Global Climate publications 

The overarching goal of our global climate research is to determine what controls the climate's sensitivity to external forcing, such as an increase in greenhouse gases. The main thrust of this research is surface albedo feedback, a positive feedback thought to increase climate sensitivity: Snow and ice cover are projected to decrease in a warmer climate, and since snow and ice are generally more reflective of sunshine than bare land or open ocean, this causes an increase in net incoming solar radiation. This in turn causes additional warming, particularly in the mid to high latitudes where snow and ice are more common. Further insight into how this feedback affects simulated climate change and internal climate variability can be found in our idealized modeling study, where we "turned off" surface albedo feedback in a global climate model. Most subsequent work has focused on measuring and constraining the snow component of the feedback (snow albedo feedback), which exhibits significant spread in current climate models.

A key uncertainty surrounding surface albedo feedback is the effect of clouds on feedback strength, since clouds attenuate the expression of surface albedo anomalies in the top-of-the-atmosphere solar radiation budget. To examine this issue, we undertook an assessment of the sensitivity of planetary albedo to snow and ice variability in the satellite record of recent climate variability. We found that snow and ice anomalies account for more than half of planetary albedo variability in areas where snow and ice are common, confirming that a future snow and ice reduction would have a significant impact on planetary albedo given current cloud distributions. We then developed the means to quantify the dependence of planetary albedo on surface albedo given any observed or simulated cloud distribution. We found that current climate models all attenuate surface albedo anomalies in snow regions by about half, in agreement with satellite data. This in turn allowed us to identify surface processes as the primary source of the nearly three-fold spread in snow albedo feedback strength in current climate models. In another study, we showed that these large variations in feedback strength account for much of the spread in the climate response in heavily-populated and economically-important northern hemisphere land masses, even in seasons such as summer when the feedback is not operating directly.

Having identified the surface as the main source of spread in current simulations of snow albedo feedback, our challenge was to find a way to constrain the feedback with observations. We did this by exploiting the fact that the feedback's operation in the present-day seasonal cycle is highly analagous to its operation in climate change. We were able to measure the feedback in the seasonal cycle and identify which models are realistic. This is the first time such a concrete strategy to constrain a critical climate feedback observationally has been devised, and the work was featured in the most recent IPCC report.

An important practical aspect of bringing simulated snow albedo feedback in line with observational constraints is knowing which aspect of the models is the controlling factor leading to spread in the feedback. We found that the albedo of 100% snow-covered surfaces varies dramatically from model to model, and is the main reason for the spread. This provides a road map for the climate modeling groups to produce a more realistic feedback for the next generation of models. This will lead to significantly reduced spread in climate change predictions, particularly in northern hemisphere land masses.

Explore other aspects of global climate we study, including paleoclimate, the southern annular mode, and the planetary boundary layer...

...or go to the regional climate page.