Editorial Type:
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Article Type:
Research Article

Estimate of the Predictability of Boreal Summer and Winter Intraseasonal Oscillations from Observations

Ruiqiang Ding State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Jianping Li State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Kyong-Hwan Seo Department of Atmospheric Sciences, Pusan National University, Busan, South Korea

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Print Publication:
01 Aug 2011
DOI:
https://doi.org/10.1175/2011MWR3571.1
Page(s):
2421–2438
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Abstract

Tropical intraseasonal variability (TISV) shows two dominant modes: the boreal winter Madden–Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO). The two modes differ in intensity, frequency, and movement, thereby presumably indicating different predictabilities. This paper investigates differences in the predictability limits of the BSISO and the boreal winter MJO based on observational data. The results show that the potential predictability limit of the BSISO obtained from bandpass-filtered (30–80 days) outgoing longwave radiation (OLR), 850-hPa winds, and 200-hPa velocity potential is close to 5 weeks, comparable to that of the boreal winter MJO. Despite the similarity between the potential predictability limits of the BSISO and MJO, the spatial distribution of the potential predictability limit of the TISV during summer is very different from that during winter. During summer, the limit is relatively low over regions where the TISV is most active, whereas it is relatively high over the North Pacific, North Atlantic, southern Africa, and South America. The spatial distribution of the limit during winter is approximately the opposite of that during summer. For strong phases of ISO convection, the initial error of the BSISO shows a more rapid growth than that of the MJO. The error growth is rapid when the BSISO and MJO enter the decaying phase (when ISO signals are weak), whereas it is slow when convection anomalies of the BSISO and MJO are located in upstream regions (when ISO signals are strong).

Corresponding author address: Dr. Jianping Li, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, P.O. Box 9804, Beijing 100029, China. E-mail: ljp@lasg.iap.ac.cn

Abstract

Tropical intraseasonal variability (TISV) shows two dominant modes: the boreal winter Madden–Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO). The two modes differ in intensity, frequency, and movement, thereby presumably indicating different predictabilities. This paper investigates differences in the predictability limits of the BSISO and the boreal winter MJO based on observational data. The results show that the potential predictability limit of the BSISO obtained from bandpass-filtered (30–80 days) outgoing longwave radiation (OLR), 850-hPa winds, and 200-hPa velocity potential is close to 5 weeks, comparable to that of the boreal winter MJO. Despite the similarity between the potential predictability limits of the BSISO and MJO, the spatial distribution of the potential predictability limit of the TISV during summer is very different from that during winter. During summer, the limit is relatively low over regions where the TISV is most active, whereas it is relatively high over the North Pacific, North Atlantic, southern Africa, and South America. The spatial distribution of the limit during winter is approximately the opposite of that during summer. For strong phases of ISO convection, the initial error of the BSISO shows a more rapid growth than that of the MJO. The error growth is rapid when the BSISO and MJO enter the decaying phase (when ISO signals are weak), whereas it is slow when convection anomalies of the BSISO and MJO are located in upstream regions (when ISO signals are strong).

Corresponding author address: Dr. Jianping Li, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, P.O. Box 9804, Beijing 100029, China. E-mail: ljp@lasg.iap.ac.cn
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