Wintertime precipitation in regions of complex terrain, defined here as areas possessing terrain features or variations on scales < 10 km, pose special challenges for winter maintenance operations by state transportation departments. These challenges arise from a combination of the remoteness of the areas (with respect to relatively sparse, by comparison, observational networks) and the fact that the scales involves are substantially less than those that can be depicted within operational numerical weather prediction analysis systems, models, and decision support tools utilizing such data. As a result, without labor-intensive and risky manual surveys during a storm, it can be difficult to nearly impossible to accurately estimate the amount of snow, ice, and freezing precipitation that accumulates on all roadways within a region characterized by complex terrain. The surface transportation ramifications include, at minimum, decreased public safety, compromised traveler mobility, and diminished productivity of roadway users.

An improved depiction of precipitation in complex terrain can be gained by fusing observations from multiple platforms together in a precipitation estimation system such as the one developed at the University of North Dakota. This system utilizes surface observations, radar, and, to a lesser extent, geostationary satellite data streams in a manner to optimize the strengths of each data stream while mitigating their weaknesses. The complex terrain issues noted above require different approaches to the blending algorithms developed for simpler terrain environments, due to the complexity of wind effects, blocking of radar beams, and issues arising from ambiguous determination of clouds (at times) by satellite platforms within complex terrain environments, the lattermost due to complex cloud thermal profiles in tandem with pre-existing snow and ice cover.

In this presentation we discuss our early approaches towards dealing with complex terrain applications of the UND Pavement Precipitation Accumulation Estimation System (PPAES), including new rule sets introduced for dealing with radar beam blockage, wind effects, and non-monotonic thermal profiles sometimes seen in winter storms within complex terrain, especially in the Intermountain West and southeastern Alaska. Tests of our methodology will be conducted for selected case studies, which will also be utilized (along with another case study over flat terrain) to demonstrate the benefits of full utilization of Clarus data within PPAES. A brief discussion of our ideas for continued improvement in handling complex terrain will be provided.