Understanding and constraining snow albedo feedback Alex Hall and Xin Qu UCLA Department of Atmospheric and Oceanic Sciences 2nd International Conference on Global Warming and the Next Ice Age and Aerosol Workshop on Climate Prediction Uncertainties July 2006 How do we measure it? (Qu and Hall 2005) How important is it? (Qu and Hall 2006) How can we constrain it observationally? (Hall and Qu 2006a) What processes control its strength? (Hall and Qu 2006b)

dependence of planetary albedo on surface albedo change in surface albedo with SAT surface albedo feedback contribution to dQ/dT s. How to quantify snow albedo feedback strength? atmospheric component surface component

Recently, we developed a method to calculate the dependence of planetary albedo on surface albedo in NH extratropical land masses based on standard model output (including cloud optical depth, cloud cover, and surface albedo). atmospheric component

The models agree with each other to within about 10%, with a typical surface albedo anomaly being associated with a planetary albedo anomaly about half as large. The models also agree with an estimate of the observed value of this quantity, based on the ISCCP data set. ISCCP atmospheric component

dependence of planetary albedo on surface albedo change in surface albedo with SAT surface albedo feedback contribution to dQ/dT s. How to quantify snow albedo feedback strength?

We can easily cal- culate  s /  T s in models by averaging surface albedo and surface air tem- perature values from the beginning and end of transient climate change experiments. Here is the evolution of springtime T s, snow extent, and  s in one rep-resentative ex- periment used in the AR4 assessment.  s TsTs surface component

The sensitivity of surface albedo to surface air temperature in land areas poleward of 30N exhibits a three-fold spread in the current generation of climate models. The divergence in snow albedo feedback results overwhelmingly from the surface component.

Correlation between local annual-mean temperature response and snow albedo feedback strength. Variations in snow albedo feedback strength are primarily responsible for the variations in temperature response over large portions of northern hemisphere landmasses. How important is snow albedo feedback?

calendar month

TsTs

 s TsTs

observational estimate based on ISCCP

95% confidence interval

What controls the strength of snow albedo feedback? We can break down snow albedo feedback strength into a contribution from the reduction in albedo of the snowpack due to snow metamorphosis, and a contribution from the reduction in albedo due to the snow cover retreat. snow cover component snow metamorphosis component

What controls the strength of snow albedo feedback? snow cover component snow metamorphosis component It turns out that the snow cover component is overwhelmingly responsible not only for the overall strength of snow albedo feedback in any particular model, but also the intermodel divergence of the feedback.

Because of the dominance of the snow cover component, snow albedo feedback strength is highly correlated with a nearly three-fold spread in simulated effective snow albedo, defined as the albedo of 100% snow- covered areas. Improving the realism of effective snow albedo in models will lead directly to reductions in the divergence of snow albedo feedback. feedback strength effective snow albedo

Conclusions How important is snow albedo feedback? The roughly three-fold spread in simulations of snow albedo feedback strength contributes to much of the spread in the temperature response of global climate models in northern hemisphere land masses. How to constrain it observationally? The feedback’s simulated strength in the seasonal cycle is highly correlated with its strength in climate change. We compared snow albedo feedback's strength in the real seasonal cycle to simulated values. They mostly fall well outside the range of the observed estimate, suggesting many models have an unrealistic snow albedo feedback. What controls its strength? The albedo reduction due to the retreat of snow cover in a warming climate is dominant over the reduction in albedo due snowpack metamorphosis in every model. This points to the importance of correct simulation of the albedos of snow-covered surfaces for realistic simulation of snow albedo feedback. These results map out a strategy for targeted climate system observation and further model analysis to reduce divergence in climate sensitivity.