Ultra-high Resolution Global Model Climate Change Projection for India: Towards a Data Intensive Paradigm

by K. Rajendran, A. Kitoh, S. Sajani

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. 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. 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.


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