Abstract
This study presents a comprehensive assessment of the possible regional climate change over India by using Providing REgional Climates for Impacts Studies (PRECIS), a regional climate model (RCM) developed by Met Office Hadley Centre in the United Kingdom. The lateral boundary data for the simulations were taken from a sub-set of six members sampled from the Hadley Centre’s 17- member Quantified Uncertainty in Model Projections (QUMP) perturbed physics ensemble. The model was run with 25 km × 25 km resolution from the global climate model (GCM) - HadCM3Q at the emission rate of special report on emission scenarios (SRES) A1B scenarios. Based on the model performance, six member ensembles running over a period of 1970-2100 in each experiment were utilized to predict possible range of variations in the future projections for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095) with respect to the baseline period (1975-2005). The analyses concentrated on maximum temperature, minimum temperature and rainfall over the region. For the whole India, the projections of maximum temperature from all the six models showed an increase within the range 2.5°C to 4.4°C by end of the century with respect to the present day climate simulations. The annual rainfall projections from all the six models indicated a general increase in rainfall being within the range 15-24%. Mann-Kendall trend test was run on time series data of temperatures and rainfall for the whole India and the results from some of the ensemble members indicated significant increasing trends. Such high resolution climate change information may be useful for the researchers to study the future impacts of climate change in terms of extreme events like floods and droughts and formulate various adaptation strategies for the society to cope with future climate change.
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Annamalai, H., K. Hamilton, and K. R. Sperber, 2007: The South Asian Summer Monsoon and Its Relationship with ENSO in the IPCC AR4 Simulations. J. Climate, 20, 1071–1092, doi:http://dx.doi.org/10.1175/JCLI4035.1.
Arakawa, A., and V. R. Lamb, 1977: Computational design of the basic dynamical processes of the UCLA general circulation model. Methods in Computational Physics, 17, J. Chang, Ed., Academic Press, 173–265.
Bhaskaran, B., R. G. Jones, J. M. Murphy, and M. Noguer, 1996: Simulations of the Indian summer monsoon using a nested regional climate model: domain size experiments. Clim. Dynam., 12, 573–587.
Bhaskaran, B., A. Ramachandran, R. Jones, and W. Moufouma-Okia, 2012: Regional climate model applications on sub-regional scales over the Indian monsoon region: The role of domain size on downscaling uncertainty. J. Geophys. Res., 117, D10113, doi:10.1029/2012JD017956.
Caesar, J., T. Janes, A. Lindsay, and B. Bhaskaran, 2015: Temperature and precipitation projections over Bangladesh and the upstream Ganges, Brahmaputra and Meghna systems. Environ. Sci. Proc. Impacts, 17, 1047–1056, doi:10.1039/C4EM00650J.
Cherchi, A., A. Alessandri, S. Masina, and A. Navarra, 2011: Effects of increased CO2 levels on monsoon. Clim. Dynam., 37, 83–101, doi: 10.1007/s00382-010-0801-7.
Climate Profile of India Report, 2010: Met Monograph No. Environment Meteorology-01/2010. [Available online at http://www.imd.gov.in/section/climate/StateLevelClimateChangeMonoFinal.pdf].
Cullen, M. J. P., 1993: The unifed forecast/climate model. Meteorol. Mag., 122, 81–94.
Dash, S. K., M. S. Shekhar, and G. P. Singh, 2006: Simulation of Indian Summer monsoon circulation and rainfall using RegCM3. Theor. Appl. Climatol., 86, 161–172, doi:10.1007/s00704-006-0204-1.
Davies, H. C., and R. E Turner, 1977: Updating prediction models by dynamical relaxation: an examination of the technique. Quart. J. Roy. Meteor. Soc., 103, 225–245.
Dimri, A. P., T. Yasunari, A. Wiltshire, P. Kumar, C. Mathison, J. Ridley, and D. Jacob, 2013: Application of regional climate models to the Indian winter monsoon over the western Himalayas. Sci. Total Environ., 468, S36–S47, doi:10.1016/j.scitotenv.2013.01.040.
Dobler, A., and B. Ahrens, 2010: Analysis of the Indian summer monsoon system in the regional climate model COSMO-CLM. J. Geophys. Res., 115, D16101, doi:10.1029/2009JD013497.
Dobler, A., and B. Ahrens, 2011: Four climate change scenarios for the Indian summer monsoon by the regional climate model COSMO-CLM. J. Geophys. Res., 116, D24104, doi:10.1029/2011JD016329.
Douville, H., 2005: Limitations of time-slice experiments for predicting regional climate change over South Asia. Clim. Dynam., 24, 373–391, doi:10.1007/s00382-004-0509-7.
Edwards, J., and A. Slingo, 1996: Studies with a flexible new radiation code I: choosing a configuration for a large-scale model. Quart. J. Roy. Meteor. Soc., 122, 689–720.
Ehret, U., E. Zehe, V. Wulfmeyer, K. Warrach-Sagi, and J. M. Liebert, 2012: HESS Opinions “Should we apply bias correction to global and regional climate model data?” Hydrol. Earth Syst. Sci., 16, 3391–3404, doi:10.5194/hessd-9-5355-2012.
Gadgil, S., and S. Sajini, 1998: Monsoon precipitation in the AMIP runs. Clim. Dynam., 14, 659–689.
Geethalakshmi, V., A. Lakshmanan, D. Rajalakshmi, R. Jagannathan, S. Gummidi, A. P. Ramaraj, K. G. Bhuvaneswari, and R. Anbhazhagan, 2011: Climate change impact assessment and adaptation strategies to sustain rice production in Cauvery basin of Tamil Nadu. Curr. Sci., 101, 3–10.
Gilbert, R. O., 1987: Statistical methods for environmental pollution monitoring. Van Nostrand Reinhold Co., 320 pp.
Giorgi, F., and X. Bi, 2000: A study of internal variability of a regional climate model. J. Geophys. Res., 105, 29503–29521, doi:10.1029/2000JD900269.
Giorgi, F., and L. O. Mearns, 2002: Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the reliability ensemble averaging (REA) method. J. Climate, 15, 1141–1158, doi:http://dx.doi.org/10.1175/1520-0442(2002) 015<1141:COAURA>2.0.CO;2.
Goswami, B. N., V. Venugopal, D. Sengupta, M. S. Madhusoodanan, and P. K. Xavier, 2006: Increasing trend of extreme rain events over India in a warming environment. Science, 314, 1442–1445, doi:10.1126/science.1132027.
Hawkins, E., T. M. Osborne, C. K. Ho, and A. J. Challinor, 2012: Calibration and bias correction of climate projections for crop modelling: an idealised case study over Europe. Agric. forest Meteor., 170, 19–31, doi:10.1016/j.agrformet.2012.04.007.
Hingane, L. S., K. Rupa Kumar, and B. V. Ramana Murthy, 1985: Longterm trends of surface air temperature in India. J. Climatol., 5, 521–528, doi:10.1002/joc.3370050505.
Ho, C. K., D. B. Stephenson, M. Collins, C. A. T. Ferro, and S. J. Brown, 2012: Calibration strategies: a source of additional uncertainty in climate change projections. Bull. Amer. Meteor. Soc., 93, 21–26, doi: http://dx.doi.org/10.1175/2011BAMS3110.1.
Hong, S.-Y., and M. Kanamitsu, 2014: Dynamical Downscaling: Fundamental Issues from an NWP Point of View and Recommendations. Asia-Pac. J. Atmos. Sci., 50, 83–104, doi:10.1007/s13143-014-0029-2.
IPCC, 2007: Climate Change 2007, The physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, 996 pp.
Islam, M. N., M. Rafiuddin, A. U. Ahmed, and R. K. Kolli, 2007: Calibration of PRECIS in employing future scenarios in Bangladesh. Int. J. Climatol, 28, 617–628, doi:10.1002/joc.1559.
Jacob, D., 2007: An inter-comparison of regional climate models for Europe: design of the experiments and model performance. Climatic Change, 81, 31–52, doi:10.1007/s10584-006-9213-4.
Jones, R., M. Noguer, D. Hassell, D. Hudson, S. Wilson, G. Jenkins, and J. Mitchell, 2004: Generating high resolution climate change scenarios using PRECIS. [Available online at http://www.metoffice.gov.uk/media/pdf/6/5/PRECIS_Handbook.pdf].
Jones, R., A. Hartley, C. McSweeney, C. Mathison, and C. Buontempo, 2012: Deriving high resolution climate data for West Africa for the period 1950-2100. UNEP-WCMC Technical Report, 25 pp.
Julien, C., M. Clemence, P. Benjamin, and R. Yves, 2011: Quantifying internal variability in a regional climate model: a case study for Southern Africa. Clim. Dynam., 37, 1335–1356, doi:10.1007/s00382-011-1021-5.
Kang, I. S., K. Jin, B. Wang, K. M. Lau, J. Shukla, and V. Krishnamurthy, 2002: Intercomparison of the climatological variations of Asian summer monsoon precipitation simulated by 10 GCMs. Clim. Dynam., 19, 383–395, doi:10.1007/s00382-002-0245-9.
Kershaw, R., and D. Gregory, 1997: Parametrization of momentum transport by convection. Part I. Theory and cloud modelling results. Quart. J. Roy. Meteor. Soc., 123, 1133–1151.
Kotroni, V., S. Lykoudis, K. Lagouvardos, and D. Lalas, 2008: A fine resolution regional climate change experiment for the Eastern Mediterranean: Analysis of the present climate simulations. Glob. Planet. Chang., 64, 93–104, doi:10.1016/j.gloplacha.2008.10.003.
Krishna Kumar, K., K. Kamala, B. Rajagoopalan, M. P. Hoerling, J. K. Eischeid, S. K. Patwardhan, G. Srinivasan, B. N. Goswami, and R. Nemani, 2010: The once and future pulse of Indian monsoonal climate. Clim. Dynam., 36, 2159–2170, doi:10.1007/s00382-010-0974-0.
Krishna Kumar, K., S. K. Patwardhan, A. Kulkarni, K. Kamala, R. K. Koteswara, and R. Jones, 2011: Simulated projections for summer monsoon climate over India by a high-resolution regional climate model (PRECIS). Curr. Sci., 101, 3–10.
Kripalani, R. H., J. H. Oh, A. Kulkarni, S. S. Sabade, and H. S. Chaudhari, 2007: South Asian summer monsoon precipitation variability: Coupled climate model simulations and Projections under IPCC AR4. Theor. Appl. Climatol., 90, 133–159, doi:10.1007/s00704-006-0282-0.
Kulkarni, A., S. Patwardhan, K. Krishna Kumar, K. Ashok, and R. Krishnan, 2013: Projected climate change in the Hindu Kush-Himalayan region by using the high-resolution regional climate model PRECIS. Mt. Res. Dev., 33, 142–151, doi:http://dx.doi.org/10.1659/MRD-JOURNAL-D-11-00131.1.
Kumar, P., 2013: Downscaled climate change projections with uncertainty assessment over India using a high resolution multimodel approach. Sci. Total Environ., 468, S18–S30, doi:10.1016/j.scitotenv.2013.01.051.
Lal, M., T. Z. Nozawa, S. Emori, H. Harasawa, K. Takahashi, M. Kimoto, A. Abe-Ouchi, T. Nakajima, T. Takemura, A. Numaguti, 2001: Future climate change: implication for Indian summer monsoon and its variability. Curr. Sci., 81, 1196–1207
Maraun, D., 2012: Nonstationarities of regional climate model biases in European seasonal mean temperature and precipitation sums. Geophys. Res. Lett., 39, L06706, doi:10.1029/2012GL051210.
Marengo, J. A., R. Jones, L. M. Alves, and M. C. Valverde, 2009: Future change of temperature and precipitation extremes in South America as derived from the PRECIS regional climate modeling system. Int. J. Climatol., 29, 2241–2255, doi:10.1002/joc.1863.
May, W., 2004: Variability and extremes of daily rainfall during the Indian summer monsoon in the period 1901-1989. Glob. Planet. Chang., 44, 83–105, doi:10.1016/j.gloplacha.2004.06.007.
May, W., 2011: The sensitivity of the Indian summer monsoon to a global warming of 2°C with respect to pre-industrial times. Clim. Dynam., 37, 1843–1868, doi:10.1007/s00382-010-0942-8.
McGregor, J. L., 1997: Regional climate modeling. Meteor. Atmos. Phys., 63, 105–117.
May, W., 2013: Recent developments in variable-resolution global climate modelling. Climatic Change, 119, doi:10.1007/s10584-013-0866-5.
McSweeney, C. F., and G. J. Richard, 2010: Selecting members of the ‘QUMP’ perturbed-physics ensemble for use with PRECIS. Met office Hadley Centre. [Available online at http://www.metoffice.gov.uk/media/pdf/e/3/SelectingCGMsToDownscale.pdf].
May, W., G. J. Richard, and B. B. B. Ben, 2012: Selecting Ensemble Members to Provide Regional Climate Change Information. J. Climate, 25, 7100–7121, doi:http://dx.doi.org/10.1175/JCLI-D-11-00526.1.
Meehl, G. A., 2007: Global Climate Projections. In Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, 747–845.
Mesinger, F., 1981: Horizontal Advection Schemes of a Staggered Grid -An Enstrophy and Energy-Conserving Model. Mon. Wea. Rev., 109, 467–478, doi:http://dx.doi.org/10.1175/1520-0493(1981)109<0467:HASOAS> 2.0.CO;2.
Met Office Report, 2012: Climate Change in Maharashtra. [Available online at http://www.metoffice.gov.uk/media/pdf/c/a/GOM_brochure_for_web.pdf].
Mohammad, A. R., and R. M. Mujibur, 2012: A Comprehensive Modeling Study on Regional Climate Model (RCM) Application-Regional Warming Projections in Monthly Resolutions under IPCC A1B Scenario. Atmosphere, 3, 557–572, doi:10.3390/atmos3040557.
Mukhopadhyay, P., S. Taraphdar, B. N. Goswami, and K. Krishna Kumar, 2010: Indian summer monsoon precipitation climatology in a high resolution regional climate model: Impact of convective parameterization on systematic biases. Wea. Forecasting, 25, 369–387, doi: http://dx.doi.org/10.1175/2009WAF2222320.1.
Murphy, J. M., 2009: UK Climate Projections Science Report: Climate change projections. Met Office Hadley Centre. [Available online at http://ukclimateprojections.metoffice.gov.uk/media. jsp?mediaid=87893].
Nakienovi, N., 2000: Special report on emissions scenarios. Cambridge University Press, 612 pp.
Nazrul Islam, Md., 2009: Rainfall and Temperature Scenario for Bangladesh. Open Atmos. Sci. J., 3, 93–103.
Önöz, B., and M. Bayazit, 2012: The Power of Statistical Tests for Trend Detection. Turkish J. Eng. Environ. Sci., 27, 247–251.
Pant, G. B., and K. Rupa Kumar, 1997: Climates of South Asia. John Wiley & Sons, 344 pp.
Parthasarathy, B., A. A. Munot, and D. R. Kothawale, 1994: All India monthly and seasonal rainfall series 1871-1993. Theor. Appl. Climatol., 49, 217–224.
Prasanta Kumar Bal, A. Ramachandran, R. Geetha, B. Bhaskaran, P. Thirumurugan, J. Indumathi, and N. Jayanthi, 2016: Climate Change Projections for Tamil Nadu: Deriving High Resolution Climate Data by a Downscaling Approach Using PRECIS. Theor. Appl. Climatol., 123, 523–535, doi:10.1007/s00704-014-1367-9.
Rajbhandari, R., A. B. Shrestha, A. Kulkarni, S. K. Patwardhan, and S. R. Bajracharya, 2014: Projected changes in climate over the Indus river basin using a high resolution regional climate model (PRECIS). Clim. Dynam., 44, 339–357, doi:10.1007/s00382-014-2183-8.
Rajeevan, M., and J. Bhate, 2008: A high resolution daily gridded rainfall data set (1971-2005) for mesoscale meteorological studies. NCC Research Report, No 9, India Meteorological Department, 14 pp.
Rajeevan, M., and R. S. Nanjundiah, 2009: Coupled model simulations of twentieth century climate of the Indian summer monsoon. Current trends in science: platinum jubilee special, N. Mukunda, Ed., Indian Academy of Sciences, 537–568.
Revadekar, J. V., D. R. Kothawale, S. K. Patwardhan, G. B. Pant, and K. Rupa Kumar, 2012: About the observed and future changes in temperature extremes over India. Nat. Hazards, 60, 1133–1155.
Reichler, T., and J. Kim, 2008: How well do coupled models simulate today's climate? Bull. Amer. Meteor. Soc., 89, 303–311, doi:http://dx.doi.org/10.1175/BAMS-89-3-303.
Rupa Kumar, K., and R. G. Ashrit, 2001: Regional aspects of global climatic change simulation: validation and assessment of climate response over Indian monsoon region to transient increase of greenhouse gases and sulphate aerosols. Mausam, 52, 229–244.
Rupa Kumar, K., A. K. Sahai, K. K. Kumar, S. K. Patwardhan, P. K. Mishra, J. V. Revadekar, K. Kamala, and G. B. Pant, 2006: High resolution climate changes scenarios for India for the 21st century. Curr. Sci., 90, 334–345.
Simmons, A., S. Uppala, D. Dee, and S. Kobayashi, 2007: ERA-Interim: new ECMWF reanalysis products from 1989 onwards. ECMWF Newsletter, 110, 25–35.
Sperber, K. R., and T. N. Palmer, 1996: Interannual Tropical Rainfall Variability in General Circulation Model simulations associated with the atmospheric model intercomparison project. J. Climate, 9, 2727–2750, doi:http://dx.doi.org/10.1175/1520-0442(1996)009<2727:ITRVIG> 2.0.CO;2.
Srivastava, A. K., M. Rajeevan, and S. R. Kshirsagar, 2008: Development of a high resolution daily gridded temperature data set (1969-2005) for the Indian region. Atmos. Sci. Lett., 10, 249–254.
Teutschbein, C., and J. Seibert, 2013: Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions? Hydrol. Earth Syst. Sci., 17, 5061–5077, doi:10.5194/hess-17-5061-2013.
Turner, A. G., 2011: Modeling monsoons: Understanding and predicting current and future behavior. The Global Monsoon System: Research and Forecast. 2nd ed., C.-P. Chang et al. Eds., World Scientific, 421–454.
Turner, A. G., and H. Annamalai, 2012: Climate change and the South Asian summer monsoon. Nat. Climatic Change, 2, 587–595, doi:10.1038/nclimate1495.
Uppala, S. M., 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 2961–3012, doi:10.1256/qj.04.176.
Wang, B., I. S. Kang, and Y. J. Lee, 2004a: Ensemble simulations of Asian-Australian monsoon variability during 1997/1998 El Nino by 11 AGCMs. J. Climate, 17, 803–818, doi:10.1029/2005GL022734.
Wang, B., Q. Ding, X. Fu, I. S. Kang, K. Jin, J. Shukla, and F. Doblas-Reyes, 2005: Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys. Res. Lett., 32, L15711, doi:10.1029/2005GL022734.
Wang, Y., L. R. Leung, J. L. McGregor, D.-K. Lee, W.-C. Wang, Y.-H. Ding, and F. Kimura, 2004b: Regional climate modeling: Progress, challenges, and prospects. J. Meteor. Soc. Japan, 82, 1599–1628, doi:http://doi.org/10.2151/jmsj.82.1599.
Zhang, Y., Y. L. Xu, W. J. Dong, L. J. Cao, and M. Sparrow, 2006: A future climate scenario of regional changes in extreme climate events over China using the PRECIS climate model. Geophys. Res. Lett., 33, L24702, doi:10.1029/2006GL027229.
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An erratum to this article is available at http://dx.doi.org/10.1007/s13143-016-0044-6.
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Bal, P.K., Ramachandran, A., Palanivelu, K. et al. Climate change projections over India by a downscaling approach using PRECIS. Asia-Pacific J Atmos Sci 52, 353–369 (2016). https://doi.org/10.1007/s13143-016-0004-1
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DOI: https://doi.org/10.1007/s13143-016-0004-1