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Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon

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Abstract

Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979–2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude–longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.

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References

  • Asharaf, S., Dobler, A., & Ahrens, B. (2012). Soil moisture precipitation feedback processes in the Indian summer monsoon season. Journal of Hydrometeorology, 13, 1461–1474.

    Article  Google Scholar 

  • Barnett, T. P., Dümenil, L., Schlese, U., Roeckner, E., & Latif, M. (1989). The effect of Eurasian snow cover on regional and global climate variations. Journal of the Atmospheric Sciences, 46, 661–686.

    Article  Google Scholar 

  • Barros, A. P., & Lang, T. J. (2003). Monitoring the monsoon in the Himalayas: Observations in central Nepal, June 2001. Monthly Weather Review, 131, 1408–1427.

    Article  Google Scholar 

  • Cook, B. I., Bonan, G. B., & Levis, S. (2006). Soil moisture feedbacks to precipitation in southern Africa. Journal of Climate, 19, 4198–4206.

    Article  Google Scholar 

  • Dorigo, W. A., Gruber, A., De Jeu, R. A. M., Wagner, W., Stacke, T., Loew, A., et al. (2014). Evaluation of the ESA CCI soil moisture product using ground-based observations. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2014.07.023.

    Google Scholar 

  • Dorigo, W., Van Oevelen, P., Wagner, W., Drusch, M., Mecklenburg, S., Robock, A., et al. (2011). A new international network for in situ soil moisture data. EOS Transactions of AGU, 92, 141–142.

    Article  Google Scholar 

  • Dorigo, W., Jeu, R., Chung, D., Parinussa, R., Liu, Y., Wagner, W., & Fernández-Prieto, D. (2012). Evaluating global trends (1988–2010) in harmonized multi-satellite surface soil moisture. Geophysical Research Letters, 39(18). http://doi.org/10.1029/2012GL052988.

  • Dorigo, W. A., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiová, A., Sanchis-Dufau, A. D., et al. (2013). Global automated quality control of in situ soil moisture data from the International Soil Moisture Network. Vadose Zone Journal. https://doi.org/10.2136/vzj2012.0097.

    Google Scholar 

  • Douville, H. (2002). Influence of soil moisture on the Asian and African monsoon. Part II: Interannual variability. Journal of Climate, 15, 701–720.

    Article  Google Scholar 

  • Douville, H., Chauvin, F., & Broqua, H. (2001). Influence of soil moisture on the Asian and African monsoons. Part 1: Mean monsoon and daily precipitation. Journal of Climate, 14, 2381–2404.

    Article  Google Scholar 

  • Froidevaux, P., Schlemmer, L., Schmidli, J., Langhans, W., & Schär, C. (2014). Influence of the background wind on the local soil moisture-precipitation feedback. Journal of Atmospheric Science, 71(2), 782–799.

    Article  Google Scholar 

  • Gates, W. L. (1992). AMIP: The atmospheric model intercomparison project. Bulletin of the American Meteorological Society, 73, 1962–1970.

    Article  Google Scholar 

  • Grossman, R. L., & Durran, D. R. (1984). Interaction of low-level flow with the western Ghat Mountains and offshore convection in the summer monsoon. Monthly Weather Review, 112, 652–672.

    Article  Google Scholar 

  • Kantharao, B., & Rakesh, V. (2017). Observational evidence for the relationship between spring soil moisture and June rainfall over the Indian region. Theoretical and Applied Climatology, 1–15. https://doi.org/10.1007/s00704-017-2116-7.

  • Liu, Y. Y., Dorigo, W. A., Parinussa, R. M., De Jeu, R. A. M., Wagner, W., McCabe, M. F., et al. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals. Remote Sensing of Environment, 123, 280–297.

    Article  Google Scholar 

  • Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., Dijk, A. I. J. M. V., et al. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425–436.

    Article  Google Scholar 

  • Mecklenburg, S., Drusch, M., Kerr, Y. H., Font, J., Martin-Neira, M., Delwart, S., et al. (2012). ESA’s soil moisture and ocean salinity mission: Mission performance and operations. IEEE Transactions on Geoscience and Remote Sensing, 50, 1354–1366.

    Article  Google Scholar 

  • Meehl, G. A. (1994). Influence of the land surface in the Asian summer monsoon: External conditions versus internal feedbacks. Journal of Climate, 7, 1033–1049.

    Article  Google Scholar 

  • Mintz, Y., & Serafini, Y. V. (1992). A global monthly climatology of soil moisture and water balances. Climate Dynamics, 8, 13–27.

    Article  Google Scholar 

  • Namias, J. (1959). Persistence of mid-tropospheric circulations between adjacent months and seasons. In B. Bolin (Ed.), The atmosphere and the sea in motion: scientific contributions to the Rossby memorial volume (pp. 240–248). New York: Rockefeller Institute Press.

  • Namias, J. (1960). Factors in the initiation, perpetuation and termination of drought. Extract of publication No. 51, I. A. S. H. Commission of surface waters 81–94.

  • Namias, J. (1989). Cold waters and hot summers. Nature, 338, 15–16.

    Article  Google Scholar 

  • New, M., Washington, R., Jack, C., & Hewitson, B. (2003). Sensitivity of southern African climate to soil-moisture. CLIVAR Exchanges, No. 8, International CLIVAR Project Office, Southampton, United Kingdom, 45–47.

  • Owe, M., & Van de Griend, A. A. (1998). Comparison of soil moisture penetration depths for several bare soils at two microwave frequencies and implications for remote sensing. Water Resources Research, 34, 2319–2327.

    Article  Google Scholar 

  • Pai, S. D., Sridhar, L., Rajeevan, M., Sreejith, O. P., Satbhai, S., & Mukhopadhyay, B. (2014). Development of a new high spatial resolution (0.25° × 0.25°) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. Mausam, 65, 1–8.

    Google Scholar 

  • Pal, J. S., & Eltahir, E. A. B. (2001). Pathways relating soil moisture conditions to future summer rainfall within a model of the land–atmosphere system. J. Climate, 14, 1227–1242.

    Article  Google Scholar 

  • Rajeevan, M., & Bhate, J. (2009). A high resolution daily gridded rain-fall dataset (1971–2005) for mesoscale meteorological studies. Current Science, 96, 558–562.

    Google Scholar 

  • Rajeevan, M., Bhate, J., Kale, J. D., Behera, B. L. S., Krishnan, R., & Yamagata, T. (2006). High resolution daily gridded rainfall data for the Indian region: analysis of break and active monsoon spells. Current Science, 91, 296–306.

    Google Scholar 

  • Robock, A. A., Schlosser, C., Vinnikov, K. A., Speranskaya, N. A., Entin, J. K., & Liu, S. (1998). Evaluation of the AMIP soil moisture simulations. Global and Planetary Change, 19, 181–208.

    Article  Google Scholar 

  • Sathyanadh, A., Karipot, A., Ranalkar, M., & Prabhakaran, T. (2016). Evaluation of soil moisture data products over Indian region and analysis of spatio-temporal characteristics with respect to monsoon rainfall. Journal of Hydrology, 542, 47–62.

    Article  Google Scholar 

  • Shea, D. J., & Sontakke, N. A. (1995). The annual cycle of precipitation over the Indian subcontinent: Daily, monthly and seasonal statistics, NCAR Technical Note, NCAR/TN-401 + STR

  • Shrivastava, S., Kar, S. C., & Sharma, A. R. (2017). Soil moisture variations in remotely sensed and reanalysis datasets during weak monsoon conditions over central India and central Myanmar. Theoretical and Applied Climatology, 129, 305–320.

    Article  Google Scholar 

  • Shukla, J. (1985). Predictability. In Advances in geophysics (Vol. 28B, pp. 87–122). Academic Press.

  • Shukla, J., & Mintz, Y. (1982). Influence of land-surface evapotranspiration on the Earth’s climate. Science, 215, 1498–1501.

    Article  Google Scholar 

  • Sud, Y. C., & Smith, W. E. (1985). Influence of local land-surface processes on the Indian monsoon: A numerical study. Journal of Climate and Applied Meteorology, 24, 1015–1036.

    Article  Google Scholar 

  • Wagner, W., Dorigo, W., de Jeu, R., Fernandez-Prieto, D., Benveniste, J., Haas, E., & Ertl, M. (2012) Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. XXII ISPRS Congress. Melbourne, Australia.

  • Yeh, T. C., Wetherald, R. T., & Manabe, S. (1984). The effect of soil moisture on the short term climate and hydrology change—A numerical experiment. Monthly Weather Review, 112, 474–490.

    Article  Google Scholar 

  • Zhang, H., McGregor, J. L., Seller, A. H., & Katzfey, K. J. (2004). Impact of land surface model complexity in a regional simulation of a typical synoptic event. Journal of Hydrometeorology, 5, 190–198.

    Article  Google Scholar 

Download references

Acknowledgements

We thank the Director, IITM and Executive Director, CCCR for all the support and necessary infrastructural facilities. We heartily thank Mr. Abdullah Sharief Kizhisseri for timely help to improve the manuscript. The data sets used in this study are properly acknowledged. We are also grateful to anonymous reviewers and the Editor Dr. Vadlamani Murty for constructive review comments.

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  1. Centre for Climate Change Research, Indian Institute of Tropical Meteorology, Pune, 411008, India

    Hamza Varikoden & J. V. Revadekar

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  1. Hamza Varikoden
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  2. J. V. Revadekar
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Correspondence to Hamza Varikoden.

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Varikoden, H., Revadekar, J.V. Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon. Pure Appl. Geophys. 175, 1187–1196 (2018). https://doi.org/10.1007/s00024-017-1740-6

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