Abstract
Based on the recently released NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset and the gridded observational daily dataset CN05.1, this study evaluates the performance of 26 CMIP6 models in simulating extreme high temperature (EHT) indices in southwestern China and estimates future changes in the EHT indices under the Shared Socioeconomic Pathways (SSPs) SSP1-2.6, SSP2-4.5, and SSP5-8.5 using 11 optimal CMIP6 models. Five EHT indices are employed: annual maximum value of daily maximum temperature (TXX), high temperature days (T35), warm days (TX90P), heat wave frequency (HWF), and heat wave days (HWD). The main results are as follows. (1) NEX-GDDP-CMIP6 is highly capable of simulating the spatial patterns of TXX and T35 in southwestern China but it presents a weaker ability to simulate the spatial patterns of TX90P, HWF, and HWD. (2) The simulated time series of T35, TX90P, HWF, and HWD in southwestern China exhibit consistent upward trends with the observations. The linear trends of increase in TX90P and HWD are much greater than those of increase in TXX, T35, and HWF. (3) The estimated increases in TXX and T35 in southwestern China are significantly greater in Chongqing and the adjacent areas of Sichuan than in the other regions. Spatial distributions of the increases in TX90P, HWF, and HWD generally show higher values in the west and lower values in the east. (4) In the three different scenarios, the projected future TXX, T35, TX90P, and HWD in southwestern China all display a continuous increase with time and radiative forcing levels, whereas HWF initially increases but then decreases under the SSP5-8.5 scenario. By the end of the 21st century, under the SSP5-8.5 scenario, TXX and T35 are projected to increase by 6.0°C and 45.0 days, respectively. The duration of individual heat waves is also expected to increase.
This is a preview of subscription content, log in via an institution to check access.
References
Bao, Y., and X. Y. Wen, 2017: Projection of China’s near- and long-term climate in a new high-resolution daily downscaled dataset NEX-GDDP. J. Meteor. Res., 31, 236–249, doi: https://doi.org/10.1007/s13351-017-6106-6.
Chen, H. P., and J. Q. Sun, 2015: Assessing model performance of climate extremes in China: an intercomparison between CMIP5 and CMIP3. Climatic Change, 129, 197–211, doi: https://doi.org/10.1007/s10584-014-1319-5.
Chen, H.-P., J.-Q. Sun, and H.-X. Li, 2017: Future changes in precipitation extremes over China using the NEX-GDDP high-resolution daily downscaled data-set. Atmos. Oceanic Sci. Lett., 10, 403–410, doi: https://doi.org/10.1080/16742834.2017.1367625.
Chen, H. P., J. Q. Sun, W. Q. Lin, et al., 2020: Comparison of CMIP6 and CMIP5 models in simulating climate extremes. Sci. Bull., 65, 1415–1418, doi: https://doi.org/10.1016/j.scib.2020.05.015.
Chen, Q. X., T. B. Zhao, L. J. Hua, et al., 2023: Future drought changes in China projected by the CMIP6 models: Contributions from key factors. J. Meteor. Res., 37, 454–168, doi: https://doi.org/10.1007/s13351-023-2169-8.
Chen, S., T. Ye, W. H. Liu, et al., 2021: Evaluation and bias correction of the historical and future near-surface climate forcing in NEX-GDDP and CMIP5 over the Qinghai-Xizang Plateau. Plateau Meteor., 40, 257–271, doi: https://doi.org/10.7522/j.issn.1000-0534.2020.00019. (in Chinese)
Chen, Z. M., T. J. Zhou, X. L. Chen, et al., 2022: Observationally constrained projection of Afro-Asian monsoon precipitation. Nat. Commun., 13, 2552, doi: https://doi.org/10.1038/s41467-022-30106-z.
China Meteorological Administration Climate Change Center, 2022: Blue Book on Climate Change in China 2022. Science Press, Beijing, 109 pp. (in Chinese)
Deng, K. Q., S. Yang, M. F. Ting, et al., 2019: Dominant modes of China summer heat waves driven by global sea surface temperature and atmospheric internal variability. J. Climate, 32, 3761–3775, doi: https://doi.org/10.1175/JCLI-D-18-0256.1.
Deng, K. Q., X. W. Jiang, C. D. Hu, et al., 2020: More frequent summer heat waves in southwestern China linked to the recent declining of Arctic sea ice. Environ. Res. Lett., 15, 074011, doi: https://doi.org/10.1088/1748-9326/ab8335.
Di Luca, A., A. J. Pitman, and R. de Elía, 2020: Decomposing temperature extremes errors in CMIP5 and CMIP6 models. Geophys. Res. Lett., 47, e2020GL088031, doi: https://doi.org/10.1029/2020GL088031.
Eyring, V., S. Bony, G. A. Meehl, et al., 2016: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev., 9, 1937–1958, doi: https://doi.org/10.5194/gmd-9-1937-2016.
Eyring, V., P. M. Cox, G. M. Flato, et al., 2019: Taking climate model evaluation to the next level. Nat. Climate Change, 9, 102–110, doi: https://doi.org/10.1038/s41558-018-0355-y.
Fan, X. W., C. Y. Miao, Q. Y. Duan, et al., 2020: The performance of CMIP6 versus CMIP5 in simulating temperature extremes over the global land surface. J. Geophys. Res. Atmos., 125, e2020JD033031, doi: https://doi.org/10.1029/2020JD033031.
Freychet, N., S. F. B. Tett, G. C. Hegerl, et al., 2018: Central-eastern China persistent heat waves: Evaluation of the AMIP models. J. Climate, 31, 3609–3624, doi: https://doi.org/10.1175/JCLI-D-17-0480.1.
Gao, Q., Z. H. Jiang, and Z. X. Li, 2017: Simulation and evaluation of multi-model dynamical downscaling of temperature extreme indices over the Middle and East China. Acta Meteor. Sinica, 75, 917–933, doi: https://doi.org/10.11676/qxxb2017.067. (in Chinese)
Gao, X. J., Y. Shi, D. F. Zhang, et al., 2012: Climate change in China in the 21st century as simulated by a high resolution regional climate model. Chinese Sci. Bull., 57, 1188–1195, doi: https://doi.org/10.1007/s11434-011-4935-8.
Guan, X. D., J. P. Huang, R. X. Guo, et al., 2015: The role of dynamically induced variability in the recent warming trend slowdown over the Northern Hemisphere. Sci. Rep., 5, 12669, doi: https://doi.org/10.1038/srep12669.
Guo, C. H., X. F. Zhu, S. Z. Zhang, et al., 2022: Hazard changes assessment of future high temperature in China based on CMIP6. J. Geo-Inf. Sci., 24, 1391–1405, doi: https://doi.org/10.12082/dqxxkx.2022.210491. (in Chinese)
Guo, D. L., and H. J. Wang, 2016: Comparison of a very-fine-resolution GCM with RCM dynamical downscaling in simulating climate in China. Adv. Atmos. Sci., 33, 559–570, doi: https://doi.org/10.1007/s00376-015-5147-y.
Guo, X. J., J. B. Huang, Y. Luo, et al., 2017: Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models. Theor. Appl. Climatol., 128, 507522, doi: https://doi.org/10.1007/s00704-015-1718-1.
Hall, A., P. Cox, C. Huntingford, et al., 2019: Progressing emergent constraints on future climate change. Nat. Climate Change, 9, 269–278, doi: https://doi.org/10.1038/s41558-019-0436-6.
Hawkins, E., and R. Sutton, 2009: The potential to narrow uncertainty in regional climate predictions. Bull. Amer. Meteor. Soc., 90, 1095–1108, doi: https://doi.org/10.1175/2009BAMS2607.1.
Hu, L. S., G. Huang, and X. Qu, 2017: Spatial and temporal features of summer extreme temperature over China during 1960–2013. Theor. Appl. Climatol., 128, 821–833, doi: https://doi.org/10.1007/s00704-016-1741-x.
Hu, T., and Y. Sun, 2022: Anthropogenic influence on extreme temperatures in China based on CMIP6 models. Int. J. Climatol., 42, 2981–2995, doi: https://doi.org/10.1002/joc.7402.
Huang, X. M., R. R. Shi, S. J. Liu, et al., 2020: Spatial-temporal characteristics and causes of summer heat waves in Southwest China. Plateau Mountain Meteor. Res., 40, 59–65. (in Chinese)
IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Masson-Delmotte, V., P. Zhai, A. Pirani, et al., Eds., Cambridge University Press, Cambridge, UK and New York, NY, USA, 2391 pp., doi: https://doi.org/10.1017/9781009157896.
Jiang, W. H., and H. P. Chen, 2021: Assessment and projection of changes in temperature extremes over the mid-high latitudes of Asia based on CMTP6 models. Trans. Atmos. Sci., 44, 592–603, doi: https://doi.org/10.13878/j.cnki.dqkxxb.20210203001. (in Chinese)
Kim, Y.-H., S.-K. Min, X. B. Zhang, et al., 2020: Evaluation of the CMIP6 multi-model ensemble for climate extreme indices. Wea. Climate Extremes, 29, 100269, doi: https://doi.org/10.1016/j.wace.2020.100269.
Kim, Y.-H., J.-B. Ahn, M.-S. Suh, et al., 2023: Future changes in extreme heatwaves in terms of intensity and duration over the CORDEX-East Asia Phase Two domain using multi-GCM and multi-RCM chains. Environ. Res. Lett., 18, 034007, doi: https://doi.org/10.1088/1748-9326/acb727.
Kong, D. D., X. H. Gu, J. F. Li, et al., 2020: Contributions of global warming and urbanization to the intensification of human-perceived heatwaves over China. J. Geophys. Res. Atmos., 125, e2019JD032175, doi: https://doi.org/10.1029/2019JD032175.
Lan, T., L. W. Huo, J. Wang, et al., 2021: Extreme drought event and its causes in Southwest China in summer 2011. Trans. Atmos. Sci., 44, 927–937, doi: https://doi.org/10.13878/j.cnki.dqkxxb.20190801007. (in Chinese)
Li, C., F. Zwiers, X. B. Zhang, et al., 2021: Changes in annual extremes of daily temperature and precipitation in CMIP6 models. J. Climate, 34, 3441–3460, doi: https://doi.org/10.1175/JCLI-D-19-1013.1.
Li, J. J., A. H. Wang, D. L. Guo, et al., 2019: Evaluation of extreme temperature indices over China in the NEX-GDDP simulated by high-resolution statistical downscaling models. Acta Meteor. Sinica, 77, 579–593, doi: https://doi.org/10.1167/qxxb2019.032. (in Chinese)
Li, N., Z. N. Xiao, and L. Zhao, 2021: A recent increase in long-lived heatwaves in China under the joint influence of South Asia and western North Pacific subtropical highs. J. Climate, 34, 7167–7179, doi: https://doi.org/10.1175/JCLI-D-21-0014.1.
Li, X. H., Z. F. Chen, L. Wang, et al., 2022: Future projections of extreme temperature events in Southwest China using nine models in CMIP6. Front. Earth Sci., 10, 942781, doi: https://doi.org/10.3389/feart.2022.942781.
Li, Y. H., H. M. Xu, and D. Liu, 2011: Features of the extremely severe drought in the east of Southwest China and anomalies of atmospheric circulation in summer 2006. Acta Meteor. Sinica, 25, 176–187, doi: https://doi.org/10.1007/s13351-011-0025-8.
Li, Y. Q., and Q. Zhang, 2014: Contemporaneous relationships between summer cloudiness and precipitation over Southwest China. J. Nat. Resour., 29, 441–453, doi: https://doi.org/10.11849/zrzyxb.2014.03.008. (in Chinese)
Liu, B., H. P. Chen, and W. Hua, 2023: Future changes in precipitation extremes over Southwest China based on RegCM4 model simulations. Trans. Atmos. Sci., 46, 180–192, doi: https://doi.org/10.13878/j.cnki.dqkxxb.20220927005. (in Chinese)
Liu, X. C., Q. H. Tang, X. J. Zhang, et al., 2018: Projected changes in extreme high temperature and heat stress in China. J. Meteor. Res., 32, 351–366, doi: https://doi.org/10.1007/s13351-018-7120-z.
Luo, N., Y. Guo, Z. B. Gao, et al., 2020: Assessment of CMIP6 and CMIP5 model performance for extreme temperature in China. Atmos. Oceanic Sci. Lett., 13, 589–597, doi: https://doi.org/10.1080/16742834.2020.1808430.
Ma, J. R., X. D. Guan, R. X. Guo, et al., 2017: Mechanism of nonappearance of hiatus in Tibetan Plateau. Sci. Rep., 7, 4421, doi: https://doi.org/10.1038/s41598-017-04615-7.
Meehl, G. A., and C. Tebaldi, 2004: More intense, more frequent, and longer lasting heat waves in the 21st century. Science, 305, 994–997, doi: https://doi.org/10.1126/science.1098704.
Navarro-Racines, C., J. Tarapues, P. Thornton, et al., 2020: Highresolution and bias-corrected CMIP5 projections for climate change impact assessments. Sci. Data, 1, 7, doi: https://doi.org/10.1038/s41597-019-0343-8.
New, M., M. Hulme, and P. Jones, 2000: Representing twentieth-century space-time climate variability. Part II: Development of 1901–96 monthly grids of terrestrial surface climate. J. Climate, 13, 2217–2238, doi: https://doi.org/10.1175/1520-0442(2000)013<2217:RTCSTC>2.0.CO;2.
O’Neill, B. C., C. Tebaldi, D. P. van Vuuren, et al., 2016: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev., 9, 3461–3482, doi: https://doi.org/10.5194/gmd-9-3461-2016.
Park, T., H. Hashimoto, W. L. Wang, et al., 2023: What does global land climate look like at 2°C warming? Earth’s Future, 11, e2022EF003330, doi: https://doi.org/10.1029/2022EF003330.
Riahi, K., D. P. van Vuuren, E. Kriegler, et al., 2017: The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global Environ. Change, 42, 153–168, doi: https://doi.org/10.1016/j.gloenvcha.2016.05.009.
Seneviratne, S. I., and M. Hauser, 2020: Regional climate sensitivity of climate extremes in CMIP6 versus CMIP5 multimodel ensembles. Earth’s Future, 8, e2019EF001474, doi: https://doi.org/10.1029/2019EF001474.
Shi, J., L. L. Cui, Y. Ma, et al., 2018: Trends in temperature extremes and their association with circulation patterns in China during 1961–2015. Atmos. Res., 212, 259–272, doi: https://doi.org/10.1016/j.atmosres.2018.05.024.
Sillmann, J., V. V. Kharin, F. W. Zwiers, et al., 2014: Evaluating model-simulated variability in temperature extremes using modified percentile indices. Int. J. Climatol., 34, 3304–3311, doi: https://doi.org/10.1002/joc.3899.
Smith, T. T., B. F. Zaitchik, and J. M. Gohlke, 2013: Heat waves in the United States: definitions, patterns and trends. Climatic Change, 118, 811–825, doi: https://doi.org/10.1007/s10584-012-0659-2.
Sun, X. R., F. Ge, Q. L. Chen, et al., 2023: How striking is the intergenerational difference in exposure to compound heatwaves over Southeast Asia? Earth’s Future, 11, e2022EF003179, doi: https://doi.org/10.1029/2022EF003179.
Sun, Z. X., Q. Zhang, R. Sun, et al., 2022: Characteristics of the extreme high temperature and drought and their main impacts in southwestern China of 2022. J. Arid Meteor., 40, 764–770, doi: https://doi.org/10.11755/j.issn.1006-7639(2022)-05-0764. (in Chinese)
Tang, T., R. H. Jin, X. Y. Peng, et al., 2014: Analysis on extremely high temperature over southern China in summer 2013. Meteor. Mon., 40, 1207–1215. (in Chinese)
Taylor, K. E., 2001: Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. Atmos., 106, 7183–7192, doi: https://doi.org/10.1029/2000JD900719.
Thrasher, B., E. P. Maurer, C. McKellar, et al., 2012: Technical Note: Bias correcting climate model simulated daily temperature extremes with quantile mapping. Hydrol. Earth Syst. Sci., 16, 3309–3314, doi: https://doi.org/10.5194/hess-16-3309-2012.
Thrasher, B., W. L. Wang, A. Michaelis, et al., 2022: NASA Global Daily Downscaled Projections, CMIP6. Sci. Data, 9, 262, doi: https://doi.org/10.1038/s41597-022-01393-4.
Wang, D., and A. H. Wang, 2017: Applicability assessment of GP-CC and CRU precipitation products in China during 1901 to 2013. Climatic Environ. Res., 22, 446–462, doi: https://doi.org/10.3878/j.issn.1006-9585.2016.16122. (in Chinese)
Wang, Q. Z., K. Liu, and M. Wang, 2022: Evaluation of extreme precipitation indices performance based on NEX-GDDP downscaling data over China. Climate Change Res., 18, 31–43, doi: https://doi.org/10.12006/j.issn.1673-1719.2020.253. (in Chinese)
Wang, Y., H. X. Li, H. J. Wang, et al., 2021: Evaluation of CMIP6 model simulations of extreme precipitation in China and comparison with CMIP5. Acta Meteor. Sinica, 79, 369–386, doi: https://doi.org/10.11676/qxxb2021.031. (in Chinese)
Wang, Y. J., F. M. Ren, and F. Yan, 2013: Study on temporal and spatial variations of regional continual high temperature event in China. Sci. Geogr. Sinica, 33, 314–321. (in Chinese)
Wei, L. X., X. G. Xin, Q. L. Li, et al., 2023: Simulation and projection of climate extremes in China by multiple Coupled Model Intercomparison Project Phase 6 models. Int. J. Climatol., 43, 219–239, doi: https://doi.org/10.1002/joc.7751.
Wu, F., D. L. Jiao, X. L. Yang, et al., 2023: Evaluation of NEX-GDDP-CMIP6 in simulation performance and drought capture utility over China—based on DISO. Hydrol. Res., 54, 703–721, doi: https://doi.org/10.2166/nh.2023.140.
Wu, J., and X. J. Gao, 2013: A gridded daily observation dataset over China region and comparison with the other datasets. Chinese J. Geophys., 56, 1102–1111, doi: https://doi.org/10.6038/cjg20130406. (in Chinese)
Wu, J., X. J. Gao, F. Giorgi, et al., 2017: Changes of effective temperature and cold/hot days in late decades over China based on a high resolution gridded observation dataset. Int. J. Climatol., 37, 788–800, doi: https://doi.org/10.1002/joc.5038.
Wu, Y., C. Y. Miao, Q. Y. Duan, et al., 2020: Evaluation and projection of daily maximum and minimum temperatures over China using the high-resolution NEX-GDDP dataset. Climate Dyn., 55, 2615–2629, doi: https://doi.org/10.1007/s00382-020-05404-1.
Xie, W. Q., S. S. Wang, and X. D. Yan, 2022: Evaluation on CMIP6 global climate model simulation of the annual mean daily maximum and minimum air temperature in China. Climatic Environ. Res., 27, 63–78, doi: https://doi.org/10.3878/j.issn.1006-9585.2021.21027. (in Chinese)
Xu, L. L., T. T. Zhang, W. Yu, et al., 2023: Changes in concurrent precipitation and temperature extremes over the Asian monsoon region: observation and projection. Environ. Res. Lett., 18, 044021, doi: https://doi.org/10.1088/1748-9326/acbfd0.
Xu, Y., X. J. Gao, Y. Shen, et al., 2009: A daily temperature dataset over China and its application in validating a RCM simulation. Adv. Atmos. Sci., 26, 763–772, doi: https://doi.org/10.1007/s00376-009-9029-z.
Xu, Z. F., Y. Han, C.-Y. Tam, et al., 2021: Bias-corrected CMIP6 global dataset for dynamical downscaling of the historical and future climate (1979–2100). Sci. Data, 8, 293, doi: https://doi.org/10.1038/s41597-021-01079-3.
Xue, Y. T., Q. L. Chen, J. Y. Zhang, et al., 2020: Trends in extreme high temperature at different altitudes of Southwest China during 1961–2014. Atmos. Oceanic Sci. Lett., 13, 417–425, doi: https://doi.org/10.1080/16742834.2020.1799689.
Yao, Y., Y. Luo, and J.-B. Huang, 2012: Evaluation and projection of temperature extremes over China based on CMIP5 model. Adv. Climate Change Res., 3, 179–185, doi: https://doi.org/10.3724/SP.J.1248.2012.00179.
Yu, S., Z. W. Yan, N. Freychet, et al., 2020: Trends in summer heatwaves in central Asia from 1917 to 2016: Association with large-scale atmospheric circulation patterns. Int. J. Climatol., 40, 115–127, doi: https://doi.org/10.1002/joc.6197.
Yuan, Y. F., Z. Liao, B. Q. Zhou, et al., 2023: Unprecedented hot extremes observed in city clusters in China during summer 2022. J. Meteor. Res., 37, 141–148, doi: https://doi.org/10.1007/s13351-023-2184-9.
Zhang, G. W., G. Zeng, X. Y. Yang, et al., 2021: Future changes in extreme high temperature over China at 1.5°C-5°C global warming based on CMIP6 simulations. Adv. Atmos. Sci., 38, 253–267, doi: https://doi.org/10.1007/s00376-020-0182-8.
Zhang, L. X., X. L. Chen, and X. G. Xin, 2019: Short commentary on CMIP6 Scenario Model Intercomparison Project (ScenarioMIP). Climate Change Res., 15, 519–525, doi: https://doi.org/10.12006/j.issn.1673-1719.2019.082. (in Chinese)
Zhang, S. B., and J. Chen, 2021: Uncertainty in projection of climate extremes: A comparison of CMIP5 and CMIP6. J. Meteor. Res., 35, 646–662, doi: https://doi.org/10.1007/s13351-021-1012-3.
Zhang, T. Y., B. Y. Cheng, Y. H. Li, et al., 2010: Variability of extreme high temperature and response to regional warming in the Three Gorges Reservoir during 1961–2008. Meteor. Mon., 36, 86–93. (in Chinese)
Zhang, X. B., L. Alexander, G. C. Hegerl, et al., 2011: Indices for monitoring changes in extremes based on daily temperature and precipitation data. WIREs Climate Change, 2, 851–870, doi: https://doi.org/10.1002/wcc.147.
Zhou, B. T., and J. Qian, 2021: Changes of weather and climate extremes in the IPCC AR6. Climate Change Res., 17, 713–718. (in Chinese)
Zhou, B. T., Q. Z. H. Wen, Y. Xu, et al., 2014: Projected changes in temperature and precipitation extremes in China by the CMIP5 multimodel ensembles. J. Climate, 27, 6591–6611, doi: https://doi.org/10.1175/JCLI-D-13-00761.1.
Zhou, B. T., Y. Xu, J. Wu, et al., 2016: Changes in temperature and precipitation extreme indices over China: analysis of a high-resolution grid dataset. Int. J. Climatol., 36, 1051–1066, doi: https://doi.org/10.1002/joc.4400.
Zhou, L., M. C. Lan, R. H. Cai, et al., 2018: Projection and uncertainties of extreme precipitation over the Yangtze River valley in the early 21st century. Acta Meteor. Sinica, 76, 47–61, doi: https://doi.org/10.11676/qxxb2017.084. (in Chinese)
Zhou, T. J., L. W. Zou, and X. L. Chen, 2019: Commentary on the Coupled Model Intercomparison Project Phase 6 (CMIP6). Climate Change Res., 15, 44–456, Doi: https://doi.org/10.12006/j.issn.1673-1719.2019.193. (in Chinese)
Zhu, H. H., Z. H. Jiang, J. Li, et al., 2020: Does CMIP6 inspire more confidence in simulating climate extremes over China? Adv. Atmos. Sci., 37, 1119–1132, doi: https://doi.org/10.1007/s00376-020-9289-1.
Zou, X. K., and H. Gao, 2007: Analysis of severe drought and heat wave over the Sichuan basin in the summer of 2006. Adv. Climate Change Res., 3, 149–153, doi: https://doi.org/10.3969/j.issn.1673-1719.2007.03.005. (in Chinese)
Acknowledgments
The authors are grateful to the editors and anonymous reviewers for their constructive comments, which have significantly improved the quality of this manuscript.
Author information
Authors and Affiliations
Corresponding author
Additional information
Supported by the China Meteorological Administration Innovation and Development Project (CXFZ2022J031 and CXFZ2021J018), National Natural Science Foundation of China (41875111 and 40975058), and Natural Science Foundation of Chongqing, China (CSTB2022NSCQ-MSX0558 and CSTB2022NSCQ-MSX0890).
Rights and permissions
About this article
Cite this article
Zhang, F., Wei, L., Li, Y. et al. Evaluation and Projection of Extreme High Temperature Indices in Southwestern China Using NEX-GDDP-CMIP6. J Meteorol Res 38, 88–107 (2024). https://doi.org/10.1007/s13351-024-3059-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13351-024-3059-4