Value of human-generated perturbations in short-range ensemble forecasts of severe weather

Victor Homar, David J. Stensrud, Jason J. Levit, David R. Bright

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


During the spring of 2003, the Storm Prediction Center, in partnership with the National Severe Storms Laboratory, conducted an experiment to explore the value of having operational severe weather forecasters involved in the generation of a short-range ensemble forecasting system. The idea was to create a customized ensemble to provide guidance on the severe weather threat over the following 48 h. The forecaster was asked to highlight structures of interest in the control run and, using an adjoint model, a set of perturbations was obtained and used to generate a 32-member fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) ensemble. The performance of this experimental ensemble is objectively evaluated and compared with other available forecasts (both deterministic and ensemble) using real-time severe weather reports and precipitation in the central and eastern parts of the continental United States. The experimental ensemble outperforms the operational forecasts considered in the study for episodes with moderate-to-high probability of severe weather occurrence and those with moderate probability of heavy precipitation. On the other hand, the experimental ensemble forecasts of low-probability severe weather and low precipitation amounts have less skill than the operational models, arguably due to the lack of global dispersion in a system designed to target the spread over specific areas of concern for severe weather. Results from an additional test ensemble constructed by combining automatic and manually perturbed members show the best results for numerical forecasts of severe weather for all probability values. While the value of human contribution in the numerical forecast is demonstrated, further research is needed to determine how to better use the skill and experience of the forecaster in the construction of short-range ensembles.

Original languageEnglish (US)
Pages (from-to)347-363
Number of pages17
JournalWeather and Forecasting
Issue number3
StatePublished - Jun 2006

All Science Journal Classification (ASJC) codes

  • Atmospheric Science


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