Abstract
The commencement of SEAS5 model for operational seasonal climate forecasting by the European Centre for Medium-Range Weather Forecasts (ECMWF) is a new development. It replaces the ECMWF System 4, which had a large international community of seasonal climate forecast users. To assist potential users of SEAS5 forecasts, a systematic and detailed evaluation of forecast skill and reliability of climate variables over land areas is valuable. In this regional study, we evaluate SEAS5 performance in forecasting precipitation and daily minimum temperature (Tmin) and daily maximum temperature (Tmax) for the Australian continent, based on 36 years of re-forecast data. We evaluate forecasts after simple mean-corrections, and statistically calibrated forecasts using the Bayesian joint probability (BJP) modelling approach. We also provide a comparison with System 4. A new simpler and more efficient BJP algorithm is introduced to facilitate this study and support wider use of the algorithm in other applications.
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