Observational and model evidence for positive low- level cloud feedback Robert J. Burgman and Amy C. Clement Rosenstiel School of Marine and Atmospheric Sciences, University of Miami Joel R. Norris Scripps Institution of Oceanography University of California, San Diego
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Observational and model evidence for positive low-level cloud feedback
Observational and model evidence for positive low-level cloud feedback. Robert J. Burgman and Amy C. Clement Rosenstiel School of Marine and Atmospheric Sciences, University of Miami Joel R. Norris Scripps Institution of Oceanography University of California, San Diego. - PowerPoint PPT Presentation
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Observational and model evidence for positive low-level cloud feedback
Robert J. Burgman and Amy C. ClementRosenstiel School of Marine and Atmospheric Sciences,
University of Miami
Joel R. NorrisScripps Institution of OceanographyUniversity of California, San Diego
“Cloud feedbacks remain the largest source of uncertainty [of equilibrium climate sensitivity].”
-Summary for Policy Makers, IPCC AR4 WG1
“…simulation of the sensitivity of marine boundary layer clouds to changing environmental conditions constitutes, currently, the main source of uncertainty in tropical cloud feedbacks simulated by GCMs.”
-Bony and Dufresne, GRL (2005)
Here we address this issue by
(1) Examining low-frequency fluctuations in observations of low-level cloud and regional meteorology, and
(2) Using these observations to evaluate climate models.
Atmospheric response to Pacific Decadal Variability
Burgman et al (2008) use multiple EOF (9.6% variance) of 5 NCEP/NCAR reanalysis variables (t, u, v, omega, and sh) for the lowest 8 pressure levels (1000 hPa–300 hPa) in the 60S-60N region over the time period 1970 to 2003. ENSO signal is ‘‘removed’’ by extreme cross correlation at least lag (+/- 12 months).
Recent shift to cooler tropical Pacific in late 1990’s allows incorporation of satellite observations to study atmospheric response to decadal changes in SST.
Passive Microwave era
Atmospheric response to Pacific Decadal Variability
• 1990’s shift strengthening in the overturning circulation– increased subsidence – drying in the upper and middle
troposphere in NE Subtropical Pacific– shoaling of the marine boundary layer– increased lower tropospheric stability.
• Co-location of increased cloud with persistent cool SSTs indicate a possible feedback between Sc and the underlying SST on decadal timescales.
mb/stdv
Wm^2/stdv
mm/stdv
okta/stdvC/stdv
Black- total cloud
Bars- low cloud
Trend noted by Stevens et al. (2007)
ISCCP cloud data corrected for satellite view angle, and inter-calibration errors (Norris, personal communication)
Observed correlation between NE Pacific cloud and meteorology
20c3m
Is this feedback present in IPCC AR4 models?
The INM-CM3.0 adopts a more empirical approach that parameterizes low-level cloud cover as a linear function of relative humidity with coefficients that depend on temperature, altitude, land/ocean, and stratification
HadGEM1 has higher spatial resolution, more explicit cloud microphysics, interactive parameterization of cloudiness as a function of local variability in humidity, and a sophisticated planetary boundary layer mixing scheme
HADGEM1 simulates reduced NE Pacific cloud cover under doubled CO2 change
WHY?
• Model simulates regional changes in SST (increase) and LTS (increase) that are consistent with all other models
• Circulation changes are also consistent with the multi-model average
• Weaker overturning circulation (Held and Soden 2006, Vecchi and Soden 2007)
• Already observed (Zhang and Song 2006)
Conclusions• It is possible to identify decadal fluctuations in low-level cloud in the NE
Pacific in multiple, independent cloud datasets.
• Cloud changes are physically consistent with local meteorology changes: Cloud cover decreases when SST is high, LTS is weak, SLP is low, and meridional advection and subsidence are weak.
• When put to the test of simulating the relationship between cloud and thermal structure as well as circulation, only one of the current state of the art model with a physically-based parameterization of clouds passes
• Under doubled CO2, that model simulates a decrease in cloud cover in the NE Pacific along with robust changes in thermal structure and circulation
Observed decadal variability in low-level clouds as an analogue to how these clouds will change with global warming
ISCCP Correction• Satellite view angle changes removed by linearly regressing out that portion of cloud
variability associated with local changes in satellite view angle. • Satellite intercalibration error removed by regressing out from each individual grid box
time series the time series of standardized cloud cover anomalies averaged over the entire view area of successive satellites.
• This procedure will remove any real cloud cover variability occurring on near-hemispheric spatial scales but should have little impact on our regression patterns that focus on differences between regions.