculations
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MODIS CERES
Fig. 4 Feedback(lat,lon)
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15Dessler, 2010
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∆Ts
∆Rcl
oud
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17∆Ts
∆Rcl
oud
800-1000 hPa
50-800 hPa
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17∆Ts
∆Rcl
oud
800-1000 hPa
50-800 hPa
High clouds vs. low clouds
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17∆Ts
∆Rcl
oud
800-1000 hPa
50-800 hPa
High clouds vs. low cloudsSW vs. LW
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17∆Ts
∆Rcl
oud
800-1000 hPa
50-800 hPa
High clouds vs. low cloudsSW vs. LWThin clouds vs. thick clouds
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17∆Ts
∆Rcl
oud
800-1000 hPa
50-800 hPa
High clouds vs. low cloudsSW vs. LWThin clouds vs. thick cloudsLatitude
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Conclusions• Response of short-term ∆Rcloud and ∆Ts variations is
an important test of our models• Cloud feedback is intrinsically uncertain due to scatter
between ∆Rcloud and ∆Ts.• Scatter arises because ∆Rcloud is a balance between
canceling terms — this is a fundamental property of the problem
• Zhou et al., J. Climate, in press (preprint on my website)
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MODIS ~0.2-0.3 W/m2/Kgreater than CERES
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MODIS ~0.2-0.3 W/m2/Kgreater than CERES
MODIS ~0.7-1.0 W/m2/Kless than CERES
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MODIS ~0.2-0.3 W/m2/Kgreater than CERES
MODIS ~0.7-1.0 W/m2/Kless than CERES
Difference in NH subtropics +midlatitudes
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23High: P < 440 hPa; Low: P > 680 hPa
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breakdown into cloudheight (low: P > 680 hPa, high: P < 440 hPa)
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26Fig. 2Monday, June 10, 13
27Fig. 6Monday, June 10, 13
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