towards stability metrics for cloud cover variation under climate change

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Towards stability metrics for cloud cover variation under climate change Rob Wood, Chris Bretherton, Matt Wyant, Peter Blossey University of Washington

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Towards stability metrics for cloud cover variation under climate change. Rob Wood, Chris Bretherton , Matt Wyant , Peter Blossey University of Washington. Stability and low clouds, history. Slingo (1980) - PowerPoint PPT Presentation

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Page 1: Towards stability metrics for cloud cover variation under climate change

Towards stability metrics for cloud cover variation under climate change

Rob Wood, Chris Bretherton, Matt Wyant, Peter BlosseyUniversity of Washington

Page 2: Towards stability metrics for cloud cover variation under climate change

Stability and low clouds, history• Slingo (1980)– Used model potential temperature lapse rate between ~700

and ~850 hPa as predictor of subtropical low cloud cover– Cloud data from satellites (Miller and Feddes 1971)

Page 3: Towards stability metrics for cloud cover variation under climate change

Stability and low clouds, history

• Klein and Hartmann (1993)– Used potential

temperature difference between 700 hPa and the surface (“lower tropospheric stability”) as predictor of subtropical low cloud cover

– Cloud data from volunteer ship observations (Warren cloud atlas)

Page 4: Towards stability metrics for cloud cover variation under climate change

Stability, low cloud, and climate change

• Miller (1997) thermostat hypothesis:

– Static stability expected to increase in warmed climate

– Cloud amount vs stability relationships indicate more cloud

– Negative cloud feedback

• Is LTS a suitable predictor of cloud responses to climate change?

Page 5: Towards stability metrics for cloud cover variation under climate change

Inversion strength and stability

• In the free-troposphere, d/dz=FT follows a moist adiabat from 700 hPa to the MBL top.

• Well mixed surface layer below the LCL, i.e. d/dz=0

• In the cloud layer, d/dz=CL follows a moist adiabat from the top of the LCL to the MBL top.

Wood and Bretherton (2006)

Page 6: Towards stability metrics for cloud cover variation under climate change

∆=(700 – 0) – FT(z700 – zi) – CL(zi – zLCL)

= (700 – 0) + zi(FT – CL) – FTz700+CLzLCL

(a) Neglect term with zi as this term is generally small

(b) Replace FT and CL with a single moist adiabat 850=m([T0+T700]/2, 850 hPa)

(c) Assume surface RH of 80% to estimate zLCL

Then define an estimated inversion strength (EIS) as

EIS = LTS – 850(z700 – zLCL)

EIS solely a function of surface and 700 hPa temperatures for a reference surface pressure p0=1000 hPa

EIS, a measure of inversion strength ∆

Page 7: Towards stability metrics for cloud cover variation under climate change

Subtropicaland tropical

Midlatitude

EIS is a far better predictor of low cloud amount than LTS over a wider temperature range

LTS/EIS and low cloud amount

Page 8: Towards stability metrics for cloud cover variation under climate change

Williams et al. (2006)

Change in LTS (K)

Low cloud amount in an ensemble of 2xCO2-control GCM simulations is poorly estimated using LTS’ (for

which a general increase is predicted)

Much better agreement with change in saturated stability

(related to EIS’)

Page 9: Towards stability metrics for cloud cover variation under climate change

Multiscale approach to the problem

• We use a suite of model simulations– Climate model runs from CAM and GFDL (SST+2K

and 2CO2/SOM, Wyant et al. 2006)

– SP-CAM global run with SST+2K (Wyant et al. JAMES) and 4CO2/fixed SST change.

– CRM and LES runs using forcings derived from SP-CAM simulations for different stability percentiles (Blossey et al. JAMES)

– Uses only data from tropics (30oS-30oN)

Page 10: Towards stability metrics for cloud cover variation under climate change

Cloud amount vs LTS (SST+2K)

controlSST+2K

Klein and Hartmann

Page 11: Towards stability metrics for cloud cover variation under climate change

Cloud amount vs EIS (SST+2K)

Wood and Bretherton

Page 12: Towards stability metrics for cloud cover variation under climate change

Cloud vs LTS (SST + 2K, with CRM and LES runs)

Page 13: Towards stability metrics for cloud cover variation under climate change

Cloud vs EIS (SST + 2K, with CRM and LES runs)

Page 14: Towards stability metrics for cloud cover variation under climate change

EIS and cloud changes

from Bony and Dufresne (2005)

The three models studied here have significant increases in EIS

However, most climate models show decreasing SWCF in the tropics in AR4 runs

Why the discrepancy?

Page 15: Towards stability metrics for cloud cover variation under climate change

SST+2K vs 2xCO2/SOM

Somewhat weaker low cloud changes for 2xCO2 runs

Page 16: Towards stability metrics for cloud cover variation under climate change

SST+2K vs 4xCO2/fixed SST (SP-CAM)

Completely different low cloud changes for 4xCO2 runs

Page 17: Towards stability metrics for cloud cover variation under climate change

MBL depth for control and perturbed runs

MODIS Obs

MBL depth decreases

despite reduced subsidence from CO2 FT warming

MBL turbulence weakens

SST+2K

N×CO2

Page 18: Towards stability metrics for cloud cover variation under climate change

Conclusions, SST+2K

• CAM3, AM2, and SP-CAM under SST+2K show large LTS increases while low cloud cover changes increase more slowly than predicted by LTS

• These models under SST+2K all show increases in EIS too. Cloud changes in CAM and SP-CAM increase somewhat more rapidly than predicted by EIS

• CRM driven by SP-CAM output consistent with SP-CAM• LES driven by SP-CAM output not consistent with SP-CAM

Page 19: Towards stability metrics for cloud cover variation under climate change

Conclusions

• Cloud responses to changing CO2 very different from those due to SST changes, even in slab-ocean models. CO2 induces additional atmospheric radiative forcing at the top of the MBL in addition to warming the surface.

• CO2 perturbs the relationship between MBL depth and EIS whereas SST+2K does not

• MBL depth changing for a given EIS consistent with cloud changes even at constant EIS

• Hypothesize that a single metric may be insufficient to capture the low cloud changes from radiative forcing by CO2 and from increased SST.

Page 20: Towards stability metrics for cloud cover variation under climate change

Doubling CO2 stabilizes lower troposphere independent of SST changes

• Standard tropical profile, Fu-Liou RT model

Page 21: Towards stability metrics for cloud cover variation under climate change

EIS, stability-driven changesfree

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A possible two-metric phase space

Page 22: Towards stability metrics for cloud cover variation under climate change

The end

Page 23: Towards stability metrics for cloud cover variation under climate change

Why different sensitivity for SST+2K vs NxCO2?

Models all show decreasing MBL depth

(defined as 50% RH level) with increasing stability

Page 24: Towards stability metrics for cloud cover variation under climate change

Comments on previous

• CRM forced from SP-CAM has larger low cloud amounts, while LES gives much smaller cloud amounts than parent model.

• SWCF for CRM similar to that from parent model, while LES is still much weaker

• Climate changes in CRM similar to that in parent model

Page 25: Towards stability metrics for cloud cover variation under climate change

Comments on previous

• All models show decreasing MBL depth with increasing EIS• SST+2K runs tend to deepen MBL depth or stay same whereas

NxCO2 runs tend to result in shallower boundary layers. • The SP-CAM results particularly troublesome to interpret as

4xCO2 run shows huge decreases in MBL depth but much weaker cloud cover changes. So increased CO2 results in shallower MBL but with lower cloud cover.

• Could this be explained by methodology for compositing (i.e. using percentiles)?

Page 26: Towards stability metrics for cloud cover variation under climate change

SWCF vs LTS and EIS

LTS EIS

Page 27: Towards stability metrics for cloud cover variation under climate change

SWCF vs LTS and EIS (with CRM and LES runs)

Page 28: Towards stability metrics for cloud cover variation under climate change

Comments on previous

• LTS better predictor of current climate model cloud cover than EIS

• Increases in LTS are large in all models (1K). Corresponding increases in low cloud cover are roughly consistent with KH93 for CAM and SP-CAM, but clouds decrease in AM3 despite large LTS increases

• Increases in EIS are seen in all models but these are much weaker than LTS increases (order 0.3-0.5K). CAM3 and SP-CAM cloud cover increases more strongly than expected from low cloud-EIS relationship of Wood and Bretherton.

• Similar conclusions drawn for SWCF vs LTS/EIS