Theoretical and Applied Climatology

, Volume 127, Issue 1–2, pp 381–392 | Cite as

Impact of aerosols and cloud parameters on Indian summer monsoon rain at intraseasonal scale: a diagnostic study

  • Charu SinghEmail author
  • Litty Thomas
  • K. Kishore Kumar
Original Paper


Aerosol and cloud parameters are known to be the influencing factors of the Indian summer monsoon rainfall (ISMR) variability at interannual and intraseasonal scales. In this study, we investigate the impact of remotely sensed aerosol optical depth and associated parameters (cloud fraction, cloud optical depth, cloud effective radii, cloud top pressure, and single-scattering albedo) on the individual active (break) spells of the Indian summer monsoon (ISM) season. Active and break spells are identified using satellite-derived data sets over the central Indian (CI) region. The present analysis suggests that the CI region is loaded with higher aerosol concentration and that rainfall is significantly negatively correlated with aerosol optical depth (significant at 1 % significance level) over CI. Contrary to the composite-based previous studies, it has been observed that the aerosol loading and cloud properties are considerably different during the individual active and break events. For break events, composite representation shows that aerosols are stacked along the Himalayan region while all individual break events do not portray this type of aerosol dispensation. It appears from the present analysis that the aerosols may impact the intraseasonal variability of ISMR through its indirect effect by altering the cloud properties and consequently the rainfall. Therefore, aerosols are supposed to be a regional contributor in affecting the intraseasonal variability of summer monsoon rainfall.


Aerosol Optical Depth Indian Summer Monsoon Outgoing Longwave Radiation Tropical Rainfall Measuring Mission Indian Summer Monsoon Rainfall 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The present work is a part of TDP and the first author would like to thank IIRS for providing computational facility to carry out the present work. Analyses and visualisations used in this paper were produced with the Giovanni online data system, developed and maintained by the NASA GES DISC. The rainfall and other data sets are acquired from the web links, and We also acknowledge the MODIS mission scientists and associated NASA personnel for the production of the data used in this research. SSA data set is procured from and authors thank the OMI International Science Team for the satellite data used in this study. The HYSPLIT model was used from the and the authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and/or READY website ( used in this publication. We also thank anonymous reviewers and editor for their constructive comments.

Supplementary material

704_2015_1640_MOESM1_ESM.doc (389 kb)
Fig. S1 (DOC 389 kb)
704_2015_1640_MOESM2_ESM.doc (344 kb)
Fig. S2 (DOC 343 kb)


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Copyright information

© Springer-Verlag Wien 2015

Authors and Affiliations

  1. 1.Indian Institute of Remote SensingISRODehradunIndia
  2. 2.Former Student of Indian Institute of Remote SensingISRODehradunIndia
  3. 3.Space Physics Laboratory, Vikram Sarabhai Space CentreISROTrivandrumIndia

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