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An Alternative Estimate of Potential Predictability on the Madden–Julian Oscillation Phase Space Using S2S Models

1
Graduate School of Science, Hokkaido University, Sapporo 060-0015, Japan
2
Faculty of Science, Hokkaido University, Sapporo 060-0015, Japan
*
Author to whom correspondence should be addressed.
Atmosphere 2017, 8(8), 150; https://doi.org/10.3390/atmos8080150
Received: 19 June 2017 / Revised: 8 August 2017 / Accepted: 10 August 2017 / Published: 15 August 2017
(This article belongs to the Special Issue Madden-Julian Oscillation)
This study proposes an alternative method to estimate the potential predictability without assuming the perfect model. A theoretical consideration relates a maximum possible value of the initial-value error to the covariance between analysis and bias-corrected ensemble-mean forecast. To test the method, the prediction limit of the Madden–Julian Oscillation (MJO) was evaluated, based on three pairs of reanalysis and forecast datasets provided by the European Centre for Medium-Range Weather Forecasting, the Japan Meteorological Agency and the National Centers for Environmental Prediction, participating in the subseasonal-to-seasonal prediction project. The results showed that the predictability was higher when MJO amplitude exceeded unity, consistent with the conventional method in which the error is evaluated as the ensemble-forecast spread. Moreover, the multimodel analysis was also conducted because the proposed method is readily applicable to the multimodel average of ensemble-mean forecasts. The phase dependency of the MJO’s potential predictability is also discussed. View Full-Text
Keywords: Madden–Julian Oscillation; potential predictability; subseasonal to seasonal prediction; multimodel ensemble forecasting Madden–Julian Oscillation; potential predictability; subseasonal to seasonal prediction; multimodel ensemble forecasting
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Ichikawa, Y.; Inatsu, M. An Alternative Estimate of Potential Predictability on the Madden–Julian Oscillation Phase Space Using S2S Models. Atmosphere 2017, 8, 150.

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