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A Revised Bourgouin Precipitation-Type Algorithm

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  • 1 National Oceanic and Atmospheric Administration, National Weather Service, Romeoville, Illinois
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Abstract

Using vertical temperature profiles obtained from upper-air observations or numerical weather prediction models, the Bourgouin technique calculates areas of positive melting energy and negative refreezing energy for determining precipitation type. Energies are proportional to the product of the mean temperature of a layer and its depth. Layers warmer than 0°C consist of positive energy; those colder than 0°C consist of negative energy. Sufficient melting or freezing energy in a layer can produce a phase change in a falling hydrometeor. The Bourgouin technique utilizes these energies to determine the likelihood of rain (RA) versus snow (SN) given a surface-based melting layer and ice pellets (PL) versus freezing rain (FZRA) or RA given an elevated melting layer. The Bourgouin approach was developed from a relatively small dataset but has been widely utilized by operational forecasters and in postprocessing of NWP output. Recent analysis with a larger dataset suggests ways to improve the original technique, especially when discriminating PL from FZRA or RA. This and several other issues are addressed by a modified version of the Bourgouin technique described in this article. Additional enhancements include use of the wet-bulb profile rather than temperature, a check for heterogeneous ice nucleation, and output that includes probabilities of four different weather types (RA, SN, FZRA, PL) rather than the single most likely type. Together these revisions result in improved performance and provide a more viable and valuable tool for precipitation-type forecasts. Several National Weather Service forecast offices have successfully utilized the revised tool in recent winters.

Significance Statement

This article describes an updated version of a widely used technique for predicting winter precipitation type at the surface. Verification statistics suggest the revised technique outperforms the original version. It also compares favorably to a more sophisticated approach for postprocessing of model output yet is simple enough for operational meteorologists to use for making real-time, critical forecast adjustments. This updated technique was adapted as the basis for precipitation-type forecasts in the NWS National Blend of Models starting with version 3.2. It also is the approach that several NWS offices have adapted for their winter forecasts in recent years. Future efforts should seek to further refine this technique and make greater use of its inherent probabilistic information.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kevin Birk, kevin.birk@noaa.gov

Abstract

Using vertical temperature profiles obtained from upper-air observations or numerical weather prediction models, the Bourgouin technique calculates areas of positive melting energy and negative refreezing energy for determining precipitation type. Energies are proportional to the product of the mean temperature of a layer and its depth. Layers warmer than 0°C consist of positive energy; those colder than 0°C consist of negative energy. Sufficient melting or freezing energy in a layer can produce a phase change in a falling hydrometeor. The Bourgouin technique utilizes these energies to determine the likelihood of rain (RA) versus snow (SN) given a surface-based melting layer and ice pellets (PL) versus freezing rain (FZRA) or RA given an elevated melting layer. The Bourgouin approach was developed from a relatively small dataset but has been widely utilized by operational forecasters and in postprocessing of NWP output. Recent analysis with a larger dataset suggests ways to improve the original technique, especially when discriminating PL from FZRA or RA. This and several other issues are addressed by a modified version of the Bourgouin technique described in this article. Additional enhancements include use of the wet-bulb profile rather than temperature, a check for heterogeneous ice nucleation, and output that includes probabilities of four different weather types (RA, SN, FZRA, PL) rather than the single most likely type. Together these revisions result in improved performance and provide a more viable and valuable tool for precipitation-type forecasts. Several National Weather Service forecast offices have successfully utilized the revised tool in recent winters.

Significance Statement

This article describes an updated version of a widely used technique for predicting winter precipitation type at the surface. Verification statistics suggest the revised technique outperforms the original version. It also compares favorably to a more sophisticated approach for postprocessing of model output yet is simple enough for operational meteorologists to use for making real-time, critical forecast adjustments. This updated technique was adapted as the basis for precipitation-type forecasts in the NWS National Blend of Models starting with version 3.2. It also is the approach that several NWS offices have adapted for their winter forecasts in recent years. Future efforts should seek to further refine this technique and make greater use of its inherent probabilistic information.

For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kevin Birk, kevin.birk@noaa.gov
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