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Dependence of snow gauge collection efficiency on snowflake characteristics

    • National Center for Atmospheric Research
    • Université du Québec à Montréal

    Research output: Contribution to journalArticlepeer-review

    93 Scopus citations

    Abstract

    Accurate snowfall measurements are critical for a wide variety of research fields, including snowpack monitoring, climate variability, and hydrological applications. It has been recognized that systematic errors in snowfall measurements are often observed as a result of the gauge geometry and the weather conditions. The goal of this study is to understand better the scatter in the snowfall precipitation rate measured by a gauge. To address this issue, field observations and numerical simulations were carried out. First, a theoretical study using finite-element modeling was used to simulate the flow around the gauge. The snowflake trajectories were investigated using a Lagrangian model, and the derived flow field was used to compute a theoretical collection efficiency for different types of snowflakes. Second, field observations were undertaken to determine how different types, shapes, and sizes of snowflakes are collected inside a Geonor, Inc., precipitation gauge. The results show that the collection efficiency is influenced by the type of snowflakes as well as by their size distribution. Different types of snowflakes, which fall at different terminal velocities, interact differently with the airflow around the gauge. Fast-falling snowflakes are more efficiently collected by the gauge than slow-falling ones. The correction factor used to correct the data for the wind speed is improved by adding a parameter for each type of snowflake. The results show that accurate measure of snow depends on the wind speed as well as the type of snowflake observed during a snowstorm.

    Original languageEnglish
    Pages (from-to)745-762
    Number of pages18
    JournalJournal of Applied Meteorology and Climatology
    Volume51
    Issue number4
    DOIs
    StatePublished - Apr 2012

    Keywords

    • Numerical analysis/modeling
    • Sensitivity studies
    • Surface observations
    • Wind effects

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