과제정보
이 논문은 2022년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(No. 2021R1I1A3060354).
참고문헌
- Alam, M. S., and A. Elshorbagy, 2015: Quantification of the climate change-induced variations in Intensity-Duration-Frequency curves in the Canadian Prairies. J. Hydrol., 527, 990-1005, doi:10.1016/j.jhydrol.2015.05.059.
- Alexander, L. V., and Coauthors, 2006: Global observed changes in daily climate extremes of temperature and precipitation. J. Geophys. Res. Atmos., 111, D05109.
- Alfieri, L., P. Burek, L. Feyen, and G. Forzieri, 2015: Global warming increases the frequency of river floods in Europe. Hydrol. Earth Syst. Sci., 19, 2247-2260, doi:10.5194/hess-19-2247-2015.
- Allan, R. P., and B. J. Soden, 2008: Atmospheric warming and the amplification of precipitation extremes. Science, 321, 1481-1484. https://doi.org/10.1126/science.1160787
- Cheng, L., and A. AghaKouchak, 2014: Nonstationary precipitation intensity-duration-frequency curves for infrastructure design in a changing climate. Sci. Rep., 4, 7093, doi:10.1038/srep07093.
- Christidis, N., G. S. Jones, and P. A. Stott, 2015: Dramatically increasing chance of extremely hot summers since the 2003 European heatwave. Nat. Clim. Change, 5, 46-50, doi:10.1038/nclimate2468.
- Collins, W. J., and Coauthors, 2011: Development and evaluation of an Earth-System model-HadGEM2. Geosci. Model Dev., 4, 1051-1075, doi:10.5194/gmd4-1051-2011.
- Doll, P., T. Trautmann, D. Gerten, H. M. Schmied, S. Ostberg, F. Saaed, and C.-F. Schleussner, 2018: Risks for the global freshwater system at 1.5℃ and 2℃ global warming. Environ. Res. Lett., 13, 044038, doi:10.1088/1748-9326/aab792.
- Donat, M. G., A. L. Lowry, L. V. Alexander, P. A. O'Gorman, and N. Maher, 2016: More extreme precipitation in the world's dry and wet regions. Nat. Clim. Change, 6, 508-513, doi:10.1038/nclimate2941.
- Donner, L. J., and Coauthors, 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. J. Climate, 24, 3484-3519, doi:10.1175/2011JCLI3955.1.
- Duan, W., N. Hanasaki, H. Shiogama, Y. Chen, S. Zou, D. Nover, B. Zhou, and Y. Wang, 2019: Evaluation and future projection of Chinese precipitation extremes using large ensemble high-resolution climate simulations. J. Climate, 32, 2169-2183, doi:10.1175/JCLID-18-0465.1.
- Elshorbagy, A., K. Lindenas, and H. Azinfar, 2018: Risk-based quantification of the impact of climate change on storm water infrastructure. Water Sci., 32, 102-114, doi:10.1016/j.wsj.2017.12.003.
- Faye, B., and Coauthors, 2018: Impacts of 1.5 versus 2.0℃ on cereal yields in the West African Sudan Savanna. Environ. Res. Lett., 13, 034014, doi:10.1088/1748-9326/aaab40.
- Felix, M. L., Y.-K. Kim, M. Choi, J.-C. Kim, X. K. Do, T. H. Nguyen, and K. Jung, 2021: Detailed trend analysis of extreme climate indices in the upper Geum River basin. Water, 13, 3171, doi:10.3390/w13223171.
- Fischer, E. M., and R. Knutti, 2015: Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes. Nat. Clim. Change, 5, 560-564, doi:10.1038/nclimate2617.
- Gent, P. R., and Coauthors, 2011: The community climate system model version 4. J. Climate, 24, 4973-4991, doi:10.1175/2011JCLI4083.1.
- Giorgetta, M. A., and Coauthors, 2013: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. J. Adv. Model. Earth Syst., 5, 572-597, doi:10.1002/jame.20038.
- Guhathakurta, P., O. P. Sreejith, and P. A. Menon, 2011: Impact of climate change on extreme rainfall events and flood risk in India. J. Earth Syst. Sci., 120, 359-373, doi:10.1007/s12040-011-0082-5.
- Haddad, K., and A. Rahman, 2011: Selection of the best fit flood frequency distribution and parameter estimation procedure: a case study for Tasmania in Australia. Stoch. Environ. Res. Risk Assess., 25, 415-428, doi:10.1007/s00477-010-0412-1.
- Hanittinan, P., Y. Tachikawa, and T. Ram-Indra, 2020: Projection of hydroclimate extreme indices over the Indochina region under climate change using a large single-model ensemble. Int. J. Climatol., 40, 2924-2952, doi:10.1002/joc.6374.
- Hardwick Jones, R., S. Westra, and A. Sharma, 2010: Observed relationships between extreme sub-daily precipitation, surface temperature, and relative humidity. Geophys. Res. Lett., 37, L22805, doi:10.1029/2010GL045081.
- Her, Y., S.-H. Yoo, J. Cho, S. Hwang, J. Jeong, and C. Seong, 2019: Uncertainty in hydrological analysis of climate change: multi-parameter vs. multi-GCM ensemble predictions. Sci. Rep., 9, 4974, doi:10.1038/s41598-019-41334-7.
- Herath, S. M., R. Sarukkalige, and V. T. Van Nguyen, 2018: Evaluation of empirical relationships between extreme rainfall and daily maximum temperature in Australia. J. Hydrol., 556, 1171-1181, doi:10.1016/j.jhydrol.2017.01.060.
- Huntington, T. G., 2006: Evidence for intensification of the global water cycle: Review and synthesis. J. Hydrol., 319, 83-95, doi:10.1016/j.jhydrol.2005.07.003.
- Hwang, J., J. Ahn, C. Jeong, and J.-H. Heo, 2018: A study on the variation of design flood due to climate change in the ungauged urban catchment. J. Korea Water Resour. Assoc., 51, 395-404, doi:10.3741/JKWRA.2018.51.5.395 (in Korean with English abstract).
- Ishii, M., and N. Mori, 2020: d4PDF: large-ensemble and high-resolution climate simulations for global warming risk assessment. Prog. Earth Planet. Sci., 7, 58, doi:10.1186/s40645-020-00367-7.
- Jakob, D., and D. Walland, 2016: Variability and long-term change in Australian temperature and precipitation extremes. Weather Clim. Extrem., 14, 36-55, doi:10.1016/j.wace.2016.11.001.
- Jang, D. W., B. S. Kim, and J. H. Kim, 2012: The quantification of disaster impact of extreme rainfall under climate change in Korea. J. Korean Soc. Hazard Mitig., 12, 169-178, doi:10.9798/KOSHAM.2012.12.4.169 (in Korean with English abstract).
- Ji, Z., and S. Kang, 2015: Evaluation of extreme climate events using a regional climate model for China. Int. J. Climatol., 35, 888-902, doi:10.1002/joc.4024.
- Kay, J. E., and Coauthors, 2015: The community earth system model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability. Bull. Amer. Meteor. Soc., 96, 1333-1349, doi:10.1175/BAMS-D13-00255.1.
- Kim, Y.-H., S.-K. Min, X. Zhang, F. Zwiers, L. V. Alexander, M. G. Donat, and Y.-S. Tung, 2016: Attribution of extreme temperature changes during 1951~2010. Climate Dyn., 46, 1769-1782, doi:10.1007/s00382-015-2674-2.
- Kumar, N., V. Poonia, B. B. Gupta, and M. K. Goyal, 2021: A novel framework for risk assessment and resilience of critical infrastructure towards climate change. Technol. Forecast. Soc. Change, 165, 120532, doi:10.1016/j.techfore.2020.120532.
- Kunkel, K. E., and Coauthors, 2013a: Regional Climate Trends and Scenarios for the U.S. National Climate Assessment Part 4. Climate of the US Great Plains. NOAA Tech. Rep. NESDIS 142-4, 91 pp.
- Kunkel, K. E., T. R. Karl, D. R. Easterling, K. Redmond, J. Young, X. Yin, and P. Hennon, 2013b: Probable maximum precipitation and climate change. Geophys. Res. Lett., 40, 1402-1408, doi:10.1002/grl.50334.
- Lavender, S. L., K. J. E. Walsh, L.-P. Caron, M. King, S. Monkiewicz, M. Guishard, Q. Zhang, and B. Hunt, 2018: Estimation of the maximum annual number of North Atlantic tropical cyclones using climate models. Sci. Adv., 4, eaat6509, doi:10.1126/sciadv.aat6509.
- Lee, M.-H., E.-S. Im, and D.-H. Bae, 2019: A comparative assessment of climate change impacts on drought over Korea based on multiple climate projections and multiple drought indices. Climate Dyn., 53, 389-404, doi:10.1007/s00382-018-4588-2.
- Li, S., P. W. Mote, D. E. Rupp, D. Vickers, R. Mera, and M. Allen, 2015: Evaluation of a regional climate modeling effort for the western United States using a superensemble from weather@home. J. Climate, 28, 7470-7488, doi:10.1175/JCLI-D-14-00808.1.
- Min, S.-K., X. Zhang, F. W. Zwiers, and G. C. Hegerl, 2011: Human contribution to more-intense precipitation extremes. Nature, 470, 378-381, doi:10.1038/nature09763.
- Mizuta, R., and Coauthors, 2017: Over 5,000 years of ensemble future climate simulations by 60-km global and 20-km regional atmospheric models. Bull. Amer. Meteorol. Soc., 98, 1383-1398, doi:10.1175/BAMSD-16-0099.1.
- Mori, N., T. Shimura, K. Yoshida, R. Mizuta, Y. Okada, M. Fujita, T. Khujanazarov, and E. Nakakita, 2019: Future changes in extreme storm surges based on mega-ensemble projection using 60-km resolution atmospheric global circulation model. Coast. Eng. J., 61, 295-307, doi:10.1080/21664250.2019.1586290.
- Mote, P. W., M. R. Allen, R. G. Jones, S. Li, R. Mera, D. E. Rupp, A. Salahuddin, and D. Vickers, 2016: Superensemble regional climate modeling for the western United States. Bull. Amer. Meteor. Soc., 97, 203-215, doi:10.1175/BAMS-D-14-00090.1.
- Nissen, K. M., and U. Ulbrich, 2017: Increasing frequencies and changing characteristics of heavy precipitation events threatening infrastructure in Europe under climate change. Nat. Hazards Earth Syst. Sci., 17, 1177-1190, doi:10.5194/nhess-17-1177-2017.
- Noor, M., T. Ismail, E.-S. Chung, S. Shahid, and J. H. Sung, 2018: Uncertainty in rainfall intensity duration frequency curves of peninsular Malaysia under changing climate scenarios. Water, 10, 1750, doi:10.3390/w10121750.
- Pachauri, R. K., and Coauthors, 2014: Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. IPCC, 151 pp.
- Peterson, T. C., and M. J. Manton, 2008: Monitoring changes in climate extremes: a tale of international collaboration. Bull. Amer. Meteor. Soc., 89, 1266-1271. https://doi.org/10.1175/2008BAMS2501.1
- Saddique, N., A. Khaliq, and C. Bernhofer, 2020: Trends in temperature and precipitation extremes in historical (1961~1990) and projected (2061~2090) periods in a data scarce mountain basin, northern Pakistan. Stoch. Environ. Res. Risk Assess., 34, 1441-1455, doi:10.1007/s00477-020-01829-6.
- Sasaki, H., K. Kurihara, I. Takayabu, and T. Uchiyama, 2008: Preliminary experiments of reproducing the present climate using the non-hydrostatic regional climate model. SOLA, 4, 25-28, doi:10.2151/sola.2008-007.
- Seneviratne, S. I., and Coauthors, 2012: Changes in climate extremes and their impacts on the natural physical environment. In C. B. Field et al. Eds., Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, IPCC, Cambridge University Press, 109-230.
- Sharma, A., and M. K. Goyal, 2020: Assessment of the changes in precipitation and temperature in Teesta River basin in Indian Himalayan Region under climate change. Atmos. Res., 231, 104670, doi:10.1016/j.atmosres.2019.104670.
- Sung, J. H., H.-I. Eum, J. Park, and J. Cho, 2018: Assessment of climate change impacts on extreme precipitation events: Applications of CMIP5 climate projections statistically downscaled over South Korea. Adv. Meteorol., 2018, 4720523, doi:10.1155/2018/4720523.
- Tanaka, T., Y. Tachikawa, Y. Ichikawa, and K. Yorozu, 2018: Flood risk curve development with probabilistic rainfall modelling and large ensemble climate simulation data: A case study for the Yodo river basin. Hydrol. Res. Lett., 12, 28-33, doi:10.3178/hrl.12.28.
- Tanaka, T., K. Kiyohara, and Y. Tachikawa, 2020: Comparison of fluvial and pluvial flood risk curves in urban cities derived from a large ensemble climate simulation dataset: A case study in Nagoya, Japan. J. Hydrol., 584, 124706, doi:10.1016/j.jhydrol.2020.124706.
- Tanaka, T., K. Kobayashi, and Y. Tachikawa, 2021: Simultaneous flood risk analysis and its future change among all the 109 class-A river basins in Japan using a large ensemble climate simulation database d4PDF. Environ. Res. Lett., 16, 074059, doi:10.1088/1748-9326/abfb2b.
- Tang, J., X. Niu, S. Wang, H. Gao, X. Wang, and J. Wu, 2016: Statistical downscaling and dynamical downscaling of regional climate in China: Present climate evaluations and future climate projections. J. Geophys. Res., 121, 2110-2129, doi:10.1002/2015JD023977.
- Trenberth, K. E., 2011: Changes in precipitation with climate change. Clim. Res., 47, 123-138, doi:10.3354/cr00953.
- Trenberth, K. E., J. Fasullo, and L. Smith, 2005: Trends and variability in column-integrated atmospheric water vapor. Climate Dyn., 24, 741-758. https://doi.org/10.1007/s00382-005-0017-4
- Utsumi, N., S. Seto, S. Kanae, E. E. Maeda, and T. Oki, 2011: Does higher surface temperature intensify extreme precipitation? Geophys. Res. Lett., 38, L16708, doi:10.1029/2011GL048426.
- Watanabe, S., and Coauthors, 2011: MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev., 4, 845-872, doi:10.5194/gmd-4-845-2011.
- Wazneh, H., M. A. Arain, and P. Coulibaly, 2020: Climate indices to characterize climatic changes across southern Canada. Meteorol. Appl., 27, e1861, doi:10.1002/met.1861.
- Yang, J.-A., S. Kim, N. Mori, and H. Mase, 2018: Assessment of long-term impact of storm surges around the Korean Peninsula based on a large ensemble of climate projections. Coast. Eng., 142, 1-8, doi:10.1016/j.coastaleng.2018.09.008.
- Yin, H., and Y. Sun, 2018: Detection of anthropogenic influence on fixed threshold indices of extreme temperature. J. Climate, 31, 6341-6352, doi:10.1175/JCLID-17-0853.1.
- Yukimoto, S., and Coauthors, 2012: A New Global Climate Model of the Meteorological Research Institute: MRI-CGCM3 -Model Description and Basic Performance-. J. Meteor. Soc. Japan. Ser. II, 90A, 23-64, doi:10.2151/jmsj.2012-A02.
- Zhang, Y., Y. Xu, W. Dong, L. 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.
- Zhao, A. D., D. S. Stevenson, and M. A. Bollasina, 2019: The role of anthropogenic aerosols in future precipitation extremes over the Asian Monsoon Region. Climate Dyn., 52, 6257-6278, doi:10.1007/s00382-018-4514-7.