The Impact of Stochastic Physics Based Hybrid GSI/EnKF Data Assimilation on Hurricane Track/Intensity Forecasts Using NCEP's Operational Hurricane Modeling System

The NOAA/NCEP/EMC operational hurricane dynamic model prediction system, Hurricane Weather and Research Forecasting (HWRF), includes the sophisticated GSI/EnKF hybrid Data Assimilation (DA) system, which allows assimilating high resolution aircraft observations in storm inner core region. In the current operational HWRF DA system, the flow-dependent background error covariances are calculated from HWRF self-cycled 40-member ensemble. This DA system has been proven to provide better initial storm structure and therefore improved storm track and intensity forecasts. However, the uncertainties from model physics are not taken into account in the current HWRF DA system. In order to further improve the HWRF DA system, two additional modifications are evaluated in this study. The first is introduction of stochastic perturbations in the model physics, including the cumulus convection scheme, the Planetary Boundary Layer (PBL) scheme, and model surface physics (drag coefficient), for HWRF based ensembles. The second is to increase of the ensemble membership from 40 to 80. The background error covariance is expected to improve the span of the ensemble in physics space, which better samples the model uncertainties and improves HWRF model track and intensity forecasts.

Several experiments are designed and conducted to study the impacts of the background error covariance obtained from different ensemble sizes and different model stochastic physics perturbations. The track and intensity forecasts from various experiments are compared and verified against best track.