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Dynamic MJO forecasts using an ensemble subseasonal-to-seasonal forecast system of IAP-CAS model.
- Source :
- EGUsphere; 3/19/2024, p1-51, 51p
- Publication Year :
- 2024
-
Abstract
- The Madden-Julian Oscillation (MJO) is a crucial predictability source on a sub-seasonal to seasonal (S2S) timescale. Therefore, the models participating in the WWRP/WCRP S2S prediction project focus on accurately predicting and analyzing the MJO. This study provided a detailed description of the configuration within the IAP-CAS S2S forecast system. We assessed the accuracy of the IAP-CAS model's MJO forecast using traditional RMM analysis and cluster analysis. Then, we explained the reasons behind any bias observed in the MJO forecast. Comparing the 20-year hindcast with observations, we found that the IAP-CAS ensemble mean has a skill of 24 days. However, there is still room for improvement in the ensemble spread. To examine the MJO structure in detail, we used cluster analysis to classify the MJO events during boreal winter into four types: fast-propagating, slow-propagating, standing, and jumping patterns of MJO. The model exhibits biases of overestimated amplitude and faster propagation speed in the propagating MJO events. Upon further analysis, it was found that the model forecasted a wetter background state. This leads to more intense forecasted convection and stronger coupled winds, especially in the fast MJO events. However, the horizontal moisture advection effect for eastward propagation is overestimated in IAP-CAS due to the wetter state and more substantial MJO circulations, which results in a faster MJO mode. These findings show that the IAP-CAS skilfully forecasts signals of MJO and its propagation, and they also provide valuable guidance for improving the current MJO forecast by developing the ensemble system and moisture forecast. [ABSTRACT FROM AUTHOR]
- Subjects :
- MADDEN-Julian oscillation
CLUSTER analysis (Statistics)
FORECASTING
ADVECTION
Subjects
Details
- Language :
- English
- Database :
- Complementary Index
- Journal :
- EGUsphere
- Publication Type :
- Academic Journal
- Accession number :
- 176128514
- Full Text :
- https://doi.org/10.5194/egusphere-2024-1