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Monsoon teleconnections over Indian and Pacific Oceans in Japan Meteorological Agency model simulation
Author(s) -
Theja P. K.,
Sreejith O. P.,
Pai D. S.
Publication year - 2015
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.4319
Subject(s) - hindcast , climatology , teleconnection , environmental science , sea surface temperature , indian ocean dipole , anomaly (physics) , el niño southern oscillation , predictability , precipitation , atmospheric sciences , meteorology , geology , geography , mathematics , statistics , physics , condensed matter physics
The study evaluates various sea surface temperature ( SST ) indices and their teleconnections with Indian summer monsoon rainfall ( ISMR ) simulated by Japan Meteorological Agency ( JMA ) coupled general circulation model ( CGCM ). The indices considered for evaluations are Niño indices (Niño 4, Niño 3.4, Niño 3 and Niño 1 + 2) of Pacific Ocean ( PO ) and Indian Ocean dipole ( IOD ) indices [eastern IO ( IOD E ), western IO ( IOD W ) and dipole mode index ( DMI )] of Indian Ocean ( IO ). The study has been carried out for the season June to September ( JJAS ) using JMA hindcast SST simulated on various initial conditions May, April, March and February (here after leads 0, 1, 2 and 3, respectively) during the period 1979–2010. The extended reconstructed SST ( ERSST ) from National Center for Environmental Prediction is used as observed SST . The important outcome of this study is that the inverse relationship between Niño 3.4 and ISMR is found to be re‐established in recent years after a period of weakening. The JMA model is able to simulate the same with highest skill on lead 1. The PO SST characteristics including climatology, spatial anomaly pattern and interannual variability of Niño indices are well captured in the model lead 0 simulation (correlation coefficient is above 0.80). The model simulation on lead 0 is able to predict the El Niño Southern oscillation ( ENSO ) events during hindcast period with good skill. It is also noted from this study that the model skill to simulate PO SST characteristics is decreasing with increase of lead time. This study is also showing that the model has some deficiency to simulate IO SST characteristics. The model performance in the simulation of IOD events is not appreciable. Thus, this study is recommending JMA model as an efficient ENSO predicting tool, however the model requires improvements to predict IOD events.