Convective Meteorology (Mesoscale Dynamics)

GSI-based, Continuously cycled, Dual Resolution Hybrid Ensemble-Variational Data Assimilation System for HWRF: system description and experiments with Edouard (2014)

Xu Lu

School of Meteorology

11 March 2016, 3:00 PM

National Weather Center, Room 5600
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

A Gridpoint Statistical Interpolation (GSI) based, continuously cycled, dual resolution hybrid ensemble Kalaman filter (EnKF)-variational data assimilation (DA) system is developed for the Hurricane Weather Research and Forecasting (HWRF) model to improve the high resolution analyses and predictions of tropical cyclones. In this ensemble-variational (EnVar) hybrid system, a newly developed directed moving nest strategy is adopted to solve the issue of non-overlapped domains for cycled ensemble DA. In addition, both dual-resolution and Four-Dimensional (4D) capabilities are implemented in the system. The performance of the system is investigated by conducting the end-to-end DA cycling and forecast experiments for hurricane Edouard (2014). All operational observations in addition to the Tail Doppler Radar data are assimilated. Experiments and diagnostics are designed to address various scientific questions using this newly extended hybrid DA system.

This study finds that a) the dual resolution hybrid DA improves upon the coarser, single resolution hybrid DA; b) Vortex initialization and relocation in the control and relocation of the ensemble background on top of the DA improve the forecasts; c) Using 4DEnVar in the TDR-involved cycles improves the intensity forecasts for early lead times compared to 3DEnVar; and d) The hybrid system improves intensity forecasts relative to operational HWRF during the intensification period due to the alleviation of the “spin-down” issue resultant from better analyzed structures for an intensifying storm.

Convective Meteorology (Mesoscale Dynamics) Seminar Series website