Abstract

Sensitivity of Asian Summer Monsoon (ASM) precipitation to tropical sea surface temperature (SST) anomalies was estimated from ensemble simulations of two atmospheric general circulation models (GCMs) with an array of idealized SST anomaly patch prescriptions. Consistent sensitivity patterns were obtained in both models. Sensitivity of Indian Summer Monsoon (ISM) precipitation to cooling in the East Pacific was much weaker than to that of the same magnitude in the local Indian–western Pacific, over which a meridional pattern of warm north and cold south was most instrumental in increasing ISM precipitation. This indicates that the strength of the ENSO–ISM relationship is due to the large-amplitude East Pacific SST anomaly rather than its sensitivity value. Sensitivity of the East Asian Summer Monsoon (EASM), represented by the Yangtze–Huai River Valley (YHRV, also known as the meiyu–baiu front) precipitation, is non-uniform across the Indian Ocean basin. YHRV precipitation was most sensitive to warm SST anomalies over the northern Indian Ocean and the South China Sea, whereas the southern Indian Ocean had the opposite effect. This implies that the strengthened EASM in the post-Nino year is attributable mainly to warming of the northern Indian Ocean. The corresponding physical links between these SST anomaly patterns and ASM precipitation were also discussed. The relevance of sensitivity maps was justified by the high correlation between sensitivity-map-based reconstructed time series using observed SST anomaly patterns and actual precipitation series derived from ensemble-mean atmospheric GCM runs with time-varying global SST prescriptions during the same period. The correlation results indicated that sensitivity maps derived from patch experiments were far superior to those based on regression methods.

Highlights

  • The Asian Summer Monsoon (ASM) is one of the most important monsoonal systems in the world and its variability can have profound socioeconomic consequences for over 40 % of the world’s population (Tao and Chen 1987; Wang et al 2001; Wang and LinHo 2002; Ding and Chan 2005; Gadgil and Kumar 2006)

  • In this study, based on two atmospheric general circulation models (GCMs) (NCARCCM3 and Max Planck Institute for Meteorology (MPIM)-ECHAM5), we quantitatively estimated the comprehensive sensitivity of ASM precipitation to tropical sea surface temperature (SST) anomalies by performing ensemble simulations with the prescription of an array of 43 theoretically steady localized SST anomaly patches over the tropics

  • It was established that Indian Summer Monsoon (ISM) precipitation is most sensitive to a meridional dipole of SST anomalies over the Indian and western tropical Pacific oceans, with warming in the north and cooling in the south being most favorable for ISM precipitation

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Summary

Introduction

The Asian Summer Monsoon (ASM) is one of the most important monsoonal systems in the world and its variability can have profound socioeconomic consequences for over 40 % of the world’s population (Tao and Chen 1987; Wang et al 2001; Wang and LinHo 2002; Ding and Chan 2005; Gadgil and Kumar 2006). In this study, based on two atmospheric GCM models, we estimated quantitatively the sensitivity of ASM precipitation to tropical SST anomalies by analyzing a large ensemble of simulations where an array of idealized SST anomalies located over the entire tropical ocean was prescribed. It was interesting to establish which of the two aforementioned methods (statistical regression analysis and dynamical patch experiments) provided the more accurate sensitivity of ASM precipitation to tropical SST forcings. Despite their formal equivalence, the sensitivities derived from the two methods could be different (Shin et al 2010). Better performance of the sensitivity maps derived from the patch experiments, in comparison with the regression-derived sensitivity maps, would imply that the sensitivity results derived from the patch experiments of this study were important

Sensitivity of ISM precipitation
Sensitivity maps
Physical links
Findings
Summary and concluding remarks
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