Statistical Evidence for the Role of Southwestern Indian Ocean Heat Content in the Indian Summer Monsoon Rainfall

T. Venugopal, M. M. Ali, M. A. Bourassa, Y. Zheng, G. J. Goni, G. R. Foltz, M. Rajeevan

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

This study examines the benefit of using Ocean Mean Temperature (OMT) to aid in the prediction of the sign of Indian Summer Monsoon Rainfall (ISMR) anomalies. This is a statistical examination, rather than a process study. The thermal energy needed for maintaining and intensifying hurricanes and monsoons comes from the upper ocean, not just from the thin layer represented by sea surface temperature (SST) alone. Here, we show that the southwestern Indian OMT down to the depth of the 26 °C isotherm during January–March is a better qualitative predictor of the ISMR than SST. The success rate in predicting above- or below-average ISMR is 80% for OMT compared to 60% for SST. Other January–March mean climate indices (e.g., NINO3.4, Indian Ocean Dipole Mode Index, El Niño Southern Oscillation Modoki Index) have less predictability (52%, 48%, and 56%, respectively) than OMT percentage deviation (PD) (80%). Thus, OMT PD in the southwestern Indian Ocean provides a better qualitative prediction of ISMR by the end of March and indicates whether the ISMR will be above or below the climatological mean value.

Original languageEnglish
Article number12092
Pages (from-to)12092
Number of pages10
JournalScientific Reports
Volume8
Issue number1
DOIs
Publication statusPublished - 14 Aug 2018

Keywords

  • DIPOLE
  • EL-NINO
  • ENSO
  • EQUATORIAL PACIFIC
  • IMPACT
  • PREDICTION
  • SEA-SURFACE TEMPERATURE
  • SST

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