9.5 Creating a Climatological Snowfall Map for the NWS Buffalo County Warning Area Using an Ordinary Least-Squares Regression of PRISM Data with Residual Correction Scheme

Wednesday, 10 January 2018: 2:30 PM
Room 17A (ACC) (Austin, Texas)
Jefferson Wood, NWS, Buffalo, NY

Climatological maps of temperature and precipitation are commonly available to scientists and the public, however, due to inherent complexities involved in snowfall measurement, high-resolution snowfall maps of are very rare. An updated 30-year snowfall climatology map of the WFO Buffalo, NY county warning area (CWA) is constructed from NCDC 1981-2010 Normals point data using a GIS-driven objective analysis technique, replacing the previous map that was constructed using human-expert techniques. The new technique, henceforth referred to as Ordinary Least-Square Regression with Residual Correction (OLRwRC), involves a regression analysis of 30-year normal snowfall point data across the CWA against values derived from gridded cold-season precipitation data, obtained from the PRISM Climate Group. The resulting regression equation is applied to the gridded PRISM precipitation data to create an initial snowfall map, which is then corrected using an interpolated grid of the residuals from the regression. The OLRwRC map is compared to maps produced using traditional spatial interpolation techniques, such as inverse distance weighting and natural neighbor, and it is found that the OLRwRC map reveals previously unresolved details and highlights the significant impacts of topography on snowfall across the area missed by traditional statistical interpolation techniques. Nonetheless, as with any interpolation scheme, the results are not perfect, as there areas where snowfall is inaccurately represented, primarily due to a scarcity of observation sites across portions of the study area. However, this technique represents a significant step forward in the representation of snowfall climatology that can likely be applied on a broader scale across the region, albeit with some adjustments likely required for application to other areas.
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