New real-time indices for the quasi-biweekly oscillation over the Asian summer monsoon region

  • Yitian Qian
  • Pang-Chi HsuEmail author
  • Kikuchi Kazuyoshi


The quasi-biweekly oscillation (QBWO), with a periodicity of 10–30 days, is one of the most important modes of intraseasonal variability over the Asian summer monsoon region. Unlike the lower frequency (30–60 days) Madden–Julian Oscillation, which has had several real-time indices proposed for monitoring and predicting its state, there are very few equivalents for the QBWO. Given that extended empirical orthogonal function (EEOF) analysis is arguably more suitable than empirical orthogonal function analysis for capturing the canonical spatial and temporal structure of a propagating wave system, we introduce two new indices for real-time monitoring of the QBWO over the tropical western North Pacific (WNP) and Indian Ocean (IO), separately, by projecting outgoing longwave radiation (OLR) anomalies onto the two leading modes of EEOF analysis for the 10–30-day-filtered OLR anomalies over the two basins during 1980–2012. The newly proposed QBWO indices faithfully represent the vigorous QBWO activities over the WNP and IO, which are underestimated and/or not necessarily well represented by existing indices. It is also shown that the indices are able to reveal the connections between the QBWO and other pronounced phenomena, such as the onset of the South China Sea and Indian monsoons, the occurrence of extreme rainfall events, and tropical cyclone genesis. Thus, monitoring and predicting the evolution of the QBWO in these two basins based on the new QBWO indices should help in the quest to mitigate future damage caused by weather-related disasters at an extended lead time.


Quasi-biweekly oscillation Real-time monitoring EEOF analysis 



This work was supported by the National Key R&D Program of China (2018YFC1505804), China National 973 Project (2015CB453200) and the Research Innovation Program for College Graduates of Jiangsu Province, China (KYCX17_0872). KK acknowledges the support by the NOAA of the U.S., Climate Program Office (Grants NA13OAR4310165 and NAl70AR4310250). This paper is contribution number 10638 of the School of Ocean and Earth Science and Technology, and contribution number 1359 of the International Pacific Research Center.

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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Key Laboratory of Meteorological Disaster of Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjingChina
  2. 2.International Pacific Research CenterUniversity of Hawaii at ManoaHonoluluUSA

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