Thursday, January 09, 2014, 12:00PM - 1:00PM
ARC room 620
Climate in mountainous regions is often as heterogeneous as the underlying local topography, and therefore is underresolved by traditional climate models, as it requires high horizontal resolution data. For this reason, much of my work has been in developing dynamically downscaled datasets that use atmospheric reanalyses—the closest datasets we have to represent large-scale atmospheric "truth"—as inputs to drive higher-resolution simulations.
This talk will briefly explore some aspects of climate extremes in complex terrain where dynamically downscaled data lends insight to the underlying physical processes. I will then focus more deeply on orographic precipitation processes in the U.S. Intermountain West, using both dynamically downscaled simulations along with a simple model of orographic precipitation, to understand what processes dominate in determining precipitation distribution in complex terrain. I'll first investigate the relative contributions of integrated water vapor transport magnitude and incidence angle on topography in determining precipitation amounts and distribution in a very strongly forced, but dynamically rather simple, case. I'll follow this with an example of the more complicated situation where the air ahead of the barrier is statically stable and show how this complication impacts precipitation distribution.