Climate Feedbacks

Improving predictions of summer climate change in the United States

Across vast, agriculturally intensive regions of the United States, the spread in predictions of summer temperature and soil moisture under global warming is curiously elevated in current climate models. This is apparent in a graphic showing the intermodel standard deviation of the anthropogenic change in summer temperature (deg C) and the fractional change in summer soil moisture over the U.S. and Canada. In the U.S., some models show modest warming of 2-3C and little drying or slight moistening by the 22nd century, while at the other extreme are simulations with warming as large as 7-8C and 20-40% reductions in soil moisture. This region of large spread arises from differences in simulations of snow albedo feedback. Evidence of this is seen in the correlation between snow albedo feedback strength in each model and the models' corresponding temperature and soil moisture responses. The reason for this connection is the following: During winter and early spring, models with strong snow albedo feedback exhibit large reductions in snowpack and hence water storage. This water deficit persists in summer soil moisture, with reduced evapotranspiration yielding warmer temperatures.

Comparison to observations from the seasonal cycle suggests these inter-model differences in snow albedo feedback are excessive, but boosts confidence in the multi-model mean. (We demonstrated the utility of the current seasonal cycle for observing snow albedo feedback strength in a previous study.) We estimate that if the next generation of models were brought into line with observations of snow albedo feedback, the unusually wide divergence in simulations of summer warming and drying over the U.S. would shrink by up to half. This is demonstrated by a final figure showing the original spread in temperature and soil moisture in current models (top), and the spread in these variables when the spread that can be linearly related to intermodel variations in snow albedo feedback is removed (bottom). Clearly, a systematic effort to constrain snow albedo feedback in climate simulations would result in substantially improved U.S. climate prediction on decadal to centennial time scales.

Download the publication (Hall et al. 2008) describing these results in more detail.

Alex Hall, Xin Qu, and David Neelin (UCLA Atmospheric and Oceanic Sciences Dep't) make up the team that performed this research.