Motivation


The figures below show that large biases exist in regional climate simulations over India by the available global climate models used in the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports. We thus need a climate model that is India centric and can be used for reliable climate projections.



Bias in JJAS Rainfall

JJAS mean rainfall for the period 1975-2005 from IMD data and its difference from 28 CMIP5 models. (click on figure for PDF view)

NRMSE vs PCC of JJAS Tas

Pattern correlation coefficient versus the normalized root mean square error of the CMIP5 models for JJAS surface air temperature (as compared to APHRODITE). (click on figure for PDF view)

NRMSE vs PCC of JJAS Rainfall

Pattern correlation coefficient versus the normalized root mean square error of the CMIP5 models for JJAS rainfall (as compared to IMD). (click on figure for PDF view)


Objective



Our team will carry out the required modifications to an existing model and develop a better model for the Indian region through improved physical and computational implementations. Specifically, we will develop the ICCM through process improvements and region-specific customization that will satisfactorily simulate the regional climate of India. Our model will be used for future climate projections at district level to assess the impacts of climate change on agriculture, health, water resources, and the energy sectors. Furthermore, we will downscale the ICCM outputs at ultra-high resolutions for various applications. Additional climate projections for the future scenarios will be made by combining the ICCM projections with soft computing, machine learning, and mathematical optimization techniques. In addition to the research objectives, our CoE will play a leading role in training and nurturing future climate modelers of India in order to sustain and augment this key component of climate science.


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