Editorial Type:
Article
Article Type:
Research Article

Short-Term Ice Accretion Forecasts for Electric Utilities Using the Weather Research and Forecasting Model and a Modified Precipitation-Type Algorithm

Arthur T. DeGaetano Northeast Regional Climate Center, Department of Earth and Atmospheric Science, Cornell University, Ithaca, New York

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Brian N. Belcher Northeast Regional Climate Center, Department of Earth and Atmospheric Science, Cornell University, Ithaca, New York

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Pamela L. Spier Northeast Regional Climate Center, Department of Earth and Atmospheric Science, Cornell University, Ithaca, New York

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Print Publication:
01 Oct 2008
DOI:
https://doi.org/10.1175/2008WAF2006106.1
Page(s):
838–853
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Abstract

The Weather Research and Forecasting model (WRF) is used to provide 6–12-h forecasts of the necessary input parameters to a separate algorithm that determines the most likely precipitation type at each model grid point. In instances where freezing rain is indicated, an ice accretion model allows forecasts of radial ice thickness to be developed. The resulting forecasts are evaluated for 38 icing events of varying magnitude that occurred in the eastern United States using National Weather Service storm impact reports and observed data from Automated Surface Observing Systems (ASOS). Ice accretion hindcasts, using the WRF, allow the development of climatologies based on archived model initialization data.

Ice accretion forecasts, based on the Ramer precipitation-type algorithm, consistently underestimated the maximum observed ice accretion amounts by between 10 and 20 mm. Ice accretion at ASOS sites was also underestimated. Applying a modification to the Ramer precipitation-type algorithm, and focusing on the thermal profile below the lowest 0°C isotherm, improved the ice accretion forecasts, but still underestimated the maximum ice thickness. Little bias was evident in ice accretion forecasts for the ASOS sites. Using previous observations from outside the forecast window to account for WRF and precipitation-type algorithm biases in precipitation amount, wind speed, temperature, and precipitation type provided some forecast improvement. The forecast procedure using the modified Ramer precipitation algorithm captures both the magnitude and extent of icing in both widespread severe icing events and localized storms. Minimal icing is indicated in events and at locations where precipitation fell as rain or snow.

Corresponding author address: Art DeGaetano, Northeast Regional Climate Center, Cornell University, 1119 Bradfield Hall, Ithaca, NY 14853. Email: atd2@cornell.edu

Abstract

The Weather Research and Forecasting model (WRF) is used to provide 6–12-h forecasts of the necessary input parameters to a separate algorithm that determines the most likely precipitation type at each model grid point. In instances where freezing rain is indicated, an ice accretion model allows forecasts of radial ice thickness to be developed. The resulting forecasts are evaluated for 38 icing events of varying magnitude that occurred in the eastern United States using National Weather Service storm impact reports and observed data from Automated Surface Observing Systems (ASOS). Ice accretion hindcasts, using the WRF, allow the development of climatologies based on archived model initialization data.

Ice accretion forecasts, based on the Ramer precipitation-type algorithm, consistently underestimated the maximum observed ice accretion amounts by between 10 and 20 mm. Ice accretion at ASOS sites was also underestimated. Applying a modification to the Ramer precipitation-type algorithm, and focusing on the thermal profile below the lowest 0°C isotherm, improved the ice accretion forecasts, but still underestimated the maximum ice thickness. Little bias was evident in ice accretion forecasts for the ASOS sites. Using previous observations from outside the forecast window to account for WRF and precipitation-type algorithm biases in precipitation amount, wind speed, temperature, and precipitation type provided some forecast improvement. The forecast procedure using the modified Ramer precipitation algorithm captures both the magnitude and extent of icing in both widespread severe icing events and localized storms. Minimal icing is indicated in events and at locations where precipitation fell as rain or snow.

Corresponding author address: Art DeGaetano, Northeast Regional Climate Center, Cornell University, 1119 Bradfield Hall, Ithaca, NY 14853. Email: atd2@cornell.edu

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