Abstract
Precipitation over the Tibetan Plateau (TP) is important to local and downstream ecosystems. Based on a weighting method considering model skill and independence, changes in the TP precipitation for near-term (2021–40), mid-term (2041–60) and long-term (2081–2100) under shared socio-economic pathways (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSSP3-7.0, SSP5-8.5) are projected with 27 models from the latest Sixth Phase of the Couple Model Intercomparison Project. The annual mean precipitation is projected to increase by 7.4%–21.6% under five SSPs with a stronger change in the northern TP by the end of the 21st century relative to the present climatology. Changes in the TP precipitation at seasonal scales show a similar moistening trend to that of annual mean precipitation, except for the drying trend in winter precipitation along the southern edges of the TP.
Weighting generally suggests a slightly stronger increase in TP precipitation with reduced model uncertainty compared to equally-weighted projections. The effect of weighting exhibits spatial and seasonal differences. Seasonally, weighting leads to a prevailing enhancement of increase in spring precipitation over the TP. Spatially, the influence of weighting is more remarkable over the northwestern TP regarding the annual, summer and autumn precipitation. Differences between weighted and original MMEs can give us more confidence in a stronger increase in precipitation over the TP, especially for the season of spring and the region of the northwestern TP, which requires additional attention in decision making.
摘要
青藏高原的降水对局地及下游生态具有重要影响. 基于CMIP6最新释出的27个模式, 及综合考虑了模式性能和独立性的加权方法, 研究了5种共享社会经济路径(SSP1-1.9、 SSP1-2.6、 SSP2-4.5、 SSSP3-7.0、 SSP5-8.5)下青藏高原降水的近期(2021-2040年)、 中期(2041-2060年)和长期(2081-2100年)变化. 结果表明, 21世纪末青藏高原的年平均降水相较于当前气候态将增加7.4% — 21.6%, 其中高原北部的变化更为强烈. 除冬季降水在高原南部的减少趋势外, 其他季节的降水呈现和年平均类似的增加趋势. 与等权重的预估结果相比, 加权后的青藏高原降水增加趋势略有增强, 同时模式不确定性减小. 此外, 加权的影响存在空间和季节差异, 季节上, 加权对降水增加的加强效应在春季更明显, 空间上, 高原西北部的降水变化受加权的影响更为显著. 预估结果在加权前后的差异提升了未来青藏高原降水趋湿的可信度, 尤其是春季和高原西北部的降水, 相关结果可为决策者提供参考.
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References
Amos, M., and Coauthors, 2020: Projecting ozone hole recovery using an ensemble of chemistry—climate models weighted by model performance and independence. Atmospheric Chemistry and Physics, 20(16), 9961–9977, https://doi.org/10.5194/acp-20-9961-2020.
Brunner, L., R. Lorenz, M. Zumwald, and R. Knutti, 2019: Quantifying uncertainty in European climate projections using combined performance-independence weighting. Environmental Research Letters, 14(12), 124010, https://doi.org/10.1088/1748-9326/ab492f.
Brunner, L., A. G. Pendergrass, F. Lehner, A. L. Merrifield, R. Lorenz, and R. Knutti, 2020: Reduced global warming from cmip6 projections when weighting models by performance and independence. Earth System Dynamics, 11(4), 995–1012, https://doi.org/10.5194/esd-11-995-2020.
Duan, A. M., R. Z. Sun, and J. H. He, 2017: Impact of surface sensible heating over the Tibetan Plateau on the western Pacific subtropical high: A land—air—sea interaction perspective. Adv. Atmos. Sci., 34(2), 157–168, https://doi.org/10.1007/s00376-016-6008-z.
Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor, 2016: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016.
Feng, L., and T. J. Zhou, 2017: Projection of summer precipitation change over the Qinghai-Tibetan Plateau with a 20 km high-resolution global climate model. Plateau Meteorology, 36(3), 587–595. (in Chinese with English abstract)
Fu, Y. H., X. J. Gao, Y. M. Zhu, and D. Guo, 2021: Climate change projection over the Tibetan Plateau based on a set of RCM simulations. Advances in Climate Change Research, 12, 313–321, https://doi.org/10.1016/j.accre.2021.01.004.
Gao, Y. H., L. H. Xiao, D. L. Chen, J. W. Xu, and H. W. Zhang, 2018: Comparison between past and future extreme precipitations simulated by global and regional climate models over the Tibetan Plateau. International Journal of Climatology, 38(3), 1285–1297, https://doi.org/10.1002/joc.5243.
Gettelman, A., and Coauthors, 2019: The whole atmosphere community climate model version 6 (WACCM6). J. Geophys. Res.: Atmos., 124(23), 12 380–12 403, https://doi.org/10.1029/2019JD030943.
Hao, Z. C., Q. Ju, W. J. Jiang, and C. J. Zhu, 2013: Characteristics and scenarios projection of climate change on the Tibetan Plateau. The Scientific World Journal, 2013, 129793, https://doi.org/10.1155/2013/129793.
Hu, Q., D. B. Jiang, and G. Z. Fan, 2015: Climate change projection on the Tibetan Plateau: Results of CMIP5 models. Chinese Journal of Atmospheric Sciences, 39(2), 260–270, https://doi.org/10.3878/j.issn.1006-9895.1406.13325. (in Chinese with English abstract)
Immerzeel, W. W., and M. F. P. Bierkens, 2012: Asia’s water balance. Nature Geoscience, 5(12), 841–842, https://doi.org/10.1038/ngeo1643.
Immerzeel, W. W., L. P. H. Van Beek, and M. F. P. Bierkens, 2010: Climate change will affect the Asian water towers. Science, 328(5984), 1382–1385, https://doi.org/10.1126/science.1183188.
Immerzeel, W. W., and Coauthors, 2020: Importance and vulnerability of the world’s water towers. Nature, 577(7900), 364–369, https://doi.org/10.1038/s41586-019-1822-y.
Ji, Z. M., and S. C. Kang, 2013: Double-nested dynamical down-scaling experiments over the Tibetan Plateau and their projection of climate change under two RCP scenarios. J. Atmos. Sci., 70(4), 1278–1290, https://doi.org/10.1175/JAS-D-12-0155.1.
Jiang, J., T. J. Zhou, X. L. Chen, and L. X. Zhang, 2020: Future changes in precipitation over Central Asia based on CMIP6 projections. Environmental Research Letters, 15, 054009, https://doi.org/10.1088/1748-9326/ab7d03.
Knutti, R., J. Sedláček, B. M. Sanderson, R. Lorenz, E. M. Fischer, and V. Eyring, 2017: A climate model projection weighting scheme accounting for performance and interdependence. Geophys. Res. Lett., 44(4), 1909–1918, https://doi.org/10.1002/2016GL072012.
Lee, J.-Y., and Coauthors, 2021: Future global climate: Scenario-based projections and near-term information. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, V. Masson-Delmotte et al., Eds., Cambridge University Press.
Li, L. L., J. Li, and R. C. Yu, 2022: Evaluation of CMIP6 High-ResMIP models in simulating precipitation over Central Asia. Advances in Climate Change Research, 13(1), 1–13, https://doi.org/10.1016/j.accre.2021.09.009.
Li, T., Z. H. Jiang, L. L. Zhao, and L. Li, 2021: Multi-model ensemble projection of precipitation changes over China under global warming of 1.5 and 2°C with consideration of model performance and independence. J. Meteor. Res., 35(1), 184–197, https://doi.org/10.1007/s13351-021-0067-5.
Liang, Y. X., N. P. Gillett, and A. H. Monahan, 2020: Climate model projections of 21st century global warming constrained using the observed warming trend. Geophys. Res. Lett., 47(12), e2019GL086757, https://doi.org/10.1029/2019GL086757.
Liu, S. F., A. M. Duan, and G. X. Wu, 2020: Asymmetrical response of the East Asian summer monsoon to the quadrennial oscillation of global sea surface temperature associated with the Tibetan Plateau thermal feedback. J. Geophys. Res.: Atmos., 125(20), e2019JD032129, https://doi.org/10.1029/2019JD032129.
Lorenz, R., N. Herger, J. Sedláček, V. Eyring, E. M. Fischer, and R. Knutti, 2018: Prospects and caveats of weighting climate models for summer maximum temperature projections over North America. J. Geophys. Res.: Atmos., 123(9), 4509–4526, https://doi.org/10.1029/2017JD027992.
Merrifield, A. L., L. Brunner, R. Lorenz, I. Medhaug, and R. Knutti, 2020: An investigation of weighting schemes suitable for incorporating large ensembles into multi-model ensembles. Earth System Dynamics, 11(3), 807–834, https://doi.org/10.5194/esd-11-807-2020.
Müller, W. A., and Coauthors, 2018: A higher-resolution version of the Max Planck Institute Earth System Model (MPI-ESM1.2-HR). Journal of Advances in Modeling Earth Systems, 10(7), 1383–1413, https://doi.org/10.1029/2017MS001217.
O’Neill, B. C., and Coauthors, 2016: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geoscientific Model Development, 9(9), 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016.
Pritchard, H. D., 2019: Asia’s shrinking glaciers protect large populations from drought stress. Nature, 569(7758), 649–654, https://doi.org/10.1038/s41586-019-1240-1.
Riahi, K., and Coauthors, 2017: The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global Environmental Change, 42, 153–168, https://doi.org/10.1016/j.gloenvcha.2016.05.009.
Rong, X. Y., and Coauthors, 2018: The CAMS climate system model and a basic evaluation of its climatology and climate variability simulation. J. Meteor. Res., 32(6), 839–861, https://doi.org/10.1007/s13351-018-8058-x.
Sanderson, B. M., R. Knutti, and P. Caldwell, 2015a: Addressing interdependency in a multimodel ensemble by interpolation of model properties. J. Climate, 28(13), 5150–5170, https://doi.org/10.1175/JCLI-D-14-00361.1.
Sanderson, B. M., R. Knutti, and P. Caldwell, 2015b: A representative democracy to reduce interdependency in a multimodel ensemble. J. Climate, 28(13), 5171–5194, https://doi.org/10.1175/JCLI-D-14-00362.1.
Sanderson, B. M., M. Wehner, and R. Knutti, 2017: Skill and independence weighting for multi-model assessments. Geoscientific Model Development, 10(6), 2379–2395, https://doi.org/10.5194/gmd-10-2379-2017.
Seland, Ø., and Coauthors, 2020: Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations. Geoscientific Model Development, 13(12), 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020.
Senior, C. A., and Coauthors, 2020: U.K. community Earth system modeling for CMIP6. Journal of Advances in Modeling Earth Systems, 12(9), e2019MS002004, https://doi.org/10.1029/2019MS002004.
Su, F. G., X. L. Duan, D. L. Chen, Z. C. Hao, and L. Cuo, 2013: Evaluation of the global climate models in the CMIP5 over the Tibetan Plateau. J. Climate, 26(10), 3187–3208, https://doi.org/10.1175/JCLI-D-12-00321.1.
United Nations Framework Convention on Climate Change (UNFCCC), 2015: Decision 1/CP.21. The Paris Agreement. 32 pp. Available online at http://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf. Accessed on 13 December 2019.
Wang, X. J., G. J. Pang, and M. X. Yang, 2018: Precipitation over the Tibetan Plateau during recent decades: A review based on observations and simulations. International Journal of Climatology, 38(3), 1116–1131, https://doi.org/10.1002/joc.5246.
Xie, Z. L., and B. Wang, 2021: Summer heat sources changes over the Tibetan Plateau in CMIP6 models. Environmental Research Letters, 16(6), 064060, https://doi.org/10.1088/1748-9326/ac0279.
Xu, Y., X. J. Gao, and F. Giorgi, 2010: Upgrades to the reliability ensemble averaging method for producing probabilistic climate-change projections. Climate Research, 41, 61–81, https://doi.org/10.3354/cr00835.
Yang, X. L., B. T. Zhou, Y. Xu, and Z. Y. Han, 2021: CMIP6 evaluation and projection of temperature and precipitation over China. Adv. Atmos. Sci., 38(5), 817–830, https://doi.org/10.1007/s00376-021-0351-4.
Yao, T. D., and Coauthors, 2012: Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings. Nature Climate Change, 2(9), 663–667, https://doi.org/10.1038/nclimate1580.
Yatagai, A., K. Kamiguchi, O. Arakawa, A. Hamada, N. Yasutomi, and A. Kitoh, 2012: APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bull. Amer. Meteor. Soc., 93(9), 1401–1415, https://doi.org/10.1175/BAMS-D-11-00122.1.
Zhang, D. F., and X. J. Gao, 2020: Climate change of the 21st century over China from the ensemble of RegCM4 simulations. Chinese Science Bulletin, 65(23), 2516–2526, https://doi.org/10.1360/TB-2020-0231. (in Chinese with English abstract)
Zhang, H. W., Y. H. Gao, J. W. Xu, Y. Xu, and Y. S. Jiang, 2019: Decomposition of future moisture flux changes over the Tibetan Plateau projected by global and regional climate models. J. Climate, 32(20), 7037–7053, https://doi.org/10.1175/JCLI-D-19-0200.1.
Zhang, R. H., and Coauthors, 2015: An overview of projected climate and environmental changes across the Tibetan Plateau in the 21st century. Chinese Science Bulletin, 60(32), 3036–3047, https://doi.org/10.1360/N972014-01296. (in Chinese with English abstract)
Zhou, T. J., W. X. Zhang, X. L. Chen, L. X. Zhang, L. W. Zou, and W. M. Man, 2020: The near-term, mid-term and long-term projections of temperature and precipitation changes over the Tibetan Plateau and the sources of uncertainties. Journal of the Meteorological Sciences, 40(5), 697–710, https://doi.org/10.3969/2020jms.0076. (in Chinese with English abstract)
Acknowledgements
This work is supported by the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant No. XDA20060102, the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (Grant No 2019QZKK0102), the National Natural Science Foundation of China under Grant No. 41988101 and K. C. WONG Education Foundation. The observational precipitation data APHRODITE can be obtained from http://aphoodtte.tt.hkosak-u.ac.jp/download. The model data from CMIP6 can be found at https://esgf-node.llnl.gov/search/cmip6/. Considerable gratitude is owed to the corresponding working teams.
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• The annual mean precipitation over the TP will increase with a relatively greater change in the north regarding the long-term projection.
• Changes in the TP precipitation at seasonal scales show a similar moistening trend to that of annual mean precipitation, except for winter.
• Weighting suggests a slightly greater increase in TP precipitation and reduced model uncertainty, with spatial and seasonal differences.
• Weighting implies greater increase in TP precipitation than raw projections, especially for spring and the northwestern TP.
This paper is a contribution to the special issue on Third Pole Atmospheric Physics, Chemistry, and Hydrology.
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Zhao, Y., Zhou, T., Zhang, W. et al. Change in Precipitation over the Tibetan Plateau Projected by Weighted CMIP6 Models. Adv. Atmos. Sci. 39, 1133–1150 (2022). https://doi.org/10.1007/s00376-022-1401-2
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DOI: https://doi.org/10.1007/s00376-022-1401-2