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MJO potential predictability and predictive skill in IAP AGCM 4.1

Kun Wang,Zhaohui Lin,Jian Ling,Yue Yu,Chengben Wu

Published 2016 in Atmospheric and Oceanic Science Letters

ABSTRACT

Abstract A 30-year hindcast was performed using version 4.1 of the IAP AGCM (IAP AGCM4.1), and its potential predictability of the MJO was then evaluated. The results showed that the potential predictability of the MJO is 13 and 24 days, evaluated using the signal-to-error ratio method based on a single member and the ensemble mean, respectively. However, the MJO prediction skill is only 9 and 10 days using the two methods mentioned above. It was further found that the potential predictability and prediction skill depend on the MJO amplitude in the initial conditions. Prediction initiated from conditions with a strong MJO amplitude tends to be more skillful. Together with the results of other measures, the current MJO prediction ability of IAP AGCM4.1 is around 10 days, which is much lower than other climate prediction systems. Furthermore, the smaller difference between the MJO predictability and prediction skill evaluated by a single member and the ensemble mean methods could be ascribed to the relatively smaller size of the ensemble member of the model. Therefore, considerable effort should be made to improve MJO prediction in IAP AGCM4.1 through application of a reasonable model initialization and ensemble forecast strategy.

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