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Fidelity of CMIP5-simulated teleconnection between Atlantic multidecadal oscillation and Indian summer monsoon rainfall

  • Manish K. Joshi
  • Kyung-Ja Ha
Article

Abstract

The present study aims to provide a relevant ground for attaining deeper perception about the teleconnection between the Atlantic multidecadal oscillation (AMO) and the Indian summer monsoon rainfall (ISMR) in observations as well as in 30 models from the World Climate Research Programme (WCRP) Coupled Model Intercomparison Project Phase 5 (CMIP5). Approximately 73% of models reproduce the internal natural variability allied with AMO, but mostly all underestimate the variance. Amongst these, very few replicate the explicit comma-shaped AMO sea surface temperature (SST) pattern, whereas rest illustrates warm SSTs over the sub-polar region and very weak or non-existent AMO’s signature over the sub-tropical North Atlantic. However, only 53% of models emulate the observed AMO–ISMR relationship. The observational analysis bestows the compelling evidence that the AMO influences ISMR through two physical processes: firstly by modulating the El Niño related anomalous Walker and regional Hadley circulations asymmetrically and secondly through the tropospheric response allied with the Rossby wave train. The models that fail to reproduce the AMO–ISMR teleconnection are incompetent in capturing the first physical mechanism correctly, whereas in general all models show limitations in simulating the second physical mechanism. The results divulge a moderate relationship between the quality of reproducing the AMO pattern and the AMO–ISMR teleconnection in models, particularly with respect to the tropical–extratropical Pacific SST gradients during AMO phases. The models, which do show the observed rainfall response over India, also simulate the large-scale features allied with AMO like the cross-equatorial flow, the tropical easterly jets, the anomalous divergence/convergence over the Indian sub-continent at upper/lower levels, the Webster and Yang Monsoon index, and the Monsoon Hadley Circulation index.

Keywords

Atlantic multidecadal oscillation AMO–ISMR teleconnection CMIP5 models Decadal-to-multidecadal variability Atmospheric circulation Monsoon prediction 

Notes

Acknowledgements

This study was supported by the Korea Ministry of Environment (MOE) as “Graduate School specialized in Climate Change” and GRL grant of the National Research Foundation (NRF) funded by the Korean Government (NRF-2011-0021927) (K.-J. Ha). The authors gratefully acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling that is responsible for CMIP, and we also thank the climate modeling groups for producing and making available their model outputs. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. Support for the Twentieth Century Reanalysis Project V2c dataset is provided by the U.S. Department of Energy, Office of Science Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office. We also thank the anonymous reviewers for their useful comments/suggestions, which helped us in improving the manuscript substantially.

Supplementary material

382_2018_4376_MOESM1_ESM.tif (3.2 mb)
Fig. S1 Variability of the observed low-pass filtered AMO index (shown by red line). The unit of AMO is °C. First and last 10-points are ignored due to end effects of low-pass filter (shown by red dashed line) (TIF 3266 KB)
382_2018_4376_MOESM2_ESM.tif (2.8 mb)
Fig. S2 Scatter plot between the AMO precipitation regressions (units are mm day−1 per standard deviation) averaged over central India and correlation coefficients representing the fidelity of CMIP5 models in simulating the internal natural variability allied with AMO (TIF 2867 KB)
382_2018_4376_MOESM3_ESM.tif (11.7 mb)
Fig. S3 a Regression of JJAS seasonal anomaly of horizontal winds (vector; m s−1) and eddy stream function (shading; 106 m2 s−1) at 200 hPa from NOAA-CIRES 20th century reanalysis V2c (1911–1994) onto the standardized low-pass filtered AMO index. b, c Same as in a, but for the averaged regressions of 16 good and 14 poor CMIP5 models, respectively. Green vectors indicate wind anomalies that are statistically significant at 90% confidence level in at least one of the wind components (meridional or zonal). The units of regression coefficients are in per standard deviation (TIF 12004 KB)
382_2018_4376_MOESM4_ESM.tif (9.7 mb)
Fig. S4 a Regression of JJAS anomaly of velocity potential at 850 hPa from NOAA-CIRES 20th century reanalysis V2c (1911–1994) onto the standardized low-pass filtered AMO index. b, c Same as in a, but for the averaged regressions of 16 good and 14 poor CMIP5 models, respectively. The unit of velocity potential is 106 m2 s−1 per standard deviation. The vectors represent the divergent wind (m s−1) (TIF 9898 KB)
382_2018_4376_MOESM5_ESM.tif (11.4 mb)
Fig. S5 a Regression of JJAS seasonal anomaly of geopotential height (shading; m) at 300 hPa from NOAA-CIRES 20th century reanalysis V2c (1911–1994) onto the standardized low-pass filtered AMO index. The vectors in a represent the wave activity flux (m2 s−2) calculated with regressed anomalies. b, c Same as in a but for the averaged regressions of 16 good and 14 poor CMIP5 models, respectively. The units of regression coefficients are in per standard deviation (TIF 11630 KB)
382_2018_4376_MOESM6_ESM.tif (11.1 mb)
Fig. S6 a Regression of JJAS seasonal anomaly of geopotential height (shading; m) at 500 hPa from NOAA-CIRES 20th century reanalysis V2c (1911–1994) onto the standardized low-pass filtered AMO index. The vectors in a represent the wave activity flux (m2 s−2) calculated with regressed anomalies. b, c Same as in a but for the averaged regressions of 16 good and 14 poor CMIP5 models, respectively. The units of regression coefficients are in per standard deviation (TIF 11366 KB)
382_2018_4376_MOESM7_ESM.tif (10 mb)
Fig. S7 a Regression of JJAS seasonal anomaly of geopotential height (shading; m) at 700 hPa from NOAA-CIRES 20th century reanalysis V2c (1911–1994) onto the standardized low-pass filtered AMO index. The vectors in a represent the wave activity flux (m2 s−2) calculated with regressed anomalies. b, c Same as in a but for the averaged regressions of 16 good and 14 poor CMIP5 models, respectively. The units of regression coefficients are in per standard deviation (TIF 10288 KB)

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© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Research Center for Climate SciencesPusan National UniversityBusanSouth Korea
  2. 2.Department of Atmospheric Sciences, Research Center for Climate SciencesPusan National UniversityBusanSouth Korea

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