Abstract
Seasonal forecasts are increasingly important tools in agricultural crop management. Regions with Mediterranean-type climates typically adopt rain-fed agriculture with minimal irrigation, hence accurate seasonal forecasts of rainfall during the growing season are potentially useful in decision making. In this paper we examined the bias and skill of a seasonal forecast system (ACCESS-S1) in simulating growing season precipitation (GSP) for south-west Western Australian (SWWA), a region with a Mediterranean-type climate and significant cereal crop production. Focusing on July–September (3-month) and May–October (6-month) forecasts, with 0- and 1-month lead times, we showed that overall ACCESS-S1 had a dry bias for SWWA rainfall and a tendency to simulate close to average rainfall during both wetter and drier than average rainfall years. ACCESS-S1 showed particularly poor skill at these timeframes for very wet and very dry years. The limitations in ACCESS-S1 for SWWA GSP were associated with inaccuracies in the timing of heavy rainfall events. In addition, limitations of the ACCESS-S1 model in accurately capturing SST and wind anomaly patterns over the tropical Indian Ocean during extreme rainfall years also contributed to errors in SWWA GSP forecasts. Model improvements in these regions have the potential to improve seasonal rainfall forecasts for SWWA.
Funder
Australian Research Council Discovery Early Career Researcher Award
Research Training Program and top-up scholarship
Subject
Atmospheric Science,Global and Planetary Change,Oceanography
Reference47 articles.
1. Alves O, Wang G, Zhong A, Smith N, Tseitkin F, Warren G, Schiller A, Godfrey S, Meyers G (2003) POAMA: Bureau of Meteorology operational coupled model seasonal forecast system. In ‘Science for Drought: Proceedings of National Drought Forum’, 15–16 April 2003, Brisbane, Qld, Australia. (Eds R Stone, I Partridge) pp. 22–32. (Queensland Department of Primary Industries) Available at
2. The Joint UK Land Environment Simulator (JULES), model description – Part 1: energy and water fluxes.;Geoscientific Model Development,2011
3. Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts.;Geoscientific Model Development,2014
4. Skilful multiweek tropical cyclone prediction in ACCESS-S1 and the role of the MJO.;Quarterly Journal of the Royal Meteorological Society,2018
5. Seasonal forecasting for Australia using a dynamical model: improvements in forecast skill over the operational statistical model.;Australian Meteorological and Oceanographic Journal,2015