Date of Award


Document Type

Honors Thesis

Degree Name

Bachelor of Science


Atmospheric and Environmental Sciences

Advisor/Committee Chair

Junhong Wang


This research project aims to examine and enhance the performance of the New York State Mesonet (NYSM) Snow Accumulation Estimation. The NYSM is a state-of-the-art network of 126 standard weather stations located across the state of New York, collecting high-quality meteorological data to improve forecast accuracy, reduce uncertainty, and mitigate harm. All NYSM standard stations measure snow depth with Campbell Scientific’s SR50A ultrasonic distance sensor. This acoustic sensor measures the distance from the sensor to a rigid snowboard if there is no snow on the ground or the top of snow layer. A reference distance and a temperature correction are applied to determine the snow depth. While snow depth measurements can be made relatively straight forward with the use of this sensor, recording total snow accumulation is more difficult. During heavy snowfall events, compaction acts to reduce total snow depth during the course of a long-duration event. Then after a snowfall event, drifting of snow may act to reduce or increase snow depth depending on the water content of the snow and the wind speed. Due to these factors, there is often a difference between estimated snowfalls and the actual snow accumulation. As such, snow accumulation is calculated using an algorithm developed by the NYSM using snow depth, rain gauge precipitation, temperature and other data. This project aims to examine the performance of this algorithm in providing accurate snow accumulation data, and to find possible enhancements to improve this algorithm. To complete this evaluation, data has been synthesized from throughout the winter of 2022-2023, including NYSM daily snowfall data, as well as National Centers for Environmental Information (NCEI) daily snowfall data, to draw comparisons between the data sets. Data from winter 2022-2023 and previous winter seasons have shown NYSM snowfall data systematically lower than NCEI data for most locations across NYS. This project will examine the reasons for these differences, and examine individual cases during winter 2022-2023 to determine how the snow accumulation algorithm behaved on both a seasonal and daily basis. The findings of this project will contribute to a better understanding of the methods used to produce accurate snow accumulation measurements, and improve those measurements overall particularly for the New York State Mesonet.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.