Impact of Ensemble Size on TIGGE Precipitation Forecasts: An End-User Perspective: Fid-Bau Portal

Impact of Ensemble Size on TIGGE Precipitation Forecasts: An End-User Perspective

Khan, Mudasser Muneer / Shamseldin, Asaad Y. / Melville, Bruce W. / Shoaib, Muhammad

Precipitation forecasts play a key role in decision making for the water resource sector. The use of an ensemble numerical weather prediction model known as the ensemble prediction system to account for the uncertainties in weather forecasting has become common practice at various meteorological centers around the world. The current ensemble prediction systems operational at different forecasting centers vary in their parameters, including but not limited to spatial and temporal resolution, ensemble size, model physics, and initial perturbation strategy. This paper presents a comparison of six ensemble systems of varying characteristics, evaluating the quantitative precipitation forecasts issued for the Waikato River catchment in New Zealand. Three derivative products of the ensemble forecasts were used, most likely precipitation event, probability of above average rain, and ensemble mean precipitation, to test the potential application of the ensembles for resource allocation, hazard management, and catchment modeling. The forecasts of three-day cumulative precipitation, issued seven days in advance at different forecasting centers and connected through the Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) network, were compared with the corresponding areal average precipitation observed in the selected catchment over a one-year period. The research investigated the effect of ensemble size on its performance and provides users an insight into the performance of various operational EPSs of different sizes in different situations of interest. The research presented in this paper also provides a preliminary framework of the evaluation of ensembles based on their intended use by different sectors. The results of the study indicate that an increased ensemble size is not always related to better performance. It was further inferred from the results that a slight gain in accuracy may be achieved by employing larger ensembles for their intended use in hazard management than the other two applications. Additionally, the grand ensemble, constructed by combining forecasts from all other ensembles tested in the study, adds no more value to an ensemble precipitation forecast if used in the context of the three scenarios adopted in this study.