Numerical Prediction of a Cold-Air Outbreak: A Case Study with Ensemble Forecasts

Stephen J. Colucci Department of Soil, Crop and Atmospheric Sciences, Cornell University, Ithaca, New York

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David P. Baumhefner Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado

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Charles E. Konrad II Department of Geography, University of North Carolina, Chapel Hill, North Carolina

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Abstract

The forecastability of a cold-air outbreak over eastern North America during January 1985 has been studied with ensemble forecasts from the NCAR Community Climate Model version 2 run at T42 horizontal resolution. The cold-air outbreak case was characterized by a pool of very cold air (T < −35°C at 850 mb) that moved southward into the central United States and intensified. The ensemble’s 10 member forecasts were initialized at 0000 UTC 15 January 85, a few days before the cold-air pool began its southward movement and reached its peak intensity. The ensemble members predicted the southward passage of the cold air but faster and weaker than analyzed. The predicted weakening of the cold-air pool was consistent with the model’s systematic error. Quasi-Lagrangian diagnosis of the 850-mb temperature tendency budget revealed that the analyzed intensification of the cold-air pool was due to residual rather than adiabatic effects. These residual effects could have been diabatic in origin but also attributable to observational errors. Similar diagnoses applied to selected ensemble members indicated that diabatic cooling, specifically longwave radiative cooling, contributed to the forecast cooling of the cold-air pool by one ensemble member but was overwhelmed by adiabatic warming in a weakening cold-air pool predicted by another ensemble member. These results suggest that the forecast details of a cold-air outbreak may depend upon the subtle balance between diabatic and adiabatic processes. Furthermore, forecasts constructed from ensemble predictions must account for model biases as well as information from the ensembles.

Corresponding author address: Stephen J. Colucci, Department of Soil, Crop and Atmospheric Sciences, Bradfield Hall, Cornell University, Ithaca, NY 14853.

Email: colucci@metvax.cit.cornell.edu

Abstract

The forecastability of a cold-air outbreak over eastern North America during January 1985 has been studied with ensemble forecasts from the NCAR Community Climate Model version 2 run at T42 horizontal resolution. The cold-air outbreak case was characterized by a pool of very cold air (T < −35°C at 850 mb) that moved southward into the central United States and intensified. The ensemble’s 10 member forecasts were initialized at 0000 UTC 15 January 85, a few days before the cold-air pool began its southward movement and reached its peak intensity. The ensemble members predicted the southward passage of the cold air but faster and weaker than analyzed. The predicted weakening of the cold-air pool was consistent with the model’s systematic error. Quasi-Lagrangian diagnosis of the 850-mb temperature tendency budget revealed that the analyzed intensification of the cold-air pool was due to residual rather than adiabatic effects. These residual effects could have been diabatic in origin but also attributable to observational errors. Similar diagnoses applied to selected ensemble members indicated that diabatic cooling, specifically longwave radiative cooling, contributed to the forecast cooling of the cold-air pool by one ensemble member but was overwhelmed by adiabatic warming in a weakening cold-air pool predicted by another ensemble member. These results suggest that the forecast details of a cold-air outbreak may depend upon the subtle balance between diabatic and adiabatic processes. Furthermore, forecasts constructed from ensemble predictions must account for model biases as well as information from the ensembles.

Corresponding author address: Stephen J. Colucci, Department of Soil, Crop and Atmospheric Sciences, Bradfield Hall, Cornell University, Ithaca, NY 14853.

Email: colucci@metvax.cit.cornell.edu

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