Automated Detection of the Bright Band Using WSR-88D Data

Jonathan J. Gourley Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

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Chris M. Calvert Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

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Abstract

During stratiform precipitation, hydrometeors within the melting layer increase backscatter to radar. This layer can persist at a nearly constant height for hours and can lead to serious radar-based overestimates in accumulated surface rainfall. Sophisticated precipitation algorithms of the present and near future are beginning to identify regions where there is contaminated reflectivity in order to make corrections to the data. An automated algorithm that operates on full-resolution Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity data (i.e., archive level II) to identify the height and depth of the bright band for every volume scan has been developed. Results from the algorithm are compared with 0°C heights from nearby radiosonde observations and from model analyses for three different regions in the United States. In addition, reflectivity observations from an independent, vertically pointing radar situated in complex terrain are compared with results from the brightband algorithm operating on WSR-88D data. The output from the brightband algorithm matches observations well. A case is presented to show how the radar-observed brightband heights can be used to identify regions in precipitation products where radar is sampling within the melting layer and therefore may be subject to overestimation. Improved monitoring of the bright band, because of the comparatively high temporal resolution of the radar observations, results from application of the algorithm. The algorithm output can provide guidance to forecasters who are using radar-based quantitative precipitation estimates to issue advisories and warnings. Moreover, the melting-layer observations can be used with a digital elevation model to map the approximate rain–snow line.

Additional affiliation: NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma

Corresponding author address: Jonathan J. Gourley, National Severe Storms Laboratory, 1313 Halley Circle, Norman, OK 73069. Email: gourley@ou.edu

Abstract

During stratiform precipitation, hydrometeors within the melting layer increase backscatter to radar. This layer can persist at a nearly constant height for hours and can lead to serious radar-based overestimates in accumulated surface rainfall. Sophisticated precipitation algorithms of the present and near future are beginning to identify regions where there is contaminated reflectivity in order to make corrections to the data. An automated algorithm that operates on full-resolution Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity data (i.e., archive level II) to identify the height and depth of the bright band for every volume scan has been developed. Results from the algorithm are compared with 0°C heights from nearby radiosonde observations and from model analyses for three different regions in the United States. In addition, reflectivity observations from an independent, vertically pointing radar situated in complex terrain are compared with results from the brightband algorithm operating on WSR-88D data. The output from the brightband algorithm matches observations well. A case is presented to show how the radar-observed brightband heights can be used to identify regions in precipitation products where radar is sampling within the melting layer and therefore may be subject to overestimation. Improved monitoring of the bright band, because of the comparatively high temporal resolution of the radar observations, results from application of the algorithm. The algorithm output can provide guidance to forecasters who are using radar-based quantitative precipitation estimates to issue advisories and warnings. Moreover, the melting-layer observations can be used with a digital elevation model to map the approximate rain–snow line.

Additional affiliation: NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma

Corresponding author address: Jonathan J. Gourley, National Severe Storms Laboratory, 1313 Halley Circle, Norman, OK 73069. Email: gourley@ou.edu

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