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Most likely strength of surface albedo feedback in future climate change

PI: Xin Qu
Institution: University of California, Los Angeles
Additional Investigators: Alex Hall
Abstract:
We will attempt to determine the most likely strength of surface albedo feedback in future climate change based on PCMDI datasets and some observational datasets. First, we will calculate surface albedo feedback parameters based on the equilibrium climate change simulated by the models in the PCMDI dataset. We will also calculate surface albedo parameters based on the mixture of internally-generated and externally-forced climate variability simulated in scenario runs by the same models. We will analyze the period of the scenario runs corresponding to the observed climate record. Then we will calculate the same surface albedo parameters based on observational datasets, such as the ISCCP D-series flux datasets. This observational result will allow us to determine which models' scenario run surface albedo feedback parameters are most realistic. Next we will regress the scenario run surface albedo parameters onto equilibrium climate change surface albedo feedback parameters to determine how statistically significant the relationship between them is. If we find a highly statistically significant relationship, we can then determine which which equilibrium climate change feedback parameters are most likely to be realistic. If successful, this work will contribute towards reducing the uncertainty
in equilibrium climate sensitivity, and could provide a paradigm for observationally-based evaluation of other climate feedbacks.
Publications:
  • Hall. A., and X. Qu, 2006: Using the current seasonal cycle to constrain snow albedo feedback in future climate change. Geophys. Res. Lett., 33, L03502, doi: 10.1029/2005GL025127. Abstract. Full Article. Edit.
  • Qu, X., and A. Hall, 2006: Assessing snow albedo feedback in simulated climate change. J. Climate. In press. Abstract. Full Article. Edit.

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