Evaluation of the North American multi-model ensemble for monthly precipitation forecast

D. Y. Faidah*, H. Kuswanto, Suhartono

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


The North American multi-model ensemble (NMME) is a multi-model seasonal forecasting system consisting of a collection of models generated from several climate modelling centers. This research examined the monthly precipitation in North Maluku generated by five NMME models. The purpose of this research is to assess the performance of monthly precipitation prediction by using RMSE and Rank Histogram analysis. The NMME models are verified against observed precipitation. The analysis shows that they are biased and underdispersive. Among the five NMME models, the Center for Ocean-Land-Atmosphere Studies (COLA) exhibits the best predictive skill. The performances of the Canadian Meteorological Centre (CMC) are relatively worse than that of the other models. The COLA model shows relatively high skill when used to forecast May-November monthly precipitation. Meanwhile, the National Oceanic and Atmospheric Administration (NOAA)'s Geophysical Fluid Dynamics Laboratory (GFDL) model shows high skill in December-April periods. The ensemble forecast is calibrated with the BMA approach in order to obtain reliable forecasts.

Original languageEnglish
Article number012067
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 7 Jan 2021
Event10th International Conference and Workshop on High Dimensional Data Analysis, ICW-HDDA 2020 - Sanur-Bali, Indonesia
Duration: 12 Oct 202015 Oct 2020


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