个人信息

张贺

邮件：zhanghe@mail.iap.ac.cn

电话：86-10-82995286

通信：北京市朝阳区北辰西路81号院中国科学院大气物理研究所

成员分类：科研人员

个人简历

男，1981年生，正高级工程师，博士生导师，中国科学院大气物理研究所国际气候与环境科学中心副主任。2003年毕业于北京大学物理学院，获理学学士学位。2009年毕业于中国科学院大气物理研究所，获理学博士学位。2009年至今在中国科学院大气物理研究所从事科研工作，期间多次赴美国纽约州立大学石溪(Stony Brook)分校做访问学者。现任“十二五”国家重大科技基础设施“地球系统数值模拟装置”地球系统模式运行部负责人。主要从事地球系统模式研发、数值模拟及其预测应用等方面的研究。主持并持续自主研发了大气环流模式IAP AGCM的多个版本。作为技术负责人，研发了具有自主知识产权的地球系统模式CAS-ESM2.0，参加了第六次国际耦合模式比较计划，相关成果荣获2023年度中国十大气象科技进展（排名第二）。获得2020年度“第九届清华大学-浪潮集团计算地球科学青年人才奖”。2022年入选中国科学院“技术支撑人才”。荣获2023年度中国十大气象科技进展（排名第二）。

主要研究方向

地球系统模式的研制及数值模拟，短期气候预测

主要科研项目

1. 地球系统与全球变化国家重点研发计划“共享开放、自主可控地球系统模式CAS-ESM 研发与应用”课题“高分辨率地球系统模式CAS-ESM3.0研制及气候模拟（2024YFF0809001）”，2024.12-2029.11，课题负责人

2.国家自然科学基金面上项目“一个适用于气候模拟的深对流参数化方案的设计及评估”（ 42275173），2023.1-2026.12. 项目负责人

3.国家重点研发国际合作项目“基于人工智能和地球系统模式的金砖国家极端气候事件的模拟与评估”（2022YFE0195900）, 2023.4-2026.3. 项目骨干

4.第二次青藏高原综合科学考察研究专题“气候变化与西风-季风协同作用”之子专题“地球系统模式对青藏高原关键区气候变化的模拟”（2019QZKK010210），2019.11-2024.10. 子专题负责人

5.国家自然科学基金重大项目“高分辨率气候系统模式对亚洲中高纬极端气候的模拟研究”( 41991282)，2020.1-2024.12.项目骨干

6.国家全球变化与应对重点研发计划项目“地球系统模式公共软件平台研发”( 2017YFA0604500)，2017.7-2022.6.项目骨干

7.国家自然科学基金重点项目“地球系统模式若干基本问题与参数化方法研究”( 41630530)，2017.1-2021.12.项目骨干

8.国家高性能计算重点研发计划“地球系统模式的改进、应用开发和高性能计算”(2016YFB0200800)，2016.7-2020.12.项目骨干

9.国家自然科学基金重点项目“面向气候和湍流模拟的百万量级异构众核可扩展并行算法与优化方法”( 61432018)，项目骨干

10.国家自然科学基金青年基金项目“大气环流模式中积云对流参数化集合方案的研究”(41005054)，2011.1-2013.12.项目负责人

11.中国科学院战略性先导科技专项“气候模式模拟和预估中的不确定性问题”(XDA05110101)，2011.1-2015.12.子课题负责人

12.973计划项目“高分辨率气候系统模式的研制与评估”(2010CB951901)，2010.7-2014.12.专题负责人

代表性论文论著

1.Zhang, H., J. Ma, Z. Chai, M. Zhang, M. Cao, 2025: Progress and prospects of the Earth System Numerical Simulation Facility (EarthLab). J. Meteor. Res., 39(3), 517–533, https://doi.org/10.1007/s13351-025-4912-9.

2.Cui, M., Ji, D., Moore, J. C., Zhang, H., et al. 2025: CAS-ESM2.0 Dataset for the G1ext Experiment of the Geoengineering Model Intercomparison Project (GeoMIP), Adv. Atmos. Sci., 42, 579-592. doi: 10.1007/s00376-024-4177-8.

3.Dong, X., Guo, R., Jin, J., Zhang, Z., Zhang, H., Chen, S., & Zeng, Q. (2025). The effects of increasing the coupling frequency and considering the sublayer temperature on the simulation by CASESM2. Journal of Geophysical Research: Atmospheres, 130, e2023JD040600. https://doi.org/10.1029/2023JD040600.

4.Kong, X., Wang, A., Xue, Y., Wei, N., Zhang, H., Hu, Q., He, J., Bi, X., and Chen, Y. 2025: Predicting on the Extreme Precipitation in East and Southeast Asia during Summer 2022 from the Antecedent Soil Temperature Anomaly over the Tibetan Plateau. J. Climate, 38, 2109-2128. https://doi.org/10.1175/JCLI-D-24-0500.1.

5.Kong, X., Jin, J., Wang, A., Dong, X., Bi, X., and Zhang, H. 2024: Impacts of Nudged Sea Surface Temperature on Tropical Precipitation, Moisture, and Vertical Velocity in an Earth System Model. J. Climate, 37, 457-473. https://doi.org/10.1175/JCLI-D-23-0355.1.

6.Zhu, J. W., He, J. X., Ji, D. Y., Li, Y. C., Zhang, H., et al. 2024: CAS-ESM2.0 Successfully Reproduces Historical Atmospheric CO2 in a Coupled Carbon Climate Simulation. Adv. Atmos. Sci., 41, 572-580. https://doi.org/10.1007/s00376-023-3172-9.

7.田凤云, 林朝晖, 张贺, 等. 2024. 三江源地区春季流量与积雪的年际变化关系[J]. 气候与环境研究, 29(5): 588−604.

8.Li, F., Wang Y., Jiang, J., Zhang H., Wang, X., and Chi, X. 2023. Heterogeneous acceleration algorithms for shallow cumulus convection scheme over GPU clusters. Future Generation Computer Systems, 146, 166-177. https://doi.org/10.1016/j.future.2023.04.021.

9.Zhang, Y., Li, J., Zhang, H., Li, X., Dong L., Rong, X., Zhao, C., Peng, X., and Wang Y. 2023. History and Status of Atmospheric Dynamical Core Model Development in China. In: Park, S.K. (eds) Numerical Weather Prediction: East Asian Perspectives. Springer Atmospheric Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-40567-9_1.

10.周彬彬, 王有香, 陈红, 林朝晖，张贺，等. 2023. 青藏高原冬春季雪深异常对云南夏季降水的影响及可能机制[J]. 气候与环境研究, 28(6): 676−686.

11.Cao, Hang; Yuan, Liang; Zhang, He; et al., 2023. AGCM-3DLF: Accelerating Atmospheric General Circulation Model via 3-D Parallelization and Leap-Format. IEEE Transactions on Parallel and Distributed Systems, 34(3): 766-780. https://doi.org/10.1109/TPDS.2022.3231013.

12.姚方玲, 秦正坤, 林朝晖, 杨传国，俞越，张贺. 2023. 基于旋转经验正交分解的流域降水气候预测误差订正方法[J]. 气候与环境研究, 28(3): 327−342.

13.Zhu, J., Zeng, X., Gao, X., Zhang, H. 2022. Response of Terrestrial Net Primary Production to Quadrupled CO2 Forcing: A Comparison between the CAS-ESM2 and CMIP6 Models. Biology, 11, 1693. https://doi.org/10.3390/biology11121693.

14.Lin, R., Dong, X., Zhang, H.,Wu, C., Jin, J. 2022. Simulation of the Boreal Winter East Asian Cold Surge by IAP AGCM4.1. Atmosphere, 13, 1176. https://doi.org/10.3390/atmos13081176.

15.Gao, X., Fan, P., Jin, J., He, J., Song, M., Zhang, H., Fei, K., Zhang, M., Zeng, Q. 2022. Evaluation of Sea Ice Simulation of CAS-ESM 2.0 in Historical Experiment. Atmosphere, 13, 1056. https://doi.org/10.3390/atmos13071056.

16.Zhang, W., Xue, F., Jin, J., Dong, X., Zhang, H., Lin, R. 2022. Comparison of East Asian Summer Monsoon Simulation between an Atmospheric Model and a Coupled Model: An Example from CAS-ESM. Atmosphere, 13, 998. https://doi.org/10.3390/atmos13070998.

17.Torsri, K., Lin, Z., Dike, V.N., Zhang, H., Wu, C., Yu, Y. 2022. Simulation of Summer Rainfall in Thailand by IAP-AGCM4.1. Atmosphere, 13, 805. https://doi.org/10.3390/atmos13050805.

18.Li, Fei, Wang, Y*., Wang Z., Ji, X., Jiang, J., Tang, X., and Zhang, H*. 2022. CC‑RRTMG_SW++: Further optimizing a shortwaveradiative transfer scheme on GPU. J. Supercomput. 78, 17378–17402. https://doi.org/10.1007/s11227-022-04566-5.

19.Jin, Jiangbo, Hailong Liu, Xiao Dong, Juanxiong He, Xin Gao, Yi Yu, He Zhang, Minghua Zhang and Qingcun Zeng. 2022. The effects of redistributed heat flux on ocean climate change in FAFMIP heat flux anomaly experiments. Ocean Modelling, 176, 102063. 

https://doi.org/10.1016/j.ocemod.2022.102063.

20.周菲凡, 叶一苇, 段晚锁, 张贺. 2022. 伴随敏感性方法、第一奇异向量方法以及条件非线性最优扰动方法在台风目标观测敏感区识别中的比较研究. 大气科学, 46(3): 677−690. https://doi.org/10.3878/j.issn.1006-9895.2202.22008

21.Gao, X. F., J. W. Zhu*, X. D. Zeng, M. H. Zhang, Y. J. Dai, D. Y. Ji, and H. Zhang, 2022: Changes in global vegetation distribution and carbon fluxes in response to global warming: simulated results from IAP-DGVM in CAS-ESM2. Adv. Atmos. Sci., 39, 1285-1298. 

https://doi.org/10.1007/s00376-021-1138-3.

22.王天一，姜金荣，迟学斌，张贺，何卷雄，郝卉群. 2021. 地球系统模式CAS-ESM2.0性能评估与分析. 计算机系统应用, 30(6), 9-17.

23.Xie, J., Zhang, M., Zeng, Q., Xie, Z., Liu, H., Chai, Z., et al. (2021). Implementation of an orographic drag scheme considering orographic anisotropy in all flow directions in the earth system model CAS-ESM 2.0. Journal of Advances in Modeling Earth Systems, 13, e2021MS002585. https://doi.org/10.1029/2021MS002585

24.田凤云，吴成来，张贺，林朝晖. 2021. 基于CAS-ESM2 的青藏高原蒸散发的模拟与预估. 地球科学进展, 36(8): 797-809. 

https://doi.org/10.11867/j.issn.1001-8166.2021. 084

25.Wu, C., Lin, Z., Liu, X., Ji, D., Zhang, H., Li, C., & Lin, G. (2021). Description of dust emission parameterization in CAS-ESM2 and its simulation of global dust cycle and East Asian dust events. Journal of Advances in Modeling Earth Systems, 13, e2020MS002456. https://doi.org/10.1029/2020MS002456.

26.孔祥慧, 王爱慧, 毕训强, 李星雨，张贺. 2021. CAS-ESM 模式对欧亚大陆逐日降水特征的数值模拟：物理参数化方案和水平分辨率的影响. 大气科学, 45(4): 725−745. https://doi.org/10.3878/j.issn.1006-9895.2010.20171

27.Chai, Z. Y., H. Zhang*, M. Zhang, et al., 2021: China’s EarthLab—Forefront of Earth system simulation research. Adv. Atmos. Sci., 38, 1611-1620. https://doi.org/10.1007/s00376-021-1175-y.

28.Jin J., X. Dong, J. He, Y. Yu, H. Liu*, M. Zhang, Q. Zeng, H. Zhang, X. Gao, G. Zhou, Y. Wang, 2021: Ocean response to climate change heat-flux perturbation in an ocean model and its corresponding coupled model. Adv. Atmos. Sci., 39(1), 55−66. https://doi.org/10.1007/s00376-021-1167-y.

29. Jiangbo Jin, He Zhang, Xiao Dong, et. al., 2021: CAS-ESM2.0 Model Datasets for CMIP6 Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP). Adv. Atmos. Sci., 38. 296-306. https://doi.org/10.1007/s00376-020-0188-2.

30. Dongxiao, Jiangbo Jin, Hailong Liu, He Zhang, et. al., 2020: CAS-ESM2.0 model datasets for the CMIP6 Ocean Model Intercomparison Project Phase 1 (OMIP1). Adv. Atmos. Sci., 38. 307-316. https://doi.org/10.1007/s00376-020-0150-3.

31. Chai, Z. Y., Zhang, M. H., Zeng, Q. C., Zhang, H., Jin, J. B., Xie, J. B., You, T. 2021. A High-top Version of the IAP-AGCM: Preliminary Assessment and Sensitivity. Atmospheric and Oceanic Science Letters, 14. 100025. https://doi.org/10.1016/j.aosl.2020.100025.

32. Chai, Z. Y., Zhang, M. H., Zeng, Q. C., Xie, J. B., You, T., Zhang, H. 2021. Simulation of the QBO in the IAP-AGCM: Analysis of momentum budget. Atmospheric and Oceanic Science Letters, 14. 100021.

https://doi.org/10.1016/j.aosl.2020.100021.

33. Du, J., Zheng F., Zhang H., Zhu J., 2021: A Multivariate Balanced Initial Ensemble Generation Approach for an Atmospheric General Circulation Model. Water, 13. 122. https://doi.org/10.3390/w13020122.

34. Zhang, H., Zhang, M., Jin, J., Fei, K., Ji, D., Wu, C., et al., 2020: Description and climate simulation performance of CAS-ESM version 2. Journal of Advances in Modeling Earth Systems, 12. e2020MS002210.

https://doi.org/10.1029/2020MS002210.

35. Cao, Hang, Liang Yuan, He Zhang*, Baodong Wu, Shigang Li, Pengqi Lu, Yunquan Zhang, Yongjun Xu, and Minghua Zhang. 2020. A Highly Efficient Dynamical Core of Atmospheric General Circulation Model based on Leap-Format. IPDPS 2020. https://doi.org/10.1109/IPDPS47924.2020.00020.

36. 周广庆，张云泉，姜金荣，张贺，吴保东，曹杭等, 2020. 地球系统模式CAS-ESM. 数据与计算发展前沿, 2(1), 38-54. https://doi.org/10.11871/jfdc.issn.2096-742X.2020.01.004.

37. Wang, T., J. Jiang, M. Zhang, H. Zhang, J. He, H. Hao, X. Chi. 2020. Design and Research of a Coupling Interface Generator for Earth System Models (CAS‐CIG). Earth and Space Science, 7(7), e2019EA000965. https://doi.org/10.1029/2019EA000965.

38.周颖，张贺*，张珂玮. 2020. 基于K-均值聚类方法的大气环流模式IAP AGCM4.1对西北太平洋热带气旋的模拟评估. 大气科学，44(5)，1141-1154.

https://doi.org/ 10.3878/j.issn.1006-9895.2002.19252.

39.CHEN Hong, ZHANG He, & ZHAN Yanling, 2020: Potential predictability of Eurasian spring snow water equivalent in IAP AGCM4 hindcasts. Atmos. Oceanic Sci. Lett., 13(2): 121-128. https://doi.org/10.1080/16742834.2020.1712996.

40.Xie, J., Zhang, M., Xie, Z., Liu, H., Chai, Z., He, J. X., & Zhang, H. 2020: An orographic-drag parametrization scheme including orographic anisotropy for all flow directions. Journal of Advances in Modeling Earth Systems, 12(3), e2019MS001921. https://doi.org/10.1029/2019MS001921

41.Wang Y., Y. Zhao, J. Jiang, and H. Zhang, 2020: A Novel GPU-Based Acceleration Algorithm for a Longwave Radiative Transfer Model. Applied Sciences, 10. 649. https://doi.org/10.3390/app10020649.

42.Kong, X., Wang, A., Bi, X., Li, X., & Zhang, H., 2020: Effects of horizontal resolution on hourly precipitation in AGCM simulations. Journal of Hydrometeorology, 21(4), 643-670. https://doi.org/10.1175/jhm-d-19-0148.1.

43.张云泉，袁良，陈一峯，冯晓兵，张贺. 2020. 高性能计算多层次不连续非线性可扩展现象研究. 计算机学报, 43(6), 973-989.

44.Adeniyi, M. O., Z. Lin, and H. Zhang, 2019: Evaluation of the performance of IAP-AGCM4.1 in simulating the climate of West Africa. Theoretical and Applied Climatology, 136. 1419-1434. https://doi.org/10.1007/s00704-018-2571-9.

45.Zhou F., and H. Zhang, 2018: The Impact of Nonlinearity on the Targeted Observations for Tropical Cyclone Prediction. In Advances in Nonlinear Geosciences, Springer, Cham, 675-692. https://doi.org/10.1007/978-3-319-58895-7_32.

46.Xie, X., H. Zhang, X. D. Liu, Y. R. Peng, and Y. G. Liu, 2018: Role of microphysical parameterizations with droplet relative dispersion in IAP AGCM 4.1. Adv. Atmos. Sci., 35. 248-259.

47.Zhou, F., W. Duan, H. Zhang, and M. Yamaguchi, 2018: Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part II: Model Uncertainty. Adv. Atmos. Sci., 35. 1277-1290.

48.Zhu, J., X. Zeng, M. Zhang, Y. Dai, D. Ji, F. Li, Q. Zhang, H. Zhang, and X. Song, 2018: Evaluation of the New Dynamic Global Vegetation Model in CAS-ESM. Adv. Atmos. Sci., 35. 659-670.

49.Xiao, J., S. Li, B. Wu, H. Zhang, et al., 2018: Communication-Avoiding for Dynamical Core of Atmospheric General Circulation Model. Proceedings of the 47th International Conference on Parallel Processing (p. 12). ACM,https://doi.org/10.1145/3225058.3225140.

50.Wang, Y., J. Jiang, J. Zhang, J. He, H. Zhang, X. Chi, and T. Yue, 2018: An efficient parallel algorithm for the coupling of global climate models and regional climate models on a large-scale multi-core cluster. Journal of Supercomputing, 74. 3999-4018. https://doi.org/10.1007/s11227-018-2406-6.

51.李星雨, 毕训强, 张贺. 2018. 全球模式NCAR CESM 和CAS ESM 对亚洲东部夏季气候的模拟性能评估：气候平均态和降水日变化分析. 气候与环境研究, 23 (6): 645−656.

52.Xie, X., H. Zhang, X. Liu, Y. Peng, and Y. Liu, 2017: Sensitivity study of cloud parameterizations with relative dispersion in CAM5.1: impacts on aerosol indirect effects. Atmos. Chem. Phys., 17. 5877-5892. https://doi.org/10.5194/acp-17-5877-2017.

53.Wang, Y., J. Jiang, H. Zhang, et al., 2017: A scalable parallel algorithm for atmospheric general circulation models on a multi-core cluster. Future Generation Computer Systems, 72. 1-10.

54.林朝晖, 王坤, 肖子牛，张贺，詹艳玲. 2017. IAP AGCM4.0 模式对热带大气季节内振荡的模拟评估. 气候与环境研究, 22 (2): 115–133.

55.LIN Zhao-hui, YU Zheng, ZHANG He and WU Cheng-Lai, 2016: Quantifying the attribution of model bias in simulating summer hot days in China with IAP AGCM 4.1. Atmos. Oceanic Sci. Lett., 9(6): 436-442.

56.Zhou, G., H. Zhang, F. Zhang, et al., 2016: Studies on High-Resolution Atmospheric and Oceanic General Circulation Models. In Development and Evaluation of High Resolution Climate System Models, R. Yu, et al., Eds., Springer Singapore, 49-103. doi: 10.1007/978-981-10-0033-1_2.

57.晏正滨, 林朝晖, 张贺. 2015. 大气环流模式IAP AGCM4.0 对东亚高空副热带西风急流的模拟及偏差原因分析. 气候与环境研究, 20 (4): 393–410.

58.Su, T., F. Xue, and H. Zhang, 2014: Simulating the Intraseasonal Variation of the East Asian Summer Monsoon by IAP AGCM4.0. Adv. Atmos. Sci., 31(3), 570-580.

59.YAN Zheng-Bin, LIN Zhao-Hui, ZHANG He, 2014: The Relationship between the East Asian Subtropical Westerly Jet and Summer Precipitation over East Asia as Simulated by the IAP AGCM4.0. Atmos. Oceanic Sci. Lett., 7(6): 487-492.

60.周菲凡, 张贺. 2014. 基于 CNOP 方法的台风目标观测中三种敏感区确定方案的比较研究. 大气科学, 38 (2): 261–272.

61.曹美春，林朝晖，张贺，2014：太阳常数变化对冬季全球辐射强迫及气候影响的数值模拟研究，气象科技进展，4(4): 38-43.

62.Zhang, H., M. Zhang, and Q. Zeng, 2013: Sensitivity of simulated climate to two atmospheric models: Interpretation of differences between dry models and moist models. Mon. Wea. Rev., 141. 1558-1576.

63.Dong, X., F. Xue, H. Zhang, and Q. Zeng, 2012: Evaluation of surface air temperature change over China and the globe during the twentieth century in IAP AGCM4.0. Atmos. Oceanic Sci. Lett., 5. 435-438.

64.张贺，林朝晖，曾庆存，2011. 大气环流模式中动力框架与物理过程的相互响应. 气候与环境研究. 16(1): 15-30.

65.张贺，林朝晖，曾庆存，2009：IAP AGCM-4 动力框架的积分方案及模式检验. 大气科学，33(6): 1267-1285.