ABSTRACT

Hot and and cold extremes of surface air temperature have a clear association with atmospheric circulation patterns, for instance the coldest temperatures over the continental US are associated with the southward flow of air behind the polar front while summer heat waves are associated with stalled high pressure systems. But while the influence of atmospheric circulation is evident from weather maps, the underlying land surface can also affect the severity of hot and cold events. For instance the maximum surface air temperature during a heat wave could be lower due to evaporative cooling if the soil is wet, thus soil moisture could play an important role in limiting the magnitude of temperature fluctuations. Other surface properties including snow cover, reflectivity, and surface roughness are thought to influence surface air temperature variability, but the extent of the influence of these properties is difficult to quantify.

This project examines the effects of atmospheric circulation and land surface properties on surface air temperature variability, seeking to determine 1) the fraction of temperature variability that can be explained by the large-scale atmospheric circulation alone, and how this varies as a function of location and season; 2) the key pathways through which the land surface can influence surface air temperature after controlling for the large-scale atmospheric circulation; and 3) the extent to which the land surface can modify the magnitude of extreme events, and may allow for subseasonal to seasonal predictability. The PIs use statistical methods to generate best-fit surface air temperature patterns based solely on the atmospheric circulation aloft, then compare the statistics of these circulation-derived temperature patterns to the actual temperature statistics to identify regions and seasons where differences in the two imply a strong role for surface properties. This observational analysis is followed by numerical experiments with a hierarchy of models to understand the physical mechanisms through which the land surface affects temperature variations. The model hierarchy includes the Community Atmosphere Model (CAM) coupled to the Simple Land Interface Model (SLIM), a land surface model configured to allows direct control of important land surface properties. Results of sensitivity studies carried out with CAM-SLIM and other model configurations are applied to the analysis of recent heat waves in North America, Europe, and Australia.

Temperature extremes have numerous effects on human well being through impacts such as mortality, crop losses, and infrastructure failure. Better understanding of the role played by land surface properties in determining the severity of these extremes could prove useful in anticipating their occurrence, and the extent to which their frequency and intensity may be affected by climate change. The work will also benefit the broader scientific community through the development and dissemination of SLIM, which will be made available as part of a public release of the Community Earth System Model. The project also includes education and outreach through the Significant Opportunities in Atmospheric Research and Science (SOARS) program, and supports a graduate student and a postdoctoral research associate.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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