| Title |
Statistical Evidence for the Role of Southwestern Indian Ocean Heat Content in the Indian Summer Monsoon Rainfall
|
|---|---|
| Published in |
Scientific Reports, August 2018
|
| DOI | 10.1038/s41598-018-30552-0 |
| Pubmed ID | |
| Authors |
T. Venugopal, M. M. Ali, M. A. Bourassa, Y. Zheng, G. J. Goni, G. R. Foltz, M. Rajeevan |
| 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. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 25% |
| India | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 60 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 20% |
| Student > Ph. D. Student | 10 | 17% |
| Other | 5 | 8% |
| Student > Master | 5 | 8% |
| Student > Bachelor | 3 | 5% |
| Other | 5 | 8% |
| Unknown | 20 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Earth and Planetary Sciences | 24 | 40% |
| Engineering | 5 | 8% |
| Environmental Science | 3 | 5% |
| Physics and Astronomy | 3 | 5% |
| Psychology | 2 | 3% |
| Other | 4 | 7% |
| Unknown | 19 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 29. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 June 2023.
All research outputs
#1,268,667
of 24,406,441 outputs
Outputs from Scientific Reports
#12,396
of 132,856 outputs
Outputs of similar age
#27,099
of 335,006 outputs
Outputs of similar age from Scientific Reports
#327
of 3,665 outputs
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