Abstract
Global warming will precariously affect agricultural production and the livelihood of farmers by unpredictably changing the abundance of rainfall and extreme events (Rajendran et al. 2013), which exhibits strong variation of rainfall. Hydropower generation and water availability are some of the other concerns that depend on rainfall variation. Thus, identification of recent climate trends and projection of future climate change are crucial for agro-economic states. As we build strong observational networks and monitor climate indicators, parallel efforts in dynamical modelling should also be practised. Since the special nature of the geographical orientation of the country with low-altitude coastlines and highly elevated mountains at the north, numerical models employed for projections should have sufficiently high spatial resolution to resolve these details. An ultra-high resolution global general circulation model (GCM) at 20-km resolution jointly developed by Meteorological Research Institute (MRI), Japan, and Japan Meteorological Agency (JMA) is used to investigate the future projection of climate change patterns for India. Analysis of four-dimensional multivariable global dataset at ultra-high resolution of 20-km and century time scale for climate change projections and for deriving inferences is highly data intensive and requires high-performance computing with huge memory, visualisation and storage. The projections are determined through time-slice integrations of the model which has shown marked fidelity in representing the present-day climate of India in all seasons especially the mean summer monsoon rainfall over India. Projected future scenario shows coherent and significant enhancement in summer rainfall over most parts of India along with significant reduction in rainfall along the southern parts of the Western Ghats.
The drastic reduction of wind by steep orography predominates over the moisture build-up effect (that causes enhanced rainfall under a warmer environment), in reducing the rainfall over the southern west coast (Rajendran et al. Theor 2012). Over this region, faster rate of increase of temperature at higher levels as compared to lower levels (upper-tropospheric warming effect) leads to increased dry static energy and vertical gross moist static stability which in turn weakens the vertical ascent, large-scale monsoon circulation and thereby rainfall (Rajendran et al. Theor 2012).
Further, the model projects future increase in extreme hot events over India and increased (decreased) occurrence of extreme rainfall events over interior parts of India (the southern Western Ghats). These outcomes are useful for state-specific climate change risk assessments, adaptation planning, improving their climate management strategies and providing information to policy makers.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank AMG, Haylock M, Collins D, Trewin B, Rahimzadeh F, Tagipour A, Ambenje P, Rupa Kumar K, Revadekar J, Griffiths G (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109, 17 pp. doi:10.1029/2005JD006290
Gadgil S, Sajani S (1998) Monsoon simulation in AMIP runs. Clim Dyn 14:659–689
Huffman GJ, Adler RF, Bolvin DT, Gu G, Nelkin EJ, Bowman KP, Hong Y, Stocker EF, Wolff DB (2007) The TRMM multisatellite precipitation analysis (TMPA): quasiglobal, multiyear combined-sensor precipitation estimates at fine scales. J Hyd Meteorol 8:38–55
Kerr RA (2013) Forecasting regional climate change flunks its first test. Science 339:638
Mizuta R, Adachi Y, Yukimoto S, Kusunoki S (2008) Estimation of the future distribution of sea surface temperature and sea ice using the CMIP3 multimodel ensemble mean. Techical Report of MRI, 56. Available at http://www.mrijma.go.jp/Publish/Technical/DATA/VOL56/56.html. 28pp
Nakicenovic N, Swart R (2000) IPCC special report on emission scenarios. IPCC W. G. I., Cambridge University Press, Cambridge, 599 pp
Rajeevan M, Bhate J, Kale JD, Lal B (2006) High resolution daily gridded rainfall data for Indian region: analysis of break and active monsoon spells. Curr Sci 91:296–306
Rajendran K, Kitoh A (2008) Indian summer monsoon in future climate projection by a super high-resolution global model. Curr Sci 95(11):1360–1367
Rajendran K, Kitoh A, Srinivasan J, Mizuta R, Krishnan R (2012) Monsoon circulation interaction with Western Ghats orography under changing climate: projection by a 20-km mesh AGCM. Theor Appl Clim 110(4):555–571, 10.1007/s00704-012-0690-2
Rajendran K, Sajani S, Jayasankar CB, Kitoh A (2013) How dependent is climate change projection of Indian summer monsoon rainfall and extreme events on model resolution. Curr Sci 104(10):1409–1418
Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP (2003) Global analyses of SST, sea ice and night marine air temperature since the late nineteenth century. J Geophys Res (Atm) 108:4407
Yatagai A, Arakawa O, Kamiguchi K, Kawamoto H, Nodzu MI, Hamada A (2009) A 44-year daily gridded precipitation dataset for Asia based on a dense network of rain gauges. SOLA 5:137–140
Acknowledgements
The first author is grateful to Prof. J. Srinivasan, IISc, Bangalore, for initiating the efforts for climate change analysis. KR and SS thank research grants from Department of Environment and Climate Change, Government of Kerala (R-1-166) and collaborative research project with MRI (R-8-118). AK is thankful to KAKUSHIN and SOUSEI Programs for the supporting collaborations for climate change studies. The authors acknowledge the help of Dr. R. Mizuta, MRI.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Rajendran, K., Kitoh, A., Sajani, S. (2014). Ultra-high Resolution Global Model Climate Change Projection for India: Towards a Data Intensive Paradigm. In: Sundaresan, J., Santosh, K., Déri, A., Roggema, R., Singh, R. (eds) Geospatial Technologies and Climate Change. Geotechnologies and the Environment, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-01689-4_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-01689-4_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01688-7
Online ISBN: 978-3-319-01689-4
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)