Icing Severity in the December 2002 Freezing-Rain Storm from ASOS Data*

Jones, Kathleen F.; Ramsay, Allan C.; Lott, J. N.

doi:10.1175/1520-0493(2004)132<1630:isitdf>2.0.co;2

Cited by 23 publications

(19 citation statements)

References 5 publications

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“…The 2002 ice storm in the southern United States was analyzed by Jones et al (2004). The authors applied the Simple Model to the METAR data (regular reports from airport meteorological stations), triggering the icing algorithm with actual observations of precipitation type.…”

Section: Icing Modelmentioning

confidence: 99%

Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event

Hosek

Musilek

Lozowski

et al. 2011

Nat. Hazards Earth Syst. Sci.

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Abstract.The northeast coast of North America is frequently hit by severe ice storms.These freezing rain events can produce large ice accretions that damage structures, frequently power transmission and distribution infrastructure. For this reason, it is highly desirable to model and forecast such icing events, so that the consequent damages can be prevented or mitigated. The case study presented in this paper focuses on the March 2010 ice storm event that took place in eastern Newfoundland. We apply a combination of a numerical weather prediction model and an ice accretion algorithm to simulate a forecast of this event.The main goals of this study are to compare the simulated meteorological variables to observations, and to assess the ability of the model to accurately predict the ice accretion load for different forecast horizons. The duration and timing of the freezing rain event that occurred between the night of 4 March and the morning of 6 March was simulated well in all model runs. The total precipitation amounts in the model, however, differed by up to a factor of two from the observations. The accuracy of the model air temperature strongly depended on the forecast horizon, but it was acceptable for all simulation runs. The simulated accretion loads were also compared to the design values for power delivery structures in the region. The results indicated that the simulated values exceeded design criteria in the areas of reported damage and power outages.

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Section: Icing Modelmentioning

confidence: 99%

Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event

Hosek

Musilek

Lozowski

et al. 2011

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…As the most prevalent form of ice accretion is caused by freezing rain, an effective method for forecasting precipitation type is required. An optimal precipitation type algorithm was determined and calibrated by comparing modeled ice accretions with observations from a well documented ice storm (Jones et al 2004). …”

Section: Ice Accretion Forecasting Systemmentioning

confidence: 99%

“…There was significant damage to power transmission systems as ice-covered trees broke equipment, and high winds broke ice-coated conductors. Jones et al (2004) documents this storm in great detail and provides ice thicknesses obtained from the Automated Surface Observing System (ASOS) ice sensors, as well as thicknesses diagnosed using two physical icing models with observed meteorological variables as inputs.…”

Section: An Ice Accretion Forecasting System (Iafs) For Power Transmimentioning

confidence: 99%

“…Table 2 presents the IAFS ice thickness, along with ice thickness inferred from the ASOS sensor and ice thickness estimated by Jones et al (2004) using the SM model and CRREL model (Jones 1996). The CRREL model improves on SM physics by including heat transfer and icicle formation.…”

Section: Outlinementioning

confidence: 99%

“…In the comparison, the ASOS measured ice accretion is taken to be correct. Jones et al (2004) used freezing rain observations to implement icing models. However, an NWP-based forecasting system cannot take observations into account.…”

Section: Outlinementioning

confidence: 99%

See 2 more Smart Citations

An Ice Accretion Forecasting System (IAFS) for Power Transmission Lines Using Numerical Weather Prediction

Musilek

Arnold

Lozowski³

2009

SOLA

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Power transmission networks are exposed to meteorological conditions that can often cause damage resulting in temporary loss of service. Because their reliability is of crucial importance to society, the ability to predict potential hazards in advance is of great interest. Studies conducted by the power transmission industry indicate that the majority of failures is caused by icing on overhead conductors and other components of power networks. This paper outlines an ice accretion forecasting system (IAFS) that uses a state-of-the-art, mesoscale, numerical weather prediction model, augmented by a precipitation type classifier, and an ice accretion model. The system is calibrated by hindcasting a well-documented freezing rain event in the United States, in December, 2002. Results indicate that IAFS can hindcast overall ice thicknesses as well as icing models can diagnose them using observed surface meteorological conditions.

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Performance-based ice engineering framework: A data-driven multi-scale approach

Snaiki

2024

Cold Regions Science and Technology

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Icing Severity in the December 2002 Freezing-Rain Storm from ASOS Data*

Cited by 23 publications

References 5 publications

Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event

Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event

An Ice Accretion Forecasting System (IAFS) for Power Transmission Lines Using Numerical Weather Prediction

Performance-based ice engineering framework: A data-driven multi-scale approach

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