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Observational data reveals MJO significantly affects subseasonal precipitation prediction skill, highlighting uncertainty.
The Madden-Julian Oscillation (MJO) is recognized as a major source of predictability in subseasonal forecasts. Many studies investigate how the MJO modulates prediction skill, often referred to as the "forecast windows of opportunity" driven by the MJO, which can be useful for operational forecasts. In this study, we use observational data and the Community Earth System Model version 2 Large Ensemble (CESM2-LE) to explore the MJO influence on weeks 3–4 precipitation prediction skill over the contiguous United States (CONUS) with statistical prediction models. The prediction skill, represented by the Heidke skill score (HSS), shows substantial variations due to the MJO modulation for different 40-year periods, which can be well explained by probability theory. Based on the theoretical explanation, the uncertainty in the MJO modulation of the prediction skill, mostly due to the limited number of MJO events in different 40-year periods, exceeds the true MJO influence. With such a low signal-to-noise ratio, high prediction skill cannot be attributed solely to the MJO modulation but also involve constructive interference between the MJO and other climate variability. This interference is random across different time periods, thus constructive interference tends to diminish in subsequent periods, leading to a lower than expected skill in future realtime application of the prediction tool over regions where high prediction skill is identified during the satellite observed period. We emphasize the need for caution when interpreting the MJO modulation of prediction skill and recommend considering the uncertainty of the modulation highlighted in this study.
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Zheng et al. (2025) studied this question.
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