Understanding and Constraining Future Arctic Climate Change

University Of California-Los Angeles, Los Angeles CA

Investigators

Abstract

Hall 0714083 UCLA Funds are provided to understand and constrain the important arctic sea-ice-albedo feedback (SIAF) in the current generation of climate models. To reduce the spread between simulations of feedbacks in models, it is necessary to identify observational constraints that can be used to evaluate the feedback's realism. The central difficulty here is that the feedbacks are aspects of future climate, and cannot be observed directly. To circumvent this, the strategy of the principal investigator (PI) is to quantify simulated SIAF strength as it impacts the most observable and prominent example of externally-forced climate variability in the extratropics - the current climate's seasonal cycle. If simulated SIAF strength in the current seasonal cycle is an excellent predictor of feedback strength in the climate change context, then observational constraints on the feedback in the current seasonal cycle should lead directly to reductions in the intermodel spread of feedback strength in the future climate predictions. This appears to have been the case with the PI's previous work on snow albedo feedback, and a strategy for producing similar results for SIAF that takes into account the feedback's peculiarities has been outlined. An essential counterpart to this effort will be determining which aspects of current climate simulations influence SIAF strength and its intermodel spread the most. The PI has developed a mathematical framework to facilitate these diagnoses from model output. It is anticipated that the work will focus on sea ice albedo parameterizations, but will also examine the role of arctic clouds in modulating SIAF, as well as the role of ocean-sea-ice interaction.