TY - JOUR

T1 - Statistical Evidence for the Role of Southwestern Indian Ocean Heat Content in the Indian Summer Monsoon Rainfall

AU - Venugopal, T.

AU - Ali, M. M.

AU - Bourassa, M. A.

AU - Zheng, Y.

AU - Goni, G. J.

AU - Foltz, G. R.

AU - Rajeevan, M.

N1 - Publisher Copyright: © 2018, The Author(s).

PY - 2018/8/14

Y1 - 2018/8/14

N2 - 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.

AB - 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.

KW - DIPOLE

KW - EL-NINO

KW - ENSO

KW - EQUATORIAL PACIFIC

KW - IMPACT

KW - PREDICTION

KW - SEA-SURFACE TEMPERATURE

KW - SST

UR - http://www.scopus.com/inward/record.url?scp=85053387028&partnerID=8YFLogxK

U2 - 10.1038/s41598-018-30552-0

DO - 10.1038/s41598-018-30552-0

M3 - Article

C2 - 30108244

AN - SCOPUS:85053387028

VL - 8

SP - 12092

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 12092

ER -