Forecast Uncertainty Dynamics in the THORPEX Interactive Grand Global Ensemble (TIGGE)

Michael A. Herrera Texas A&M University, College Station, Texas

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Istvan Szunyogh Texas A&M University, College Station, Texas

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Joseph Tribbia National Center for Atmospheric Research, Boulder, Colorado

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Abstract

This paper employs local linear, spatial spectral, and Lorenz curve–based diagnostics to investigate the dynamics of uncertainty in global numerical weather forecasts in the NH extratropics. The diagnostics are applied to ensembles in the THORPEX Interactive Grand Global Ensemble (TIGGE). The initial growth of uncertainty is found to be the fastest at the synoptic scales (zonal wavenumbers 7–9) most sensitive to baroclinic instability. At later forecast times, the saturation of uncertainties at the synoptic scales and the longer sustainable growth of uncertainty at the large scales lead to a gradual shift of the wavenumber of the dominant uncertainty toward zonal wavenumber 5. At the subsynoptic scales, errors saturate as predicted by Lorenz’s classic theory. While the ensembles capture the general characteristics of the uncertainty dynamics efficiently, there are locations where the predicted magnitude and structure of uncertainty have considerable time-mean errors. In addition, the magnitude of systematic errors in the prediction of the uncertainty increases with increasing forecast time. These growing systematic errors are dominated by errors in the prediction of low-frequency changes in the large-scale flow.

Corresponding author address: Michael A. Herrera, Department of Atmospheric Sciences, Texas A&M University, 3150 TAMU, College Station, TX 77843-3150. E-mail: mherr77m@gmail.com

Abstract

This paper employs local linear, spatial spectral, and Lorenz curve–based diagnostics to investigate the dynamics of uncertainty in global numerical weather forecasts in the NH extratropics. The diagnostics are applied to ensembles in the THORPEX Interactive Grand Global Ensemble (TIGGE). The initial growth of uncertainty is found to be the fastest at the synoptic scales (zonal wavenumbers 7–9) most sensitive to baroclinic instability. At later forecast times, the saturation of uncertainties at the synoptic scales and the longer sustainable growth of uncertainty at the large scales lead to a gradual shift of the wavenumber of the dominant uncertainty toward zonal wavenumber 5. At the subsynoptic scales, errors saturate as predicted by Lorenz’s classic theory. While the ensembles capture the general characteristics of the uncertainty dynamics efficiently, there are locations where the predicted magnitude and structure of uncertainty have considerable time-mean errors. In addition, the magnitude of systematic errors in the prediction of the uncertainty increases with increasing forecast time. These growing systematic errors are dominated by errors in the prediction of low-frequency changes in the large-scale flow.

Corresponding author address: Michael A. Herrera, Department of Atmospheric Sciences, Texas A&M University, 3150 TAMU, College Station, TX 77843-3150. E-mail: mherr77m@gmail.com
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