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This document describes skill scores used to evaluate seasonal prediction models, including mean squared skill score (MSSS), anomaly correlation coefficient (ACC), and root mean square error (RMSE). Tables 1-3 list these scores for different models and multi-model analysis methods for June-July-August averages of precipitation and temperature. The MSSS, ACC, and RMSE scores indicate the CPPM and MME methods performed best overall at predicting precipitation, while CPPM, MME, and MR performed best for temper

Author

Venkat Chandrakanth A

Language

EN