Data denial experiments for extratropical transition

Extratropical transition (ET) of tropical cyclones presents a significant challenge to numerical weather forecasts. Small uncertainties in sensitive regions around ET events can lead to large forecast errors. An important source of such uncertainties lies in the insufficient data coverage. Introducing targeted observations made in sensitive regions into the data assimilation procedure may have a notable value for a numerical forecast.

Data denial experiments using the ECMWF IFS are designed to investigate the value of targeted observations for historical ET cases. The impact of removing data in specified locations on the forecast for the ET events is examined. Data is denied in sensitive areas determined with singular vectors optimizing on a 2 day interval. Furthermore, the influence of observations in the vicinity of the decaying tropical cyclone (TC) and associated with data structures inherent to a TC on the forecast is examined. Forecasts with and without data in the different areas are compared. This project will contribute to the preparation for the T-PARC experiment.