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An Assessment of the Performance of the Operational Global Ensemble Forecast Systems in Predicting the Forecast Uncertainty
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This study investigates the efficiency of the operational global ensemble forecast systems in capturing the spatiotemporal evolution of the forecast uncertainty. It has two novel aspects: first, it extends the results of an earlier study from 2012 to 2015; second, it documents the first attempts to predict the reliability of the ensembles in capturing the uncertain forecast features and the 95th percentile value of the forecast error for operational ensembles. It is found that the main characteristics of the systems of the different centers in their efficiency in representing the spatiotemporal evolution of the forecast uncertainty have not changed much in the last three years. The only exception is the UKMO ensemble, whose performance improved in predicting the total magnitude of the uncertainty, but greatly degraded in predicting the patterns of forecast uncertainty. All ensembles were found to have major difficulties with predicting the large scale atmospheric flow in the forecast range longer than 10 days. These difficulties are due to the inability of the models to maintain the large-scale zonal anomalies of the atmospheric flow in the long forecast range. It was also found that the flow-dependent reliability of the ensembles in capturing the local structure of the forecast uncertainty and the 95th percentile value of the forecast error can accurately be predicted.
Loeser, Carlee Frances (2016). An Assessment of the Performance of the Operational Global Ensemble Forecast Systems in Predicting the Forecast Uncertainty. Master's thesis, Texas A & M University. Available electronically from