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Climate Change Research ›› 2022, Vol. 18 ›› Issue (3): 305-318.doi: 10.12006/j.issn.1673-1719.2021.165
• Changes in Climate System • Previous Articles Next Articles
HAN Zhen-Yu(), XU Ying, WU Jia, SHI Ying
Received:
2021-08-13
Revised:
2021-11-01
Online:
2022-05-30
Published:
2022-03-29
HAN Zhen-Yu, XU Ying, WU Jia, SHI Ying. Evaluation on the simulated runoff in China and future change projection based on multiple regional climate models[J]. Climate Change Research, 2022, 18(3): 305-318.
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URL: http://www.climatechange.cn/EN/10.12006/j.issn.1673-1719.2021.165
Fig. 1 Annual runoff averaged over 1986-1995 in different observational data (a-e) and ensemble mean (f) of simulation results, and the SCOR (g), RMSE (h), and Taylor score (i) among different data
Fig. 2 Climatic mean of monthly contributions to annual runoff over 9 basins and the TCOR and S scores among different datasets.(Red markers indicate maximum monthly runoff, blue shadings indicate the uncertainty ranges)
Fig. 4 Linear trends (a) in annual runoff in 2021-2098, and the changes in the end of the 21st century (b). (Hatched areas in (a) indicate that the linear trends are significant, and those in (b) indicate that 80% or more of ensemble members agree on the sign of change)
Fig. 6 Simulated climatic mean of monthly contributions on runoff averaged over each basin during historical reference period (1986-2005) and the end of 21st century (2079-2098)
[1] | Wang G Q, Zhang J Y, Jin J L, et al. Assessing water resources in China using PRECIS projections and a VIC model[J]. Hydrology & Earth System Sciences, 2012, 16 (1): 231-240 |
[2] |
Leng G, Tang Q, Huang M, et al. Projected changes in mean and interannual variability of surface water over continental China[J]. Science China Earth Sciences, 2015, 58 (5): 739-754
doi: 10.1007/s11430-014-4987-0 URL |
[3] |
Li J, Chen Y D, Zhang L, et al. Future changes in floods and water availability across China: linkage with changing climate and uncertainties[J]. Journal of Hydrometeorology, 2016, 17 (4): 1295-1314
doi: 10.1175/JHM-D-15-0074.1 URL |
[4] |
Zhai R, Tao F, Xu Z. Spatial-temporal changes in runoff and terrestrial ecosystem water retention under 1.5 and 2℃ warming scenarios across China[J]. Earth System Dynamics, 2018, 9 (2): 717-738
doi: 10.5194/esd-9-717-2018 URL |
[5] |
Zou J, Xie Z H, Qin P H, et al. Changes of terrestrial water storage in river basins of China projected by RegCM4[J]. Atmospheric and Oceanic Science Letters, 2013, 6 (3): 154-160
doi: 10.1080/16742834.2013.11447073 URL |
[6] | Lee J W, Ham S, Hong S Y, et al. Future changes in surface runoff over Korea projected by a regional climate model under A1B scenario[J]. Advances in Meteorology, 2014, 753790: 1-8 |
[7] |
Du E, Di Vittorio A, Collins W D. Evaluation of hydrologic components of community land model 4 and bias identification[J]. International Journal of Applied Earth Observation and Geoinformation, 2016, 48: 5-16
doi: 10.1016/j.jag.2015.03.013 URL |
[8] |
Yang H, Zhou F, Piao S, et al. Regional patterns of future runoff changes from Earth system models constrained by observation[J]. Geophysical Research Letters, 2017, 44 (11): 5540-5549
doi: 10.1002/2017GL073454 URL |
[9] |
Di Sante F, Coppola E, Giorgi F. Projections of river floods in Europe using EURO-CORDEX, CMIP5 and CMIP6 simulations[J]. International Journal of Climatology, 2021, 41 (5): 3203-3221
doi: 10.1002/joc.7014 URL |
[10] |
Dai A. Hydroclimatic trends during 1950-2018 over global land[J]. Climate Dynamics, 2021, 56 (11): 4027-4049
doi: 10.1007/s00382-021-05684-1 URL |
[11] |
Gao X, Giorgi F. Use of the RegCM system over East Asia: review and perspectives[J]. Engineering, 2017, 3 (5): 766-772
doi: 10.1016/J.ENG.2017.05.019 URL |
[12] | 吴佳, 高学杰. 一套格点化的中国区域逐日观测资料及与其它资料的对比[J]. 地球物理学报, 2013, 56 (4): 1102-1111. |
Wu J, Gao X J. A gridded daily observation dataset over China region and comparison with the other datasets[J]. Chinese Journal of Geophysics, 2013, 56 (4): 1102-1111 (in Chinese) | |
[13] |
Schellekens J, Dutra E, Martínez-De La Torre A, et al. A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset[J]. Earth System Science Data, 2017, 9 (2): 389-413
doi: 10.5194/essd-9-389-2017 URL |
[14] |
Warszawski L, Frieler K, Huber V, et al. The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): project framework[J]. Proceedings of The National Academy of Sciences, 2014, 111 (9): 3228-3232
doi: 10.1073/pnas.1312330110 URL |
[15] | Fekete B M, Vörösmarty C J, Grabs W. High-resolution fields of global runoff combining observed river discharge and simulated water balances[J]. Global Biogeochem Cycles, 2002, 16 (3): 15-1-15-10 |
[16] | Fekete B, Vorosmarty C, Hall F, et al. ISLSCP II UNH/GRDC composite monthly runoff[DB/OL]. 2011 [2021-08-13]. https://doi.org/10.3334/ORNLDAAC/994 |
[17] |
Ghiggi G, Humphrey V, Seneviratne S I, et al. GRUN: an observation-based global gridded runoff dataset from 1902 to 2014 [J]. Earth System Science Data, 2019, 11 (4): 1655-1674
doi: 10.5194/essd-11-1655-2019 URL |
[18] |
Gudmundsson L, Seneviratne S I. Observation-based gridded runoff estimates for Europe (E-RUN version 1.1)[J]. Earth System Science Data, 2016, 8 (2): 279-295
doi: 10.5194/essd-8-279-2016 URL |
[19] |
Abatzoglou J T, Dobrowski S Z, Parks S A, et al. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015[J]. Scientific Data, 2018, 5 (1): 1-12
doi: 10.1038/s41597-018-0002-5 URL |
[20] |
Beck H E, De Roo A, Van Dijk A I. Global maps of streamflow characteristics based on observations from several thousand catchments[J]. Journal of Hydrometeorology, 2015, 16 (4): 1478-1501
doi: 10.1175/JHM-D-14-0155.1 URL |
[21] |
Murray S, Foster P, Prentice I. Evaluation of global continental hydrology as simulated by the Land-surface Processes and eXchanges Dynamic Global Vegetation Model[J]. Hydrology and Earth System Sciences, 2011, 15 (1): 91-105
doi: 10.5194/hess-15-91-2011 URL |
[22] |
Davie J, Falloon P, Kahana R, et al. Comparing projections of future changes in runoff from hydrological and biome models in ISI-MIP[J]. Earth System Dynamics, 2013, 4 (2): 359-374
doi: 10.5194/esd-4-359-2013 URL |
[23] |
Wang D, Wang G, Parr D T, et al. Incorporating remote sensing: based ET estimates into the Community Land Model version 4.5[J]. Hydrology and Earth System Sciences, 2017, 21 (7): 3557-3577
doi: 10.5194/hess-21-3557-2017 URL |
[24] |
Umair M, Kim D, Choi M. Impacts of land use/land cover on runoff and energy budgets in an East Asia ecosystem from remotely sensed data in a community land model[J]. Science of The Total Environment, 2019, 684: 641-656
doi: 10.1016/j.scitotenv.2019.05.244 URL |
[25] |
Yan J, Jia S, Lv A, et al. Water resources assessment of China’s transboundary river basins using a machine learning approach[J]. Water Resources Research, 2019, 55 (1): 632-655
doi: 10.1029/2018WR023044 URL |
[26] |
Miao Y, Wang A. Evaluation of routed-runoff from land surface models and reanalysis using observed streamflow in Chinese river basins[J]. Journal of Meteorological Research, 2020, 34 (1): 73-87
doi: 10.1007/s13351-020-9120-z URL |
[27] |
Qin Y, Abatzoglou J T, Siebert S, et al. Agricultural risks from changing snowmelt[J]. Nature Climate Change, 2020, 10 (5): 459-465
doi: 10.1038/s41558-020-0746-8 URL |
[28] |
Giorgi F, Coppola E, Solmon F, et al. RegCM4: model description and preliminary tests over multiple CORDEX domains[J]. Climate Research, 2012, 52: 7-29
doi: 10.3354/cr01018 URL |
[29] |
Gao X J, Wu J, Shi Y, et al. Future changes in thermal comfort conditions over China based on multi-RegCM4 simulations[J]. Atmospheric and Oceanic Science Letters, 2018, 11 (4): 291-299
doi: 10.1080/16742834.2018.1471578 URL |
[30] | 韩振宇, 高学杰, 石英, 等. 中国高精度土地覆盖数据在RegCM4/CLM模式中的引入及其对区域气候模拟影响的分析[J]. 冰川冻土, 2015, 37 (4): 857-866. |
Han Z Y, Gao X J, Shi Y, et al. Development of Chinese high resolution land cover data for the RegCM4/CLM and its impact on regional climate simulation[J]. Journal of Glaciology and Geocryology, 2015, 37 (4): 857-866 (in Chinese) | |
[31] |
Gao X, Shi Y, Giorgi F. Comparison of convective parameterizations in RegCM4 experiments over China with CLM as the land surface model[J]. Atmospheric and Oceanic Science Letters, 2016, 9 (4): 246-254
doi: 10.1080/16742834.2016.1172938 URL |
[32] |
Gao X, Shi Y, Han Z, et al. Performance of RegCM4 over major river basins in China[J]. Advances in Atmospheric Sciences, 2017, 34 (4): 441-455
doi: 10.1007/s00376-016-6179-7 URL |
[33] | IPCC. Climate change 2013: the physical science basis[M]. Cambridge: Cambridge University Press, 2013 |
[34] |
Shi Y, Wang G, Gao X. Role of resolution in regional climate change projections over China[J]. Climate Dynamics, 2018, 51 (5): 2375-2396
doi: 10.1007/s00382-017-4018-x URL |
[35] | Han Z, Shi Y, Wu J, et al. Combined dynamical and statistical downscaling for high-resolution projections of multiple climate variables in the Beijing-Tianjin-Hebei region of China[J]. Journal of Applied Meteorological Science, 2019, 58 (11): 2387-2403 |
[36] | 韩振宇, 高学杰, 徐影. 多区域模式集合的东亚陆地区域的平均和极端降水未来预估[J]. 地球物理学报, 2021, 64 (6): 1869-1884. |
Han Z Y, Gao X J, Xu Y. Mean and extreme precipitation projection over land area of East Asia based on multiple regional climate models[J]. Chinese Journal of Geophysics, 2021, 64 (6): 1869-1884 (in Chinese) | |
[37] |
Wang Y, Han Z, Gao R. Changes of extreme high temperature and heavy precipitation in the Guangdong-Hong Kong-Macao Greater Bay Area[J]. Geomatics, Natural Hazards and Risk, 2021, 12 (1): 1101-1126
doi: 10.1080/19475705.2021.1912834 URL |
[38] | Oleson K, Niu G Y, Yang Z L, et al. Improvements to the Community Land Model and their impact on the hydrological cycle[J]. Journal of Geophysical Research: Biogeosciences, 2008, 113, G01021 |
[39] |
Perkins S, Pitman A, Holbrook N, et al. Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions[J]. Journal of Climate, 2007, 20 (17): 4356-4376
doi: 10.1175/JCLI4253.1 URL |
[40] |
Taylor K E. Summarizing multiple aspects of model performance in a single diagram[J]. Journal of Geophysical Research: Atmospheres, 2001, 106 (D7): 7183-7192
doi: 10.1029/2000JD900719 URL |
[41] |
Peng D, Zhou T, Zhang L, et al. Observationally constrained projection of the reduced intensification of extreme climate events in Central Asia from 0.5℃ less global warming[J]. Climate Dynamics, 2020, 54 (1): 543-560
doi: 10.1007/s00382-019-05014-6 URL |
[42] | 李博, 周天军. 基于IPCC A1B情景的中国未来气候变化预估: 多模式集合结果及其不确定性[J]. 气候变化研究进展, 2010, 6 (4): 270-276. |
Li B, Zhou T J. Projected climate change over China under SRES A1B scenario: multi-model ensemble and uncertainties[J]. Climate Change Research, 2010, 6 (4): 270-276 (in Chinese) | |
[43] | Tebaldi C, Arblaster J M, Knutti R. Mapping model agreement on future climate projections[J]. Geophysical Research Letters, 2011, 38 (23): L23701 |
[44] |
Li H Y, Leung L R, Getirana A, et al. Evaluating global streamflow simulations by a physically based routing model coupled with the Community Land Model[J]. Journal of Hydrometeorology, 2015, 16 (2): 948-971
doi: 10.1175/JHM-D-14-0079.1 URL |
[45] |
Sheng M, Lei H, Jiao Y, et al. Evaluation of the runoff and river routing schemes in the Community Land Model of the Yellow River basin[J]. Journal of Advances in Modeling Earth Systems, 2017, 9 (8): 2993-3018
doi: 10.1002/2017MS001026 URL |
[46] | 陈仁升, 张世强, 阳勇, 等. 冰冻圈变化对中国西部寒区径流的影响[M]. 北京: 科学出版社, 2019. |
Chen R S, Zhang S Q, Yang Y, et al. The impact of cryospheric change on runoff of cold regions in Western China[M]. Beijing: Science Press, 2019 (in Chinese) | |
[47] |
Xing W, Wang W, Zou S, et al. Projection of future runoff change using climate elasticity method derived from Budyko framework in major basins across China[J]. Global and Planetary Change, 2018, 162: 120-135
doi: 10.1016/j.gloplacha.2018.01.006 URL |
[48] |
Lehner F, Wood A W, Vano J A, et al. The potential to reduce uncertainty in regional runoff projections from climate models[J]. Nature Climate Change, 2019, 9 (12): 926-933
doi: 10.1038/s41558-019-0639-x URL |
[49] |
Zou J, Xie Z, Yu Y, et al. Climatic responses to anthropogenic groundwater exploitation: a case study of the Haihe River basin, Northern China[J]. Climate Dynamics, 2014, 42 (7-8): 2125-2145
doi: 10.1007/s00382-013-1995-2 URL |
[50] |
占车生, 宁理科, 邹靖, 等. 陆面水文-气候耦合模拟研究进展[J]. 地理学报, 2018, 73 (5): 893-905.
doi: 10.11821/dlxb201805009 |
Zhan C S, Ning L K, Zou J, et al. A review on the fully coupled atmosphere-hydrology simulations[J]. Acta Geographica Sinica, 2018, 73 (5): 893-905 (in Chinese) | |
[51] | Xie Z, Liu S, Zeng Y, et al. A high-resolution land model with groundwater lateral flow, water use, and soil freeze-thaw front dynamics and its applications in an endorheic basin[J]. Journal of Geophysical Research: Atmospheres, 2018, 123 (14): 7204-7222 |
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