The relationship between the daily dominant monsoon modes of South Asia and SST
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ORIGINAL PAPER
The relationship between the daily dominant monsoon modes of South Asia and SST Namendra Kumar Shahi 1,2
&
Shailendra Rai 2,3 & A. K. Sahai 4
Received: 16 April 2019 / Accepted: 15 June 2020 # Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract The aim of the present work is to scrutinize the relationship between dominant monsoon modes and sea surface temperature (SST) anomalies on a daily time scale based on the observation and P1-P4 lead forecasts of the climate forecast system version 2 (CFSv2) model during 2001–2014. Daily monsoon modes have been obtained by performing multichannel singular spectrum analysis (MSSA) on precipitation anomalies. The modes consist of 42-day oscillatory mode [reconstructed component RC(1, 2)] and a seasonally persistent mode [RC3]. It has been found that the P1 lead forecast of the model is able to simulate accurately the strong contribution of RC3 to the seasonal mean precipitation anomaly on a daily time scale during the weak (normal) monsoon year of 2002 (2010). It has also been observed that the seasonal mean precipitation anomaly and the contribution of RC3 on it are decreased from the P2 lead onwards. The observed phase composites pattern of SST anomalies corresponding to the active and break spells of the summer monsoon reveals a 42-day oscillation of the SST anomalies over the northern part of the Indian and western Pacific Oceans (clearly exhibits the northeastward propagation of the SST anomalies), and it is well captured by the P1 lead forecast. The RC3 shows the strong correlation with the equatorial Pacific Ocean and moderate correlation with the Indian and Atlantic Oceans for a long lead-lag time range. The co-variability of the Indian, Pacific, and the Atlantic Oceans on the long lead-lag time range has been observed in a single mode.
1 Introduction Charney and Shukla (1981) concluded that the interannual variability of the tropical climate is mainly governed by slowly-changing parameters such as sea surface temperature (SST). However, the ability of the SST of the Indian and Pacific Oceans to predict the June-July-August-September (JJAS) seasonal mean rainfall of India has not been strongly established. The well-known El Niño-Southern Oscillation (ENSO)-Indian summer monsoon rainfall (ISMR)
* Namendra Kumar Shahi [email protected] 1
CNRS-IPSL Laboratoire de Météorologie Dynamique, École Polytechnique, Palaiseau, France
2
K. Banerjee Centre of Atmospheric and Ocean Studies, University of Allahabad, Prayagraj, India
3
M. N. Saha Centre of Space Studies, University of Allahabad, Prayagraj, India
4
Indian Institute of Tropical Meteorology (IITM), Pune, India
relationship has weakened in recent decades (Kumar et al. 1999), and the relationship of Indian Ocean dipole (IOD) with ISMR and ENSO is still a matter of debate (Wang et al. 2016). India Meteorological Department (IMD) uses SST predictors in statistical prediction method for forecasting of All-India JJAS seasonal mean rainfall (Rajeevan 2001, Shahi et al. 2019). Rece
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