The bias correction technique uses a multivariate linear regression method to bias correct storm intensity and structure. Special strategies are used to maintain ensemble spread after bias correction; to predict the radius to gales when the model storm is below this intensity; and to predict the radius of maximum winds. The system was trained on ECMWF-EPS TC data from two cyclone seasons which was found to yield better results than other alternatives.
The system inserts corrected vortices, based on the bias-corrected parameters, into the original surface wind and pressure fields. The vortex insertion method retains the modelled asymmetry and incorporates a surface wind inflow angle designed to match measurements from a large body of dropsonde data. These corrected wind fields are used to estimate wind exceedance probabilities, and to drive a wave model.
The bias-corrected system has shown an overall skill improvement over the uncorrected ECMWF-EPS for all TC intensity and structure parameters with the most significant gains for the maximum wind speed prediction. The spread-skill relationships, and other measures of ensemble quality, have also improved. This translates operationally to an increase in confidence of guidance as to the worst case scenario up to ten days ahead of time, enabling effective decision making. It also enables more accurate forecasting of the ocean response, in particular the wave field. The system has been operational at the Australian Bureau of Meteorology since November 2016.