HWRF Based Ensemble Prediction System Using Perturbations from GEFS and Stochastic Convective Trigger Function

• Main Authors: Zhan Zhang, Vijay Tallapragada, Chanh Kieu, Samuel Trahan, Weiguo Wang
• Format: Article in Journal/Newspaper
• Language: English
• Published: KeAi Communications Co., Ltd. 2014
• Subjects: Physical geography; GB3-5030; Environmental sciences; GE1-350; North Atlantic
• Online Access: https://doi.org/10.6057/2014TCRR03.02; https://doaj.org/article/b82b2fd1bab04bd9b63c7d857e42f3ec

ABSTRACT: In this study, an ensemble prediction system (EPS) for the operational Hurricane Weather Research and Forecast (HWRF) model at the Environmental Modeling Center (EMC) of National Centers for Environmental Prediction (NCEP) is introduced and evaluated. The HWRF-EPS takes into account two main sources of uncertainties related to the initial/boundary conditions and the model physics by 1) using the large scale fields from NCEP Global Ensemble Forecast System (GEFS); and 2) stochastically perturbing the convective trigger function in the cumulus convection parameterization scheme.Verification for the 2011-2012 North Atlantic hurricane seasons shows that HWRF-EPS outperforms its deterministic versions at all lead times for both track and intensity forecast errors. Statistical characteristics are investigated and analyzed to demonstrate the effectiveness and robustness of the HWRF-EPS. The relationship between ensemble spread and forecast error for track and intensity in the HWRF-EPS indicated that the spread is likely more useful as a predictor of forecast error when it has moderately low values. Rank histogram analysis shows that the HWRF-EPS is well dispersed in both track and intensity forecasts except for the systematic errors inherited from the deterministic version. Further comparison with 2012 hurricane season’s top-flight models shows improved track and intensity forecasts from the HWRF-EPS. Keywords: ensemble forecasting, hurricane/tropical cyclone, track/intensity verification