Understanding and constraining snow albedo feedback

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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)

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How to quantify snow albedo feedback strength?
surface albedo feedback contribution to dQ/dTs.
atmospheric component
surface component
dependence of planetary albedo on surface albedo
change in surface albedo with SAT
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atmospheric 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).
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atmospheric component
ISCCP
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.
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How to quantify snow albedo feedback strength?
surface albedo feedback contribution to dQ/dTs.
dependence of planetary albedo on surface albedo
change in surface albedo with SAT
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surface component
We can easily cal-culate ??s/?Ts 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 Ts, snow extent, and
?s in one rep-resentative ex-periment used in the
AR4 assessment.
?Ts
??s
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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.
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How important is snow albedo feedback?
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.
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calendar month
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?Ts
calendar month
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?Ts
??s
calendar month
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(No Transcript)
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observational estimate based on ISCCP
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observational estimate based on ISCCP
95 confidence interval
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What controls the strength of snow albedo
feedback?
snow cover component
snow metamorphosis component
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.
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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.
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feedback strength
effective snow albedo
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.
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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 feedbacks
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.