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Using AMSR-E to Estimate Cloud Feedbacks Over the Global Oceans. Roy W. Spencer Principal Research Scientist The University of Alabama in Huntsville 3 June, 2010. Low cloud feedback the largest uncertainty (reflected SW) How temperature change => cloud change has been confused with
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Using AMSR-E toEstimate Cloud FeedbacksOver the Global Oceans Roy W. Spencer Principal Research Scientist The University of Alabama in Huntsville 3 June, 2010
Low cloud feedback the largest uncertainty (reflected SW) How temperature change => cloud change has been confused with cloud change => temperature change -Spencer & Braswell, 2008; 2010 Feedback (climate sensitivity) represents the single largest uncertainty in global warming projections
Global Warming in Models isGreatly Magnified by Positive Cloud Feedback Warming in models amplified by clouds & vapor (~3 deg. C by 2100) Warming from CO2 only Satellite data suggests clouds reduce warming (~0.5°C by 2100)
Aqua CERES vs. AMSU Tropospheric Temp.suggests negative net (LW+SW) feedback(slope of regression line)
But a simple forcing-feedback modelshows a wide variety of regression slopesare possible for a givenfeedback
Aqua CERES Shows Accumulation ofEnergy….but where is the warming? CERES Radiative Fluxes Increasing CO2 forcing AMSR-E SST
Can AMSR-E CLW be used as a surrogate for CERES SW?(3-day avgs, 60N-60S Oceans, ~8 years)
CERES SW vs. Tair Suggests NEGATIVE Feedback IPCC Models: -0.95 to +0.98
CERES SW vs. Tair Suggests NEGATIVE Feedback IPCC Models: -0.95 to +0.98
AMSR-E –est. SW vs. Tair Suggests NEGATIVE Feedback IPCC Models: -0.95 to +0.98
Satellite Observations Show that Natural Cloud Variations are Potentially a Much Larger Forcing than Increasing CO2 Satellite-Observed Change in Cloud forcing (assuming LW+SW feedback parameter = 6) Change in CO2 Forcing (theoretically calculated)