Applying a transfer function to correct snowfall climatology data at several automated weather stations across the United States


Measuring snowfall accumulation is a fundamental cornerstone in observing and predicting weather events. A major problem that occurs with snowfall data collection is when snowfall events are paired with high wind speeds. During such events accumulation gauges report snowfall data that is below what is expected due to the snow moving more horizontally with the wind, than falling more vertically into the gauge. To correct this discrepancy, a Double Fence Intercomparison Reference shield (DFIR) can be installed around the gauge, however the size of the shield is roughly 40 feet in diameter and is inconvenient for locations such as airports. Instead a transfer function can be applied to correct the data that is reported by the under reporting gauge by comparing gauges with smaller shielding to a DFIR-shielded gauge. Three gauges were compared: the under-reporting Pluvio in a Tretyakov shield, a second under-reporting Pluvio in a double Alter and the more accurate GEONOR in a DFIR. Looking at snowfall event data from the National Center for Atmospheric Research (NCAR) Marshall field test site in Boulder, CO, where all of these gauge/shield combinations were installed, a transfer function was developed that related the wind speed to undercatch of the Pluvio gauges. The transfer function was applied to several Automated Surface Observing Systems (ASOS) across the United states, which are operated by the National Weather Service (NWS). The data analyzed was from the following stations: Glasgow MT, Anchorage AK, Buffalo NY, and Caribou ME. When the function was applied to snowfall event data from the listed stations, a rise in accumulation data was observed in the under-reporting Pluvio.


Meteorology | Other Applied Mathematics


Scott Landolt

Lab site

National Center for Atmospheric Research (NCAR)

Funding Acknowledgement

This material is based upon work supported by the Chevron Corporation and is made possible with contributions from the National Science Foundation under Grant No. 1340110, Howard Hughes Medical Institute, S.D. Bechtel Jr. Foundation, National Marine Sanctuary Foundation, and from the host research center. Any opinions, findings, and conclusions or recommendations expressed in this material are solely those of the authors. The STAR Program is administered by the Cal Poly Center for Excellence in STEM Education on behalf of the California State University system.

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