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.
JJAS mean rainfall for the period 1975-2005 from IMD data and its difference from 28 CMIP5 models. (click on figure for PDF view)
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)
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.
Mishra. S. K., S. Sahany, P. Salunke, 2017: CMIP5 vs. CORDEX over the Indian region: how much do we benefit from dynamical downscaling?. Theoretical and Applied Climatology, DOI 10.1007/s00704-017-2237-z
Dash, Y., S. K. Mishra, S. Sahany, B. K. Panigrahi, 2017: Indian Summer Monsoon Rainfall Prediction: A Comparison of Iterative and Non-Iterative Approaches. Appl. Soft Comput. J., ASOC-4445, 1-13.
Dash, S. K., S. K. Mishra, S. Sahany, V. Venugopal, Ashok K., A. Gupta, 2017: Climate Modeling in India: Present Status and Way Forward. Bulletin of the American Meteorological Society, DOI:10.1175/BAMS-D-16-0322.1, ES183-ES188
Neelin J. D., S. Sahany, S. Stechmann, and D. Bernstein, 2017: Global warming precipitation accumulation increases above the current-climate cutoff scale. Proc. Nat. Acad. Sci., doi: 10.1073/pnas.1615333114., 1258–1263.
Mishra. S. K., S. Sahany, P. Salunke, 2017: Linkages between MJO and summer monsoon rainfall over India and surrounding region. Meteorology and Atmospheric Physics, Vol. 129, Issue 3, DOI: 10.1007/s00703-016-0470-0., 283-296.
Prakash K.R., Vimlesh Pant, 2016: Upper oceanic response to tropical cyclone Phailin in the Bay of Bengal using a coupled atmosphere-ocean model, Ocean Dynamics, doi:10.1007/s10236-016-1020-5, 1-14.
Das, S., S. Dey, S. K. Dash, G. Giuliani and F. Solmon, 2015: “Dust aerosol feedback on the Indian summer monsoon: Sensitivity to absorption property", Journal of Geophysical Research, 120 (18), 9642-9652.
Dash. S. K., S. K. Mishra, K. C. Pattnayak, A. Mamgain, L. Mariotti, E. Coppola, F. Giorgi, G. Giuliani, 2015: Projected Seasonal Mean Summer Monsoon over India and Adjoining Regions for the 21st Century. Theor Appl Climatol 122:581–593 DOI 10.1007/s00704-014-1310-0
McBride J. L., S. Sahany, M. E. Hassim, C. M. Nguyen, S. Y. Lim, R. Rahmat, and W. K. Cheong, 2015: The 2014 Record Dry Spell at Singapore An Intertropical Convergence Zone (ITCZ)-drought. Bulletin of the American Met. Soc., Vol. 96, 12, DOI: 10.1175/BAMS-D-15-00117.1.
Sahany, S., J. D. Neelin, K. Hales, and R. Neale, 2014: Deep Convective Transition Characteristics in the Community Climate System Model and Changes Under Global Warming. J. Clim., Vol. 27(24), 9214-9232.
Tripati, A. K., S. Sahany, D. Pittmann, R. A. Eagle, J. D. Neelin, J. L. Mitchell, L. Beaufort, 2014: Modern and glacial tropical snowlines controlled by sea surface temperature and atmospheric mixing. Nature Geoscience, Vol. 7, 205-209.
Acharya, N., N. A. Shrivastava, B. K. Panigrahi, U. C. Mohanty, 2014: Development of an artificial neural network based multi-model ensemble to estimate the northeast monsoon rainfall over south peninsular India: An application of extreme learning machine", Climate Dynamics, Volume 43, Issue 5-6,Pages 1303-1310
Roy S. B., M. Smith, L. Morris, N. Orlovsky, A. Khalilov, 2014: Impact of the desiccation of the Aral Sea on summertime surface air temperatures, Journal of Arid Environments 110, 79-85.
Kumar, R., and A. Dewan, 2014, Computation Models for Turbulent Thermal Plumes: Recent Advances and Challenges, Heat Transfer Engineering, Vol. 35, No. 4, pp. 367-383
Das, S., S. Dey, S. K. Dash and G. Basil, 2013: “Examining mineral dust transport over the Indian subcontinent using the regional climate model, RegCM 4.1", Atmospheric Research, 134, 64-76.
Evans K., P. Lauritzen , S. K. Mishra , R. Neale, M. A. Taylor, and J. J. Tribbia, 2012: AMIP Simulation with the CAM4 Spectral Element Dynamical Core. Journal of Climate, 26, 689 – 709
Ganguly, D., Philip J. Rasch, Hailong Wang, and Jin-ho Yoon 2012: Fast and slow responses of the South Asian monsoon system to anthropogenic aerosols, Geophysical Research Letters, 39, L18804
Sahany, S., J. D. Neelin, K. Hales, and R. Neale, 2012: Temperature-Moisture Dependence of the Deep Convective Transition as a Constraint on Entrainment in Climate Models. J. Atmos. Sci.
Ganguly, D., Philip J. Rasch, Hailong Wang, and Jin-ho Yoon , 2012: Climate response of the South Asian monsoon system to anthropogenic aerosols, Journal of Geophysical Research, 117, D13209
Panda J., and Maithili Sharan, 2012: Influence of land-surface and turbulent parameterization schemes on regional-scale boundary layer characteristics over northern India. Atmospheric Research, 112, 89-111
Mishra. S. K., 2011: Sensitivity of the Indian Summer Monsoon Rainfall and its Interannual Variation to Model Time Step. Atmospheric Research, 101, 67-77, doi:10.1016/j.atmosres.2011.01.011
Mishra. S. K., 2011: Effects of Convective Adjustment Time Scale on the Simulation of Tropical Climate. Theoretical and Applied Climatology, 107, 211-228, 2011, DOI: 10.1007/s00704-011-0479-8
Mishra. S. K., M. A. Taylor, R. D. Nair, P. H. Lauritzen, H. M. Tufo, and J. J. Tribbia, 2011: Evaluation of the HOMME Dynamical Core in the Aqua-Planet Configuration of NCAR CAM4: Rainfall. Journal of Climate, 24, 4037-4055, doi: 10.1175/2011JCLI3860.1
A. Dewan, 2011, Tackling Turbulent Flows in Engineering, p. 124, Springer, Germany (Indexed in Scopus)
Sahany, S., and S. K. Mishra, 2011: Effects of Convective Scale Downdrafts on the Rainfall Simulation in NCAR-CAM3. Theoretical and Applied Climatology, Vol. 107, Nos. 3-4, 547-562, doi 10.1007/s00704-011-0504-y
Mishra. S. K., M. A. Taylor, R. D. Nair, H. M. Tufo, and J. J. Tribbia, 2011: Performance of the HOMME Dynamical Core in the Aqua-Planet Configuration of NCAR CAM4: Equatorial Waves. Annales Geophysicae, 29, 221 - 227, doi:10.5194/angeo-29-221-2011
Mishra. S. K., and S. Sahany, 2011: Effects of Time Step Size on the Simulation of Tropical Climate in NCAR-CAM3. Climate Dynamics, 37, 689-704, DOI 10.1007/s00382-011-0994-4
Mishra. S. K., and S. Sahany, 2011: Sensitivity of Kelvin Waves and Madden-Julian Oscillation to Convective Downdrafts in the NCAR-CAM3. Atmospheric Science Letters, DOI: 10.1002/asl.334
Mishra. S. K., 2011: Influence of Convective Adjustment Time Scale on the Tropical Transient Activity. Meteorology and Atmospheric Physics, 114, 17-34, 2011. DOI: 10.1007/s00703-011-0154-8
Mishra. S. K., J. Srinivasan, and R. S. Nanjundiah, 2008: The Impact of Time Step on the Intensity of ITCZ in Aquaplanet GCM. Monthly Weather Review, 136, 4077 – 4091, DOI: 10.1175/2008MWR2478
Sahany, S., and R. S. Nanjundiah, 2008: Impact of Convective Downdrafts on Model Simulations Results from Aqua-planet Integrations. Annales Geophysicae, Vol. 26, Issue 7, 1877-1887.