Adaptive Mapping of Design Ground Snow Loads in the Conterminous United States

Abstract

Recent amendments to design ground snow load requirements in current US standards have reduced the size of case-study regions by 91% from what they were in previous standards, primarily in western states. This reduction is made possible through the development of highly accurate regional generalized additive models (RGAMs), stitched together with a novel smoothing scheme implemented in the R software package remap, to produce the continental-scale maps of reliability-targeted design ground snow loads available in current standards. This approach allows for better characterizations of the changing relationship between temperature, elevation, and ground snow loads across the conterminous US (CONUS). RGAMs are shown to have 10% or better improvement in mean absolute mapping error in two independently created data sets when compared with traditional mapping techniques. Structures must be able to withstand environmental stresses without collapsing, including snow. Design ground snow loads are estimated using snow measurements taken at weather stations throughout the US. Mapping techniques allow design ground snow loads to be estimated at regions between weather stations. This paper describes a regional approach for mapping design ground snow loads in CONUS and demonstrates the improved accuracy of the approach, relative to previous methods, on two independently created national data sets.