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Projected Change and Variability Assessment of Indian Summer Monsoon Precipitation in South Asia CORDEX Domain Under High-Emission Pathway

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Abstract

The regional climate model version 4 (RegCM4) is analyzed in this study to assess Indian summer monsoon precipitation (ISMP) over six homogeneous precipitation regions and various meteorological subdivisions of India embedded therein during a reference period (1976–2005) and mid- (2031–2060) and far-future (2070–2099) periods under the RCP8.5 scenario over the South Asia CORDEX domain. A Coupled Model Intercomparison Project (CIMIP5) global model GFDL-ESM2M provides initial and boundary conditions to the RegCM4 under the high-emission scenario RCP8.5. RegCM4 precipitation fields are validated against observed India Meteorological Department (IMD) and Asian Precipitation-Highly Resolved Observational Data Integration Toward Evaluation (APHRODITE) precipitation datasets, while wind and specific humidity fields obtained from RegCM4 are validated against National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and the parent GFDL model integrated fields. Model comparisons indicate that RegCM4 captures the regional characteristics of ISMP satisfactorily in terms of biases, trends, interannual variability, and circulation patterns. RegCM4 precipitation fields show high correlations of 0.9 and 0.8 with those of IMD and APHRODITE, respectively, and RegCM shows better skill in comparison with GFDL over about 68% of meteorological subdivisions. RegCM4 projects increases in precipitation by about 15.3% (28.4%), 5.1% (16.2%), and 5.4% (18.4%) respectively over the Northwest (NW), Northeast (NE) and Hilly Regions (HR) in the mid-(far-)future but decreases in precipitation over the Peninsular (PE) region by about −1.5% (−15.7%) during the same period. A similar precipitation change pattern is also found when analyzing the probability distribution functions (PDFs) over the same regions. The precipitation intensity (95th percentile) shows increases above 40% over numerous subdivisions of the West Central (WC), NW, and HR regions. The present analysis also reveals significant increases of more than 50% in mean precipitation over several meteorological subdivisions. Analysis of the circulation fields depicts a northward shift of the high-precipitation belt while high-pressure systems dominate the peninsular region when approaching the central India global warming scenario. It is interesting to note that the extreme precipitation index Rx5day exactly follows the pattern of projected increase in mean precipitation. In addition, it is noted that the projected variability and change in the mean precipitation are less frequent than for RX5day, while a consistently stronger spread in variability is projected in the mid- to far-future under the warming scenario.

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References

  • Annamalai, H., Hamilton, K., & Sperber, K. R. (2007). The south Asian summer monsoon and its relationship to ENSO in the IPCC AR4 simulations. Journal of Climate,20, 1071–1092. https://doi.org/10.1175/JCLI4035.1.

    Article  Google Scholar 

  • Ashfaq, M., Shi, Y., Tung, W. W., Trapp, R. J., Gao, X., Pal, J. S., et al. (2009). Suppression of south Asian summer monsoon precipitation in the 21st century. Geophysical Research Letters,36, L01704. https://doi.org/10.1029/2008GL036500.

    Article  Google Scholar 

  • Boos, W. R., Hurley, J. V., & Murthy, V. S. (2015). Adiabatic westward drift of Indian monsoon depressions. Quarterly Journal of the Royal Meteorological Society, 141(689), 1035–1048.

    Article  Google Scholar 

  • Chen, Y.-C. (2017). A tutorial on kernel density estimation and recent advances. Biostatistics & Epidemiology. https://doi.org/10.1080/24709360.2017.1396742.

    Article  Google Scholar 

  • Christensen, J. H., Krishna Kumar, K., Aldrian, E., An, S. I., Cavalcanti, I. F. A., de Castro, M., et al. (2013). Climate phenomena and their relevance for future regional climate change. In T. F. Stocker (Ed.), Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 1217–1308). Cambridge: Cambridge University Press.

    Google Scholar 

  • Das, P. K., Chakraborty, A., & Seshasai, M. V. R. (2014). Spatial analysis of temporal trend of rainfall and rainy days during the Indian Summer Monsoon season using daily gridded (0.5 × 0.5) rainfall data for the period of 1971–2005. Meteorological Applications,21, 481–493.

    Article  Google Scholar 

  • Dash, S. K., Jenamani, R. K., Kalsi, S. R., & Panda, S. K. (2007). Some evidence of climate change in twentieth-century India. Climatic Change,85, 299–321.

    Article  Google Scholar 

  • Dash, S. K., Kulkarni, M. A., Mohanty, U. C., & Prasad, K. (2009). Changes in the characteristics of rain events in India. Journal of Geophysical Research Atmospheres,114, D10. https://doi.org/10.1029/2008JD010572.

    Article  Google Scholar 

  • Dash, S. K., Mamgain, A., Pattnayak, K. C., & Giorgi, F. (2013). Spatial and temporal variations in Indian summer monsoon rainfall and temperature: An analysis based on RegCM3 simulations. Pure and Applied Geophysics. https://doi.org/10.1007/s00024-012-0567-4.

    Article  Google Scholar 

  • Dash, S. K., Mishra, S. K., Pattnayak, K. C., Mamgain, A., Mariotti, L., Coppola, E., et al. (2015). Projected seasonal mean summer monsoon over India and adjoining regions for the twenty-first century. Theoretical and Applied Climatology,122, 581–593. https://doi.org/10.1007/s00704-014-1310-0.

    Article  Google Scholar 

  • Dash, S. K., Shekhar, M. S., & Singh, G. P. (2006). Simulation of Indian summer monsoon circulation and rainfall using RegCM3. Theoretical and Applied Climatology,86, 161–172. https://doi.org/10.1007/s00704-006-0204-1.

    Article  Google Scholar 

  • Dickinson, E., Henderson-Sellers, A. & Kennedy, J. (1993). Biosphere-atmosphere transfer scheme (BATS) version 1e as coupled to the NCAR community climate model NCAR Tech. Note TN383 + STR, p 72.

  • Elguindi, N., Bi, X., Giorgi, F., Nagarajan, B., Pal, J., Solmon, F., Rauscher, S., Zakey, A. (2010). RegCM Version 4.0 User’s guide.

  • Emanuel, K. A., & Zivkovic-Rothman, M. (1999). Development and evaluation of a convection scheme for use in climate models. Journal of Atmospheric Science,56, 1766–1782.

    Article  Google Scholar 

  • Fan, F., Mann, M. E., Lee, S., & Evans, J. L. (2012). Future changes in the South Asian summer monsoon: An analysis of the CMIP3 multimodel projections. Journal of Climate,25, 3909–3928. https://doi.org/10.1175/JCLI-D-11-00133.1.

    Article  Google Scholar 

  • Frich, P., Alexander, L. V., Della-Marta, P. M., Gleason, B., Haylock, M., Tank, A. K., et al. (2002). Observed coherent changes in climatic extremes during the second half of the twentieth century. Climate Research,19, 193–212.

    Article  Google Scholar 

  • Fritsch, J. M., & Chappell, C. F. (1980). Numerical prediction of convectively driven mesoscale pressure systems. Part I: convective parameterization. J Atmos Sci,37(8), 1722–1733.

    Article  Google Scholar 

  • Fu, C., Diaz, H. F., Dong, D., & Fletcher, J. O. (1999). Changes in atmospheric circulation over northern hemisphere oceans associated with the rapid warming of the 1920s. International Journal of Climatology,19, 581–606.

    Article  Google Scholar 

  • Ghosh, S., Vittal, H., Sharma, T., Karmakar, S., Kasiviswanathan, K. S., Dhanesh, Y., et al. (2016). Indian summer monsoon rainfall: implications of contrasting trends in the spatial variability of means and extremes. PLoS One,11, e0158670. https://doi.org/10.1371/journal.pone.0158670.

    Article  Google Scholar 

  • Giorgi, F., Coppola, E., Solmon, F., et al. (2012). RegCM4: Model description and preliminary tests over multiple CORDEX domains. Climate Research,52, 7–29.

    Article  Google Scholar 

  • Giorgi, F., Marinucci, M. R., & Bates, G. T. (1993a). Development of a second-generation regional climate model (RegCM2). Part I: Boundary-layer and radiative transfer processes. Monthly Weather Review,121, 2794–2813. https://doi.org/10.1175/1520-0493(1993)121%3c2794:DOASGR%3e2.0.CO;2.

    Article  Google Scholar 

  • Giorgi, F., Marinucci, M. R., Bates, G. T., & De Canio, G. (1993b). Development of a second-generation regional climate model (RegCM2). Part II: Convective processes and assimilation of lateral boundary conditions. Monthly Weather Review,121, 2814–2832. https://doi.org/10.1175/1520-0493(1993)121%3c2814:DOASGR%3e2.0.CO;2.

    Article  Google Scholar 

  • Godbole, R. V. (1977). The composite structure of the monsoon depression. Tellus,29, 25–40. https://doi.org/10.3402/tellusa.v29i1.11327.

    Article  Google Scholar 

  • Goswami, B. N., Venugopal, V., Sengupta, D., Madhusoodanan, M. S., & Xavier, P. K. (2006). Increasing trend of extreme rain events over India in a warming environment. Science,314, 1442–1445. https://doi.org/10.1126/science.1132027.

    Article  Google Scholar 

  • Gramacki, A. (2018). Studies in Big Data 37 nonparametric kernel density estimation and its computational aspects, 37, https://doi.org/10.1007/978-3-319-71688-6.

  • Grell, G. A. (1993). Prognostic evaluation of assumptions used by cumulus parameterizations. Monthly Weather Review,121, 754–787.

    Article  Google Scholar 

  • Guhathakurta, P., & Rajeevan, M. (2008). Trends in the rainfall pattern over India. International Journal of Climatology,28, 1453–1469.

    Article  Google Scholar 

  • Holtslag, A. A. M., De Bruijn, E. I. F., & Pan, H.-L. (1990). A high resolution air mass transformation model for short-range weather forecasting. Monthly Weather Review,118, 1561–1575.

    Article  Google Scholar 

  • Hu, Z. Z., Latif, M., Roeckner, E., & Bengtsson, L. (2000). Intensified Asian summer monsoon and its variability in a coupled model forced by increasing greenhouse gas concentrations. Geophysical Research Letter,27, 2681–2684. https://doi.org/10.1029/2000GL011550.

    Article  Google Scholar 

  • IPCC. (2007). Climate change 2007: The physical science basis. In S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, & H. L. Miller (Eds.), Contribution of Working Group 1 to the fourth assessment report of the intergovernmental panel on climate change. Cambridge: Cambridge University Press.

    Google Scholar 

  • IPCC (2013) Climate change 2013: the physical science basis. In: Contribution of Working Group 1 to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge.

  • Jagannathan, P., & Parthasarathy, B. (1973). Trends and periodicities of rainfall over India. Monthly Weather Review,101, 371–375. https://doi.org/10.1175/1520-0.

    Article  Google Scholar 

  • Jain, S. K., & Kumar, V. (2012). Trend analysis of rainfall and temperature data for India. Current Science,102, 37–49.

    Google Scholar 

  • Jin, Q., & Wang, C. (2017). A revival of Indian summer monsoon rainfall since 2002. Nature Climate Change,7(8), 587. https://doi.org/10.1038/nclimate3348.

    Article  Google Scholar 

  • Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., et al. (1996). The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society,77, 437–472.

    Article  Google Scholar 

  • Kiehl, J.T., Hack, J.J., Bonan, G.B., Boville, B.A., Williamson, D.L., Rasch, P.J. (1996). Description of the NCAR Community Climate Model (CCM3). NCAR Tech Note NCAR/TN-420 + STR. https://doi.org/10.5065/d6ff3q99.

  • Kitoh, A., Yukimoto, S., Noda, A., & Motoi, T. (1997). Simulated changes in the Asian summer monsoon at times of increased atmospheric CO2. Journal of the Meteorological Society of Japan,75, 1019–1031. https://doi.org/10.2151/jmsj1965.75.6_1019.

    Article  Google Scholar 

  • Klein, T.A., Zwiers, F., Zhang, X. (2009). Guidelines on analysis of extremes in a changing climate in support of informed decisions for adaptation. Climate Data Monit WCDMP-No. 72, WMO-TD N.1500: 56.

  • Kripalani, R. H., Kulkarni, A., Sabade, S. S., & Khandekar, M. L. (2003). Indian monsoon variability in a global warming scenario. Natural Hazards,29, 189–206. https://doi.org/10.1023/A:1023695326825.

    Article  Google Scholar 

  • Kripalani, R. H., Oh, J. H., Kulkarni, A., Sabade, S. S., & Chaudhari, H. S. (2007). South Asian summer monsoon precipitation variability: Coupled climate model simulations and projections under IPCC AR4. Theoretical and Applied Climatology,90, 133–159. https://doi.org/10.1007/s00704-006-0282-0.

    Article  Google Scholar 

  • Krishnamurthy, V., & Ajayamohan, R. S. (2010). Composite structure of monsoon low pressure systems and its relation to Indian rainfall. Journal of Climate,23, 4285–4305.

    Article  Google Scholar 

  • Krishnamurthy, V., & Shukla, J. (2008). Seasonal persistence and propagation of intraseasonal patterns over the Indian monsoon region. Climate Dynamics, 30(4), 353–369.

    Article  Google Scholar 

  • Krishnan, R., Sabin, T. P., Ayantika, D. C., Kitoh, A., Sugi, M., Murakami, H., et al. (2013). Will the South Asian monsoon overturning circulation stabilize any further? Climate Dynamics,40, 187–211. https://doi.org/10.1007/s00382-012-1317-0.

    Article  Google Scholar 

  • Kumar, V., & Jain, S. K. (2010). Trends in seasonal and annual rainfall and rainy days in Kashmir Valley in the last century. Quaternary International,212, 64–69. https://doi.org/10.1038/nclimate1327.

    Article  Google Scholar 

  • Kumar, V., Jain, S. K., & Singh, Y. (2010). Analysis of long-term rainfall trends in India. Hydrological Sciences Journal-Journal des Sciences Hydrologiques,55, 484–496.

    Article  Google Scholar 

  • Kumar, K. K., Kamala, K., Rajagopalan, B., Hoerling, M. P., Eischeid, J. K., Patwardhan, S. K., et al. (2011a). The once and future pulse of Indian monsoonal climate. Climate Dynamics,36, 2159–2170. https://doi.org/10.1007/s00382-010-0974-0.

    Article  Google Scholar 

  • Kumar, K. R., Pant, G. B., Parthasarathy, B., & Sontakke, N. A. (1992). Spatial and subseasonal patterns of the long-term trends of Indian summer monsoon rainfall. International Journal of Climatology,12, 257–268. https://doi.org/10.1002/joc.3370120303.

    Article  Google Scholar 

  • Kumar, K. K., Patwardhan, S. K., Kulkarni, A., Kamala, K., Rao, K. K., & Jones, R. (2011b). Simulated projections for summer monsoon climate over India by a high-resolution regional climate model (PRECIS). Current Science,101, 312–326.

    Google Scholar 

  • Lal, M., Nozawa, T., Emori, S., Harasawa, H., Takahashi, K., Kimoto, M., et al. (2001). Future climate change: Implications for Indian summer monsoon and its variability. Current Science,81, 1196–1207.

    Google Scholar 

  • Li, X., Ting, M., Li, C., & Henderson, N. (2015). Mechanisms of Asian summer monsoon changes in response to anthropogenic forcing in CMIP5 models. Journal of Climate,28, 4107–4125. https://doi.org/10.1175/JCLI-D-14-00559.1.

    Article  Google Scholar 

  • Mann, H. B. (1945). Nonparametric tests against trend. Econometrica,13, 245–259. https://doi.org/10.2307/1907187.

    Article  Google Scholar 

  • Maurya, R. K. S., & Singh, G. P. (2015). Simulation of present-day precipitation over India using a regional climate model. Meteorology and Atmospheric Physics,128, 211–228. https://doi.org/10.1007/s00703-015-0409-x.

    Article  Google Scholar 

  • May, W. (2002). Simulated changes of the Indian summer monsoon under enhanced greenhouse gas conditions in a global time-slice experiment. Geophysical Research Letter,29, 22-1. https://doi.org/10.1029/2001GL013808.

    Article  Google Scholar 

  • Meehl, G. A., Arblaster, J. M., & Tebaldi, C. (2005). Understanding future patterns of increased precipitation intensity in climate model simulations. Geophysical Research Letters,32, L18719. https://doi.org/10.1029/2005GL023680.

    Article  Google Scholar 

  • Meehl, G. A., & Washington, W. M. (1993). South Asian summer monsoon variability in a model with doubled atmospheric carbon dioxide concentration. Science,260, 1101–1104.

    Article  Google Scholar 

  • Menon, A., Levermann, A., & Schewe, J. (2013a). Enhanced future variability during India’s rainy season. Geophysical Research Letters,40, 3242–3247. https://doi.org/10.1002/grl.50583.

    Article  Google Scholar 

  • Menon, A., Levermann, A., Schewe, J., Lehmann, J., & Frieler, K. (2013b). Consistent increase in Indian monsoon rainfall and its variability across CMIP-5 models. Earth System Dynamics,4, 287–300. https://doi.org/10.5194/esd-4-287-2013.

    Article  Google Scholar 

  • Mooley, D.A. & Shukla, J. (1987). Characteristics of the westward moving summer monsoon low pressure systems over the Indian region and their relationship with the monsoon rainfall. Center for Ocean-Land-Atmosphere Studies, George Mason Univ, Fairfax, VA, p 47.

  • Pal, J. S., Giorgi, F., Bi, X., Elguindi, N., Solmon, F., Gao, X., et al. (2007). Regional climate modeling for the developing world: The ICTP RegCM3 and RegCNET. Bulletin of the American Meteorological Society,88, 1395–1410. https://doi.org/10.1175/BAMS-88-9-1395.

    Article  Google Scholar 

  • Pal, J. S., Small, E. E., & Eltahir, E. A. B. (2000). Simulation of regional scale water and energy budgets: Influence of a new moist physics scheme within RegCM. Journal of Geophysical Research,105, 579-529.

    Article  Google Scholar 

  • Pattnayak, K. C., Panda, S. K., & Dash, S. K. (2013). Comparative study of regional rainfall characteristics simulated by RegCM3 and recorded by IMD. Global planetary change,106, 111–122. https://doi.org/10.1016/j.gloplacha.2013.03.006.

    Article  Google Scholar 

  • Pendergrass, A. G., Knutti, R., Lehner, F., Deser, C., & Sanderson, B. M. (2017). Precipitation variability increases in a warmer climate. Scientific reports,7, 17966. https://doi.org/10.1038/s41598-017-17966-y.

    Article  Google Scholar 

  • Preethi, B., Mujumdar, M., Kripalani, R. H., Amita, P., & Krishnan, R. (2017a). Recents trends and teleconnections among South and East Asian summer monsoon in a warming environment. Climate Dynamics,48, 2489–2505. https://doi.org/10.1007/s00382-016-3218-0.

    Article  Google Scholar 

  • Preethi, B., Mujumdar, M., Prabhu, A., & Kripalani, R. H. (2017b). Variability and tele-connections of South and East Asia summer monsoons in present and future projections of CMIP5 Climate models. The Asia-Pacific Journal of Atmospheric Sciences,53, 305–325. https://doi.org/10.1007/s13143-017-0034-3.

    Article  Google Scholar 

  • Rai, P. K., Singh, G. P., & Dash, S. K. (2019). Projected changes in extreme precipitation events over various subdivisions of India using RegCM4. Climate Dynamics. https://doi.org/10.1007/s00382-019-04997-6.

    Article  Google Scholar 

  • Rajeevan, M., Bhatek, J., & Jaswal, A. K. (2008). Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data. Geophysical Research Letters,35, L18707. https://doi.org/10.1029/2008GL035143.

    Article  Google Scholar 

  • Rajeevan, M., Bhatek, J., Kalek, J. D., & Lal, B. (2006). High resolution daily gridded rainfall data for the Indian region: Analysis of break and active monsoon spells. Current Science,93, 296–306.

    Google Scholar 

  • Ramesh, K. V., & Goswami, P. (2014). Assessing reliability of regional climate projections: the case of Indian monsoon. Scientific reports,4, 4071. https://doi.org/10.1038/srep04071.

    Article  Google Scholar 

  • Revadekar, J. V., Patwardhan, S. K., & Rupa Kumar, K. (2011). Characteristic features of precipitation extremes over India in the warming scenarios. Advances in Meteorology, 2011(11), 138425. https://doi.org/10.1155/2011/138425.

    Article  Google Scholar 

  • Roxy, M. K., Ghosh, S., Pathak, A., Athulyak, R., Mujumdar, M., Murtugudde, R., et al. (2017). A threefold rise in widespread extreme rain events over central India. Nature Communication,8, 1–11. https://doi.org/10.1038/s41467-017-00744-9.

    Article  Google Scholar 

  • Rupakumar, K., Sahai, A. K., Krishnakumar, K., Patwardhan, S. K., Mishra, P. K., Revadekar, J. V., et al. (2006). High-resolution climate change scenarios for India for the 21st century. Current Science,90(3), 334–345.

    Google Scholar 

  • Sabade, S. S., Kulkarni, A., & Kripalani, R. H. (2011). Projected changes in South Asian summer monsoon by multi-model global warming experiments. Theoretical and Applied Climatology,103, 543–565. https://doi.org/10.1007/s00704-010-0296-5.

    Article  Google Scholar 

  • Saha, A., Ghosh, S., Sahana, A. S., & Rao, E. P. (2014). Failure of CMIP5 climate models in simulating post-1950 decreasing trend of Indian monsoon. Geophysical Research Letters,41, 7323–7330. https://doi.org/10.1002/2014GL061573.

    Article  Google Scholar 

  • Sahai, A. K., Grimm, A. M., Satyan, V., & Pant, G. B. (2003). Long-lead prediction of Indian summer monsoon rainfall from global SST evolution. Climate Dynamics,20, 855–863. https://doi.org/10.1007/s00382-003-0306-8.

    Article  Google Scholar 

  • Sandeep, S., & Ajaya Mohan, R. S. (2015). Poleward shift in Indian summer monsoon low level Jetstream under global warming. Climate Dynamics,45, 337–351. https://doi.org/10.1007/s00382-014-2261-y.

    Article  Google Scholar 

  • Sandeep, S., Ajayamohan, R. S., Boos, W. R., Sabin, T. P., & Praveen, V. (2018). Decline and poleward shift in Indian summer monsoon synoptic activity in a warming climate. Proceedings of the National Academy of Sciences,115, 2681–2686.

    Article  Google Scholar 

  • Schleussner, C., Pfleiderer, P., & Fischer, E. (2017). In the observational record half a degree matters. Nature Climate Change, 7, 460–462. https://doi.org/10.1038/nclimate3320.

    Article  Google Scholar 

  • Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s Tau. Journal of the American Statistical Association,63, 1379–1389. https://doi.org/10.1080/01621459.1968.10480934.

    Article  Google Scholar 

  • Sharmila, S., Joseph, S., Sahai, A. K., Abhilash, S., & Chattopadhyay, R. (2015). Future projection of Indian summer monsoon variability under climate change scenario: An assessment from CMIP5 climate models. Global Planetary Change,124, 62–78.

    Article  Google Scholar 

  • Shukla, J. (1977). Barotropic-baroclinic instability of mean zonal wind during summer monsoon. Pure Applied Geophysics,115, 1449–1461.

    Article  Google Scholar 

  • Sikka, D. R. (1977). Some aspects of the life history, structure and movement of monsoon depressions. Pure Applied Geophysics,115, 1501–1529.

    Article  Google Scholar 

  • Silverman, B. W. (1986). Density estimation for statistics and data analysis, Monographs on statistics and applied probability. London: Chapman and Hall.

    Google Scholar 

  • Singh, G. P., & Oh, J. H. (2007). Impact of Indian Ocean sea-surface temperature anomaly on Indian summer monsoon precipitation using a regional climate model. International Journal of Climatology,27, 1455–1465.

    Article  Google Scholar 

  • Singh, D., Tsiang, M., Rajaratnam, B., & Diffenbaugh, N. S. (2014). Observed changes in extreme wet and dry spells during the south Asian summer monsoon season. Nature Climate Change,4, 456–461. https://doi.org/10.1038/nclimate2208.

    Article  Google Scholar 

  • Sooraj, K. P., Terray, P., & Mujumdar, M. (2015). Global warming and the weakening of the Asian summer monsoon circulation: Assessments from the CMIP5 models. Climate Dynamics,45, 233–252. https://doi.org/10.1007/s00382-014-2257-7.

    Article  Google Scholar 

  • Srivastava, A. K., Singh, G. P., & Singh, O. P. (2016). Variability and trends in extreme rainfall over India. Mausam,67, 745–766.

    Google Scholar 

  • Stowasser, M., Annamalai, H., & Hafner, J. (2009). Response of the South Asian summer monsoon to global warming: mean and synoptic systems. Journal of Climate,22, 1014–1036. https://doi.org/10.1175/2008JCLI2218.1.

    Article  Google Scholar 

  • Subash, N., & Sikka, A. K. (2014). Trend analysis of rainfall and temperature and its relationship over India. Theoretical and Applied Climatology,117, 449–462. https://doi.org/10.1007/s00704-013-1015-9.

    Article  Google Scholar 

  • Tanaka, H., Ishizaki, N., & Nohara, D. (2005). Intercomparison of the intensities and trends of Hadley, Walker and monsoon circulations in the global warming projections. SOLA,1, 77–80. https://doi.org/10.2151/sola.2005-021.

    Article  Google Scholar 

  • Taylor, K. E. (2001). Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research,106, 7183–7192. https://doi.org/10.1029/2000JD900719.

    Article  Google Scholar 

  • Trenberth, K.E. & Shea, D.J. (1997). Atmospheric circulation changes and links to changes in rainfall and drought. In Conference Preprints, AMS Thirteenth Conference on Hydrology, 2–7 February, 1997, Long Beach, CA, pp. J14–J17.

  • Turner, A. G., & Annamalai, H. (2012). Climate change and the South Asian summer monsoon. Nature Climate Change,2, 587–595. https://doi.org/10.1038/NCLIMATE1495.

    Article  Google Scholar 

  • Ueda, H., Iwai, A., Kuwako, K., & Hori, M. E. (2006). Impact of anthropogenic forcing on the Asian summer monsoon as simulated by eight GCMs. Geophysical Research Letters,33, L06703. https://doi.org/10.1029/2005GL025336.

    Article  Google Scholar 

  • Woo, S., Singh, G. P., Oh, J. H., & Lee, K. M. (2018). Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution AGCM based on the RCP scenarios. Meteorology and Atmospheric Physics. https://doi.org/10.1007/s00703-018-0612-7.

    Article  Google Scholar 

  • Yatagai, A., Kamiguchi, K., Arakawa, O., Hamada, A., Yasutomi, N., & Kitoh, A. (2012). Aphrodite constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bulletin of the American Meteorological Society,93, 1401–1415. https://doi.org/10.1175/BAMS-D-11-00122.1.

    Article  Google Scholar 

  • Zeng, X., Zhao, M., & Dickinson, R. E. (1998). Intercomparison of bulk aerodynamic algorithms for the computation of sea surface fluxes using TOGA COARE and TAO data. Journal of Climate,11, 2628–2644.

    Article  Google Scholar 

  • Zhang, X., Alexander, L., Hegerl, G. C., Jones, P., Tank, A. K., Peterson, T. C., et al. (2011). Indices for monitoring changes in extremes based on daily temperature and precipitation data. Wiley Interdisciplinary Review Climate Change,2, 851–870. https://doi.org/10.1002/wcc.147.

    Article  Google Scholar 

  • Zhou, W., Tang, J., Wang, X., Wang, S., Niu, X., & Wang, Y. (2016). Evaluation of regional climate simulations over the CORDEX-EA-II domain using the COSMO-CLM model. Asia-Pacific Journal of Atmospheric Sciences, 52(2), 107–127.

    Article  Google Scholar 

  • Zou, L., Zhou, T., & Peng, D. (2016). Dynamical downscaling of historical climate over CORDEX East Asia domain: A comparison of regional ocean-atmosphere coupled model to stand-alone RCM simulations. Journal of Geophysical Research: Atmospheres, 121(4), 1442–1458.

    Google Scholar 

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Acknowledgments

The authors acknowledge the International Centre for Theoretical Physics (ICTP) for use of their RgCM4 model and forcing online data of CIMIP5 (http://clima-dods.ictp.it/Data/). The authors are grateful to the India Meteorological Department (IMD) for daily gridded precipitation data. The authors would also like to thank the Research Institute for Humanity and Nature(RIHN) and the Meteorological Research Institute of Japan Metrological Agency (MRI/JMA) for providing APHRODITE data online (http://www.chikyu.ac.jp/precip/scope/index.html). We are also very grateful to the reviewers for their constructive comments.

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  1. Department of Geophysics, Institute of Science, Banaras Hindu University, Varanasi, 221005, India

    P. K. Rai & G. P. Singh

  2. Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India

    S. K. Dash

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  1. P. K. Rai
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Correspondence to G. P. Singh.

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Rai, P.K., Singh, G.P. & Dash, S.K. Projected Change and Variability Assessment of Indian Summer Monsoon Precipitation in South Asia CORDEX Domain Under High-Emission Pathway. Pure Appl. Geophys. 177, 3475–3499 (2020). https://doi.org/10.1007/s00024-019-02373-3

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