Climate Dynamics

, Volume 48, Issue 7–8, pp 2581–2596 | Cite as

Retrospective seasonal prediction of summer monsoon rainfall over West Central and Peninsular India in the past 142 years

  • Juan Li
  • Bin Wang
  • Young-Min Yang


Prediction of Indian summer (June–September) rainfall on regional scales remains an open issue. The operational predictions of West Central Indian summer rainfall (WCI-R) and Peninsular Indian summer rainfall (PI-R) made by the Indian Meteorological Department (IMD) had no skills during 2004–2012. This motivates the present study aiming at better understanding the predictability sources and physical processes governing summer rainfall variability over these two regions. Analysis of 133 year data reveal that although the lower boundary forcing that associated with enhanced WCI-R and PI-R featured a similar developing La-Nina and “east high west low” sea-level pressure (SLP) dipole pattern across the Indo-Pacific, the anomalous high sea surface temperature (SST) over the northern Indian Ocean and weak low pressure over northern Asia tended to enhance PI-R but reduce WCI-R. Based on our understanding of physical linkages with the predictands, we selected four and two causative predictors for predictions of the WCI-R and PI-R, respectively. The intensified summer WCI-R is preceded by (a) Indian Ocean zonal dipole-like SST tendency (west-warming and east-cooling), (b) tropical Pacific zonal dipole SST tendency (west-warming and east-cooling), (c) central Pacific meridional dipole SST tendency (north-cooling and south-warming), and (d) decreasing SLP tendency over northern Asia in the previous season. The enhanced PI-R was lead by the central-eastern Pacific cooling and 2-m temperature cooling tendency east of Lake Balkhash in the previous seasons. These causative processes linking the predictors and WCI-R and PI-R are supported by ensemble numerical experiments using a coupled climate model. For the period of 1871–2012, the physics-based empirical (P-E) prediction models built on these predictors result in cross-validated forecast temporal correlation coefficient skills of 0.55 and 0.47 for WCI-R and PI-R, respectively. The independent forecast skill is significantly higher than the skill of operational seasonal forecast made by the IMD for the period of 2004–2012. These prediction models offer a tool for seasonal prediction and their retrospective forecast skills provide an estimation of the lower bound of the predictability for WCI-R and PI-R.


Seasonal prediction Summer rainfall predictability West Central India Peninsular India Physics-based empirical (P-E) prediction models 



This study is supported by the Atmosphere–Ocean Research Center (AORC) and IPRC at University of Hawaii and the National Research Foundation (NRF) of Korea through a Global Research Laboratory (GRL) grant of the Korean Ministry of Education, Science and Technology (MEST, #2011-0021927). The AORC is partially funded by Nanjing University of Information Science and Technology (NUIST). This is the NUIST-Earth System Modeling Center (ESMC) publication number 116, the SOEST publication number 9642, the IPRC publication number 1199.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Earth System Modeling CenterNanjing University of Information Science and TechnologyNanjingChina
  2. 2.Department of Atmospheric Sciences and International Pacific Research CenterUniversity of Hawaii at ManoaHonoluluUSA

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