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气候系统模式FGOALS-g3模拟的全球季风:版本比较和海气耦合过程影响分析

张星 周天军 张文霞 左萌 张丽霞

张星, 周天军, 张文霞, 等. 2023. 气候系统模式FGOALS-g3模拟的全球季风:版本比较和海气耦合过程影响分析[J]. 大气科学, 47(2): 470−486 doi: 10.3878/j.issn.1006-9895.2112.21099
引用本文: 张星, 周天军, 张文霞, 等. 2023. 气候系统模式FGOALS-g3模拟的全球季风:版本比较和海气耦合过程影响分析[J]. 大气科学, 47(2): 470−486 doi: 10.3878/j.issn.1006-9895.2112.21099
ZHANG Xing, ZHOU Tianjun, ZHANG Wenxia, et al. 2023. Global Monsoon Simulated by FGOALS-g3 Climate System Model: A Comparison with the Previous Version and Influences of Air–Sea Coupling [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(2): 470−486 doi: 10.3878/j.issn.1006-9895.2112.21099
Citation: ZHANG Xing, ZHOU Tianjun, ZHANG Wenxia, et al. 2023. Global Monsoon Simulated by FGOALS-g3 Climate System Model: A Comparison with the Previous Version and Influences of Air–Sea Coupling [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(2): 470−486 doi: 10.3878/j.issn.1006-9895.2112.21099

气候系统模式FGOALS-g3模拟的全球季风:版本比较和海气耦合过程影响分析

doi: 10.3878/j.issn.1006-9895.2112.21099
基金项目: 国家重点研发计划项目2017YFA0604601、2020YFA0608900,中国科学院“国际伙伴计划—国际大科学计划培育专项”项目“全球季风模拟研究国际计划”134111KYSB20160031,国家自然科学基金项目41775091,第二次青藏科考项目(STEP)2019QZKK0102
详细信息
    作者简介:

    张星,女,1996年出生,硕士研究生,主要从事全球季风研究。E-mail: zhangxing@lasg.iap.ac.cn

    通讯作者:

    周天军,E-mail: zhoutj@lasg.iap.ac.cn

  • 中图分类号: P461

Global Monsoon Simulated by FGOALS-g3 Climate System Model: A Comparison with the Previous Version and Influences of Air–Sea Coupling

Funds: National Key Research and Development Program of China (Grants 2017YFA0604601, 2020YFA0608900), International Partnership Program of Chinese Academy of Sciences (Grant 134111KYSB20160031), National Natural Science Foundation of China (NSFC) (Grant 41775091), Second Tibetan Plateau Scientific Expedition and Research (STEP) Program (Grant 2019QZKK0102)
  • 摘要: 本文基于观测和再分析资料,采用水汽收支诊断和合成分析方法,对新一代气候系统模式FGOALS-g3模拟的全球季风进行了系统评估,给出其较之前版本FGOALS-g2的优缺点,并通过与其大气分量模式GAMIL结果的比较,讨论了海气耦合过程的影响。结果表明,FGOALS-g3能合理再现全球季风气候态的基本特征,包括年平均、年循环模态、季风降水强度和季风区范围等,但模式低估陆地季风区年平均降水,高估海洋平均降水,模拟的热带地区春秋非对称模态偏强。研究指出FGOALS-g3模拟的陆地季风区范围偏小,这与模式模拟的夏季水汽垂直平流(尤其是热力项)偏小有关。年际变率上,FGOALS-g3能再现El Niño年全球季风降水偏少的整体特征,其不足之处在于部分季风区的降水异常存在一定偏差,例如其模拟的El Niño年西非季风区降水偏多和西南印度洋的偶极子型降水异常,均与观测分布不一致,且模式中西北太平洋季风区降水较观测偏多。这是由于El Niño年,模式中西非高层无弱辐合中心,且海洋性大陆较观测偏暖,对流中心西移。相较于FGOALS-g2,FGOALS-g3对环流、季风降水的年际变率和季风–ENSO关系的模拟有改善。比较耦合和非耦合模拟结果,耦合模式的偏差大多源自大气模式本身,海气耦合过程部分提高了对亚澳季风区和热带印度洋的降水和环流的模拟,但耦合过程引起的海温偏差增强了气候态上印度半岛的干偏差和热带印度洋的湿偏差。
  • 图  1  1979~2005年年平均的全球降水(填色,单位: mm d−1)和850 hPa风场(矢量,单位: m s−1)的气候态分布:(a)GPCP/ERA5; (b)CMAP/NCEP2;(c)FGOALS-g3;(d)FGOALS-g2;(e)GAMIL3;(f)GAMIL2。红色区域为根据1979~2005年GPCP(Global Precipitation Climatology Project dataset) 降水计算得到的季风区范围(下同)

    Figure  1.  Climatology of the annual mean global precipitation (shaded, units: mm d−1) and 850 hPa winds (vector, units: m s−1) averaged over 1979–2005: (a) GPCP/ERA5; (b) CMAP/NCEP2; (c) FGOALS-g3; (d) FGOALS-g2; (e)GAMIL3; (f) GAMIL2. Red lines denote the global monsoon region calculated from the Global Precipitation Climatology Project dataset (GPCP) precipitation during 1979–2005 (the same below)

    图  2  全球年平均降水(填色,单位:mm d−1)和850 hPa风场(矢量,单位:m s−1)的偏差, (a)–(d)分别为FGOALS-g3、FGOALS-g2、GAMIL3、GAMIL2相对于GPCP/ERA5的偏差,(e)FGOALS-g3相对于GAMIL3的偏差,(f)FGOALS-g2相对于GAMIL2的偏差

    Figure  2.  Biases of the global annual precipitation (shaded, units: mm d−1) and 850 hPa winds (vector, units: m s−1): (a)–(d) are the biases of FGOALS-g3, FGOALS-g2, GAMIL3, and GAMIL2 relative to GPCP/ERA5, respectively; (e) differences between FGOALS-g3 and GAMIL3, (f) same as (e) but for the differences between FGOALS-g2 and GAMIL2

    图  3  全球年平均和夏季(MJJAS,May–September)海温的气候态分布(单位:°C,填色:ERSST,黑线:FGOALS-g3,蓝色:GAMIL3)及其与观测的差值(单位:°C),(a)和(b)为气候态分布,(c)和(d)为FGOALS-g3与观测的差值

    Figure  3.  Climatology of the annual mean and summer (MJJAS,May–September) global sea surface temperature (units: °C, shaded: ERSST, black line: FGOALS-g3, blue line: GAMIL3) and the differences with observation (units: °C): (a) and (b) are the climatology and (c) and (d) are the differences between FGOALS-g3 and observation

    图  4  观测和模式模拟的年循环模态(填色:降水, 单位:mm d−1;矢量:850 hPa风场,单位:m s−1):(a–e)季风模态(monsoon mode);(f–j)春秋非对称模态(spring–fall asymmetric mode)。第一行至第五行分别为GPCP/ERA5、FGOALS-g3、FGOALS-g2、GAMIL3、GAMIL2

    Figure  4.  Annual cycle modes (shaded: precipitation, units: mm d−1; vectors: 850 hPa winds, units: m s−1): (a–e) Monsoon mode; (f–j) spring–fall asymmetric mode. The first to fifth rows correspond to GPCP/ERA5, FGOALS-g3, FGOALS-g2, GAMIL3, and GAMIL2, respectively

    图  5  全球季风降水强度(MPI指数)(填色)和季风区范围(红线区域):(a)GPCP;(b)CMAP;(c)FGOALS-g3;(d)FGOALS-g2;(e)GAMIL3;(f)GAMIL2。右上角为全球范围内(40°S~60°N,0°~360°)的季风降水强度相对于GPCP的PCC和RMSE

    Figure  5.  Global monsoon precipitation intensity (MPI) (shaded) and monsoon region (red lines): (a) GPCP; (b) CMAP; (c) FGOALS-g3; (d) FGOALS-g2; (e) GAMIL3; (f) GAMIL2. The PCC and RMSE of the global precipitation intensity relative to GPCP are displayed in the upper right corner based on the global range (40°S–60°N,0°–360°)

    图  6  气候态平均的夏季(北半球MJJAS, 南半球NDJFM)全球陆地季风区和各个子季风区的定量水汽收支(单位:mm d−1),包括:降水(P)、蒸发(E)、水汽垂直平流项($-\left\langle{\omega \cdot {\partial }_{{p}}q}\right\rangle$)、水汽水平平流项($-\left\langle{\boldsymbol{V}\cdot \nabla q}\right\rangle$)和残差项(res),季风区均采用1979~2005年GPCP降水计算得到的季风区范围(下同),其分别为:(a) 全球陆地季风区、(b)北半球陆地季风区、(c)南半球陆地季风区、(d)南亚陆地季风区(7°~35°N, 65°~95°E)、(e)东亚陆地季风区(20°~40°N,110°~130°E)、(f)北美陆地季风区(0°~32°N,50°~115°W)、(g) 南美陆地季风区(5°~25°S,40°~70°W)、(h)北非陆地季风区(5°~15°N,15°~40°E)、(i)南非陆地季风区(0°~40°S,0°~40°°E)、(j)澳大利亚陆地季风区(0°~30°S,110°~150°E),不同颜色柱状图分别代表:ERA5(红色)、FGOALS-g3(橙色)、FGOALS-g2(绿色)、GAMIL3(深蓝色)、GAMIL2(浅蓝色)

    Figure  6.  Climatology moisture budget of the global land monsoon region and sub-monsoon region in summer (units: m d−1) including the precipitation (P), evaporation (E), vertical moisture advection ($-\left\langle{\omega \cdot {\partial }_{{p}}q}\right\rangle$), moisture horizontal advection ($-\langle {\boldsymbol{V}}\cdot \nabla q\rangle$), and residual term (res). The monsoon region is calculated from the GPCP precipitation during 1979–2005 (the same below). They are the (a) global land monsoon region, (b) northern hemisphere land monsoon region, (c) southern hemisphere land monsoon region, (d) south Asia land monsoon region (7°–°35°N, 65°–°95°E), (e) east Asia land monsoon region (20°–°40°N, 110°–°130°E), (f) north America land monsoon region (0°–°32°N, 50°–°115°W), (g) south America land monsoon region (5°–°25°S, 40°–°70°W), (h) north Africa land monsoon region (5°–°15°N, 15°W°–°40°E), (i) south Africa land monsoon region (0°–°40°S, 0°–°40°E), and (j) Australia land monsoon region (0°–°30°S, 110°–°150°E). Different color histograms represent ERA5 (red), FGOALS-g3 (orange), FGOALS-g2 (green), GAMIL3 (deep blue), and GAMIL2 (light blue)

    图  7  夏季全球陆地季风区和各个子季风区水汽收支偏差(单位:mm d−1),包括:降水偏差(P′)、蒸发偏差(E′)、水汽垂直平流项偏差$\left(-\left\langle{\omega \cdot {\partial }_{{p}}q}\right\rangle{'}\right)$、水汽水平平流项偏差$\left(-\left\langle{\boldsymbol{V}\cdot \nabla q}\right\rangle{'}\right)$、垂直动力偏差$\left( -\left\langle{\omega {'}\cdot {\partial }_{\mathrm{p}}\bar{q}}\right\rangle \right)$和垂直热力偏差$\left( -\left\langle{\bar{\omega }\cdot {\partial }_{\mathrm{p}}q{'}}\right\rangle \right)$,季风区范围同图6,不同颜色柱状图分别代表:FGOALS-g3与ERA5之差(红色)、FGOALS-g2与ERA5之差(橙色)、GAMIL3与ERA5之差(绿色)、GAMIL2与ERA5之差(深蓝色)、FGOALS-g3与GAMIL3之差(浅蓝色)、FGOALS-g2与GAMIL2之差(紫色)

    Figure  7.  Bias of the moisture budget of the global land monsoon region and sub-monsoon region in summer (units: mm d−1), including the precipitation bias (P′), evaporation bias (E′), moisture vertical advection term bias $\left( -\left\langle{\omega \cdot {\partial }_{{p}}q}\right\rangle{'} \right)$, moisture horizontal advection term bias $\left(-\left\langle{\boldsymbol{V}\cdot \nabla q}\right\rangle{'} \right)$, vertical dynamic bias $\left(-\left\langle{\omega {'}\cdot {\partial }_{\mathrm{p}}\bar{q}}\right\rangle \right)$, and vertical thermodynamic bias $\left(-\left\langle{\bar{\omega }\cdot {\partial }_{\mathrm{p}}q{'}}\right\rangle \right)$. The monsoon region is the same as Fig. 5. Different color histograms represent the difference between FGOALS-g3 and ERA5 (red), FGOALS-g2 and ERA5 (orange), GAMIL3 and ERA5 (green), GAMIL2 and ERA5 (deep blue), FGOALS-g3 and GAMIL3 (light blue), and FGOALS-g2 and GAMIL2 (purple)

    图  8  季风年平均(5月至次年4月)的季风降水的年际变化以及季风—ENSO关系:(a–e)季风降水异常EOF分解的第一模态,括号中为解释方差;(f–j)PC1与同期Niño3.4指数的时间序列, 右上角为相关系数。第一行至第五行分别为:GPCP、FGOALS-g3、FGOALS-g2、GAMIL3、GAMIL2

    Figure  8.  Interannual variability of the monsoon precipitation and monsoon-ENSO relationship of the monsoon year (from May to next April): (a–e) First mode of the EOF in the monsoon precipitation anomaly, the explained variance is in the parenthesis; (f–j) time series of PC1 (the first principle component) and the simultaneous Niño3.4 index, the correlation coefficient is in the upper right corner. The first to fifth rows correspond to GPCP, FGOALS-g3, FGOALS-g2, GAMIL3, and GAMIL2, respectively

    图  9  (a–d)合成的ENSO年(即El Niño和La Niña差值)200 hPa速度势(填色,单位:106 m2 s−1)和辐散风(矢量,单位:m s−1)以及(e–h)季风年Niño3.4指数回归的同期海温异常(划线区域表示通过95%显著性检验)。 第一行至第五行分别为:ERA5/ERSST、FGOALS-g3与ERA5/ERSST的差值、FGOALS-g2与ERA5/ERSST的差值、FGOALS-g3与GAMIL3的差值

    Figure  9.  (a–d) Composite velocity potential (shaded, units: 106 m2 s−1) and divergent wind (vector, units: m s−1) at 200 hPa during the ENSO year (difference between El Ni$ \stackrel{~}{\mathrm{n}} $o and La Ni$ \stackrel{~}{\mathrm{n}} $a), and (e–h) the sea surface temperature anomaly regresses on the simultaneous Niño3.4 index of the monsoon year (the slashes indicate the values that are significant at the 95% confidence level). The first to fifth row correspond to ERA5/ERSST, differences between FGOALS-g3 and ERA5/ERSST, differences between FGOALS-g2 and ERA5/ERSST, and differences between FGOALS-g3 and GAMIL3

    表  1  FGOALS-g2模式和FGOALS-g3模式各分量模块的对比

    Table  1.   Comparison of component models of FGOALS-g3 and FGOALS-g2 models

    FGOALS-g2FGOALS-g3
    AGCMGAMIL2~2.8°(128×60) L26GAMIL3~2°(180×80) L26
    OGCMLICOM 2.0 360×196 L30LICOM 3.0 360×218 L30
    陆面CLM3128×60 L10+5CAS-LSM180×80
    海冰CICE4-LASG360×196 L4CICE 4.0360×218 L4+1
    耦合器CPL6CPL7
    参考文献(Li et al., 2013)(Li et al., 2020)
    下载: 导出CSV

    表  2  GAMIL3和GAMIL2的对比

    Table  2.   Comparison of GAMIL3 model and GAMIL2 model

    GAMIL2GAMIL3
    动力框架有限差分有限差分
    水汽方程求解两步保形平流方案(TSPAS)修正的TSPAS
    计算并行度一维剖分二维剖分
    物理过程 层积云对流层低层稳定度(LTS)基于估计反演强度的层积云方案(EIS)
     云量生成Slingo方案新的云量生成方案
     边界层K廓线方案TKE(Turbulent Kinetic Energy)方案
    外强迫未考虑火山强迫考虑火山强迫的CMIP6外强迫
    参考文献(Slingo, 1987; Holtslag and Boville, 1993; Klein and Hartmann, 1993; Yu, 1994; 唐彦丽等, 2019)(Yu, 1994; Guo and Zhou, 2014; Liu et al., 2014; Sun et al., 2016; Nie et al., 2019; 唐彦丽等, 2019; Li et al., 2020)
    下载: 导出CSV

    表  3  基于全球范围(40°S~60°N,0°~360°)计算的模式的年平均降水、环流和年循环模态相对于GPCP/ERA5的均方根误差(RMSE)和空间相关系数(PCC)

    Table  3.   Root mean square error (RMSE) and pattern correlation coefficient (PCC) of the simulated annual mean precipitation, circulation, and annual cycle modes relative to the GPCP/ERA5 based on the global range (40°S–60°N, 0°–360°)

    年平均季风模态春秋非对称模态
    RMSEPCCRMSEPCCRMSEPCC
    降水FGOALS-g31.48 mm d–10.802.18 mm d–10.741.81 mm d–10.61
    FGOALS-g21.22 mm d–10.801.80 mm d–10.801.53 mm d–10.69
    GAMIL31.33 mm d–10.832.23 mm d–10.771.33 mm d–10.76
    GAMIL21.53 mm d–10.782.91 mm d–10.721.69 mm d–10.69
    850 hPa经向风FGOALS-g31.41 m s–10.972.13 m s–10.911.47 m s–10.78
    FGOALS-g21.96 m s–10.922.25 m s–10.881.73 m s–10.78
    GAMIL31.26 m s–10.972.88 m s–10.891.35 m s–10.83
    GAMIL21.56 m s–10.953.15 m s–10.851.89 m s–10.76
    850 hPa纬向风FGOALS-g30.77 m s–10.841.31 m s–10.870.91 m s–10.76
    FGOALS-g20.83 m s–10.791.41 m s–10.810.88 m s–10.77
    GAMIL30.76 m s–10.851.40 m s–10.860.85 m s–10.78
    GAMIL20.84 m s–10.811.62 m s–10.821.01 m s–10.74
    下载: 导出CSV
  • [1] Adler R F, Huffman G J, Chang A, et al. 2003. The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present) [J]. Journal of Hydrometeorology, 4(6): 1147−1167. doi: 10.1175/1525-7541(2003)004<1147:tvgpcp>2.0.co;2
    [2] Chou C, Neelin J D, Chen C A, et al. 2009. Evaluating the “Rich-Get-Richer” mechanism in tropical precipitation change under global warming [J]. J. Climate, 22(8): 1982−2005. doi: 10.1175/2008JCLI2471.1
    [3] Cook K H, Vizy E K. 2013. Projected changes in East African rainy seasons [J]. J. Climate, 26(16): 5931−5948. doi: 10.1175/JCLI-D-12-00455.1
    [4] Guo Z, Zhou T J. 2014. An improved diagnostic stratocumulus scheme based on estimated inversion strength and its performance in GAMIL2 [J]. Science China Earth Sciences, 57(11): 2637−2649. doi: 10.1007/s11430-014-4891-7
    [5] 何林强, 周天军, 李立娟, 等. 2022. FGOALS-g3模拟的南亚夏季风: 气候态和年际变率[J]. 大气科学, 46(5): 1098–1112

    He Linqiang, Zhou Tianjun, Li Lijuan, et al. 2022. South Asian summer monsoon simulated by FGOALS-g3 climate system model: Climatology and interannual variability [J]. Chinese Journal of Atmospheric Sciences (in Chinese). 46(5): 1098–1112. doi:10.3878/j.issn.1006-9895.2105.21042
    [6] Hersbach H, Bell W, Berrisford P, et al. 2019. Global reanalysis: Goodbye ERA-Interim, hello ERA5 [J]. ECMWF Newsletter, 159: 17−24. doi: 10.21957/vf291hehd7
    [7] Holtslag A A M, Boville B A. 1993. Local versus nonlocal boundary-layer diffusion in a global climate model [J]. J. Climate, 6(10): 1825−1842. doi: 10.1175/1520-0442(1993)006<1825:LVNBLD>2.0.CO;2
    [8] Huang B Y, Thorne P W, Banzon V F, et al. 2017. Extended reconstructed sea surface temperature, version 5 (ERSSTv5): Upgrades, validations, and intercomparisons [J]. J. Climate, 30(20): 8179−8205. doi: 10.1175/JCLI-D-16-0836.1
    [9] Kanamitsu M, Ebisuzaki W, Woollen J, et al. 2002. NCEP-DOE AMIP-II reanalysis (R-2) [J]. Bull. Amer. Meteor. Soc., 83(11): 1631−1643. doi: 10.1175/BAMS-83-11-1631
    [10] Klein S A, Hartmann D L. 1993. The seasonal cycle of low stratiform clouds [J]. J. Climate, 6(8): 1587−1606. doi: 10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2
    [11] Lee J Y, Wang B. 2014. Future change of global monsoon in the CMIP5 [J]. Climate Dyn. , 42(1–2): 101–119. doi: 10.1007/s00382-012-1564-0
    [12] Li J P, Zeng Q C. 2003. A new monsoon index and the geographical distribution of the global monsoons [J]. Advances in Atmospheric Sciences, 20(2): 299−302. doi: 10.1007/s00376-003-0016-5
    [13] Li L J, Lin P F, Yu Y Q, et al. 2013. The flexible global ocean–atmosphere–land system model, grid-point version 2: FGOALS-g2 [J]. Advances in Atmospheric Sciences, 30(3): 543−560. doi: 10.1007/s00376-012-2140-6
    [14] Li L J, Yu Y Q, Tang Y L, et al. 2020. The flexible global ocean–atmosphere–land system model grid-point version 3 (FGOALS-g3): Description and evaluation [J]. Journal of Advances in Modeling Earth Systems, 12(9): e2019MS002012. doi: 10.1029/2019MS002012
    [15] Liu L, Xie S P, Zheng X T, et al. 2014. Indian Ocean variability in the CMIP5 multi-model ensemble: The zonal dipole mode [J]. Climate Dyn. , 43(5–6): 1715–1730. doi:10.1007/s00382-013-2000-9
    [16] Nie Y, Li L J, Tang Y L, et al. 2019. Impacts of changes of external forcings from CMIP5 to CMIP6 on surface temperature in FGOALS-g2 [J]. SOLA, 15: 211−215. doi: 10.2151/sola.2019-038
    [17] Pascale S, Boos W R, Bordoni S, et al. 2017. Weakening of the North American monsoon with global warming [J]. Nat. Climate Change, 7(11): 806−812. doi: 10.1038/nclimate3412
    [18] Qian W H. 2000. Dry/wet alternation and global monsoon [J]. Geophys. Res. Lett., 27(22): 3679−3682. doi: 10.1029/1999GL011255
    [19] Seager R, Naik N, Vecchi G A. 2010. Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming [J]. J. Climate, 23(17): 4651−4668. doi: 10.1175/2010JCLI3655.1
    [20] Shi X J, Zhang W T, Liu J J. 2019. Comparison of anthropogenic aerosol climate effects among three climate models with reduced complexity [J]. Atmosphere, 10(18): 456. doi: 10.3390/atmos10080456
    [21] Slingo J M. 1987. The development and verification of a cloud prediction scheme for the ECMWF model [J]. Quart. J. Roy. Meteor. Soc., 113(477): 899−927. doi: 10.1002/qj.49711347710
    [22] Sperber K R, Annamalai H, Kang I S, et al. 2013. The Asian summer monsoon: An intercomparison of CMIP5 vs. CMIP3 simulations of the Late 20th century [J]. Climate Dyn., 41(9–10): 2711–2744. doi:10.1007/s00382-012-1607-6
    [23] Stevens B, Fiedler S, Kinne S, et al. 2017. MACv2-SP: A parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6 [J]. Geoscientific Model Development, 10(1): 433−452. doi: 10.5194/gmd-10-433-2017
    [24] Sun W Q, Li L J, Wang B. 2016. Reducing the biases in shortwave cloud radiative forcing in tropical and subtropical regions from the perspective of boundary layer processes [J]. Science China Earth Sciences, 59(7): 1427−1439. doi: 10.1007/s11430-016-5290-z
    [25] 唐彦丽, 俞永强, 李立娟, 等. 2019. FGOALS-g模式及其参与CMIP6的方案 [J]. 气候变化研究进展, 15(5): 551−557. doi: 10.12006/j.issn.1673-1719.2019.042

    Tang Yanli, Yu Yongqiang, Li Lijuan, et al. 2019. The introduction of FGOALS-g model and the experiment design in CMIP6 [J]. Climate Change Research (in Chinese), 15(5): 551−557. doi: 10.12006/j.issn.1673-1719.2019.042
    [26] Trenberth K E, Stepaniak D P, Caron J M. 2000. The global monsoon as seen through the divergent atmospheric circulation [J]. J. Climate, 13(22): 3969−3993. doi: 10.1175/1520-0442(2000)013<3969:TGMAST>2.0.CO;2
    [27] Wang B, Ding Q H. 2008. Global monsoon: Dominant mode of annual variation in the tropics [J]. Dyn. Atmos. Oceans, 44(3–4): 165–183. doi: 10.1016/j.dynatmoce.2007.05.002
    [28] Wang B, Wu R G, Fu X H. 2000. Pacific–East Asian teleconnection: How does ENSO affect East Asian climate? [J]. J. Climate, 13(9): 1517−1536. doi: 10.1175/1520-0442(2000)013<1517:PEATHD>2.0.CO;2
    [29] Wang B, Ding Q H, Fu X H, et al. 2005. Fundamental challenge in simulation and prediction of summer monsoon rainfall [J]. Geophys. Res. Lett., 32(15): L15711. doi: 10.1029/2005GL022734
    [30] Wang B, Kim H J, Kikuchi K, et al. 2011. Diagnostic metrics for evaluation of annual and diurnal cycles [J]. Climate Dyn. , 37(5–6): 941–955. doi:10.1007/s00382-010-0877-0
    [31] Wang B, Liu J, Kim H J, et al. 2012. Recent change of the global monsoon precipitation (1979-2008) [J]. Climate Dyn., 39(5): 1123−1135. doi: 10.1007/s00382-011-1266-z
    [32] Wang P X, Wang B, Cheng H, et al. 2017. The global monsoon across time scales: Mechanisms and outstanding issues [J]. Earth-Science Reviews, 174: 84−121. doi: 10.1016/j.earscirev.2017.07.006
    [33] Wang B, Jin C H, Liu J. 2020. Understanding future change of global monsoons projected by CMIP6 models [J]. J. Climate, 33(15): 6471−6489. doi: 10.1175/JCLI-D-19-0993.1
    [34] Wang B, Biasutti M, Byrne M P, et al. 2021. Monsoons climate change assessment [J]. Bull. Amer. Meteor. Soc., 102(1): E1−E19. doi: 10.1175/bams-d-19-0335.1
    [35] Wu Z W, Li J P. 2009. Seasonal prediction of the global precipitation annual modes with the grid–point atmospheric model of IAP LASG [J]. Acta Meteorologica Sinica, 23(4): 428−437.
    [36] Wu X Q, Deng L P, Song X L, et al. 2007. Coupling of convective momentum transport with convective heating in global climate simulations [J]. J. Atmos. Sci., 64(4): 1334−1349. doi: 10.1175/JAS3894.1
    [37] Xie P P, Arkin P A. 1997. Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs [J]. Bull. Amer. Meteor. Soc., 78(11): 2539−2558. doi: 10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2
    [38] Xie Z H, Di Z H, Luo Z D, et al. 2012. A quasi-three-dimensional variably saturated groundwater flow model for climate modeling [J]. Journal of Hydrometeorology, 13(1): 27−46. doi: 10.1175/JHM-D-10-05019.1
    [39] Yu R C. 1994. A two-step shape-preserving advection scheme [J]. Advances in Atmospheric Sciences, 11(4): 479−490. doi: 10.1007/BF02658169
    [40] 俞永强, 唐绍磊, 刘海龙, 等. 2018. 任意正交曲线坐标系下的海洋模式动力框架的发展与评估 [J]. 大气科学, 42(4): 877−889. doi: 10.3878/j.issn.1006-9895.1805.17284

    Yu Yongqiang, Tang Shaolei, Liu Hailong, et al. 2018. Development and evaluation of the dynamic framework of an ocean general circulation model with arbitrary orthogonal curvilinear coordinate [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 42(4): 877−889. doi: 10.3878/j.issn.1006-9895.1805.17284
    [41] Zeng Y J, Xie Z H, Yu Y, et al. 2016a. Ecohydrological effects of stream-aquifer water interaction: A case study of the Heihe River basin, northwestern China [J]. Hydrology and Earth System Sciences, 20(6): 2333−2352. doi: 10.5194/hess-20-2333-2016
    [42] Zeng Y J, Xie Z H, Yu Y, et al. 2016b. Effects of anthropogenic water regulation and groundwater lateral flow on land processes [J]. Journal of Advances in Modeling Earth Systems, 8(3): 1106−1131. doi: 10.1002/2016MS000646
    [43] Zeng Y J, Xie Z H, Zou J. 2017. Hydrologic and climatic responses to global anthropogenic groundwater extraction [J]. J. Climate, 30(1): 71−90. doi: 10.1175/JCLI-D-16-0209.1
    [44] Zeng Y J, Xie Z H, Liu S, et al. 2018. Global land surface modeling including lateral groundwater flow [J]. Journal of Advances in Modeling Earth Systems, 10(8): 1882−1900. doi: 10.1029/2018MS001304
    [45] Zhang L X, Zhou T J. 2014. An assessment of improvements in global monsoon precipitation simulation in FGOALS-s2 [J]. Advances in Atmospheric Sciences, 31(1): 165−178. doi: 10.1007/s00376-013-2164-6
    [46] 张丽霞, 周天军, 吴波, 等. 2008. 气候系统模式FGOALS_s1.1对热带降水年循环模态的模拟 [J]. 气象学报, 66(6): 968−981. doi: 10.3321/j.issn:0577-6619.2008.06.011

    Zhang Lixia, Zhou Tianjun, Wu Bo, et al. 2008. The annual modes of tropical precipitation simulated by LASG/IAP ocean–atmosphere coupled model FGOALS-s1.1 [J]. Acta Meteorologica Sinica (in Chinese), 66(6): 968−981. doi: 10.3321/j.issn:0577-6619.2008.06.011
    [47] 张丽霞, 周天军, 曾先锋, 等. 2011. 积云参数化方案对热带降水年循环模态模拟的影响 [J]. 大气科学, 35(4): 777−790. doi: 10.3878/j.issn.1006-9895.2011.04.16

    Zhang Lixia, Zhou Tianjun, Zeng Xianfeng, et al. 2011. The annual modes of tropical precipitation simulated with LASG/IAP AGCM: Sensitivity to convection schemes [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 35(4): 777−790. doi: 10.3878/j.issn.1006-9895.2011.04.16
    [48] 张涛, 谢丰, 薛巍, 等. 2016. 格点大气环流模式GAMIL2参数不确定性的量化分析与优化 [J]. 地球物理学报, 59(2): 465−475. doi: 10.6038/cjg20160206

    Zhang Tao, Xie Feng, Xue Wei, et al. 2016. Quantification and optimization of parameter uncertainty in the grid–point atmospheric model GAMIL2 [J]. Chinese Journal of Geophysics (in Chinese), 59(2): 465−475. doi: 10.6038/cjg20160206
    [49] Zhang L X, Zhou T J, Klingaman N P, et al. 2018. Effect of horizontal resolution on the representation of the global monsoon annual cycle in AGCMs [J]. Advances in Atmospheric Sciences, 35(8): 1003−1020. doi: 10.1007/s00376-018-7273-9
    [50] Zhou T J, Yu R C, Li H M, et al. 2008. Ocean forcing to changes in global monsoon precipitation over the recent half–century [J]. J. Climate, 21(15): 3833−3852. doi: 10.1175/2008jcli2067.1
    [51] Zhou T J, Chen X L, Dong L, et al. 2014. Chinese contribution to CMIP5: An overview of five Chinese models’ performances [J]. Journal of Meteorological Research, 28(4): 481−509. doi: 10.1007/s13351-014-4001-y
    [52] Zhou T J, Turner A G, Kinter J L, et al. 2016. GMMIP (v1.0) contribution to CMIP6: Global Monsoons Model Inter-comparison Project [J]. Geosci. Model Dev., 9(10): 3589−3604. doi: 10.5194/gmd-9-3589-2016
    [53] Zhou T J, Wang B, Yu Y Q, et al. 2018. The FGOALS climate system model as a modeling tool for supporting climate sciences: An overview [J]. Earth and Planetary Physics, 2(4): 276−291. doi: 10.26464/epp2018026
    [54] 周天军, 陈晓龙, 何编, 等. 2019a. 全球季风模式比较计划(GMMIP)概述 [J]. 气候变化研究进展, 15(5): 493−497. doi: 10.12006/j.issn.1673-1719.2019.132

    Zhou Tianjun, Chen Xiaolong, He Bian, et al. 2019a. Short commentary on CMIP6 global monsoons model intercomparison project (GMMIP) [J]. Climate Change Research (in Chinese), 15(5): 493−497. doi: 10.12006/j.issn.1673-1719.2019.132
    [55] 周天军, 邹立维, 陈晓龙. 2019b. 第六次国际耦合模式比较计划(CMIP6)评述 [J]. 气候变化研究进展, 15(5): 445−456. doi: 10.12006/j.issn.1673-1719.2019.193

    Zhou Tianjun, Zou Liwei, Chen Xiaolong. 2019b. Commentary on the coupled model intercomparison project phase 6 (CMIP6) [J]. Climate Change Research (in Chinese), 15(5): 445−456. doi: 10.12006/j.issn.1673-1719.2019.193
    [56] Zou J, Xie Z H, Yu Y, et al. 2014. Climatic responses to anthropogenic groundwater exploitation: A case study of the Haihe River basin, northern China [J]. Climate Dyn., 42(7–8): 2125–2145. doi:10.1007/s00382-013-1995-2
    [57] Zou J, Xie Z H, Zhan C S, et al. 2015. Effects of anthropogenic groundwater exploitation on land surface processes: A case study of the Haihe River basin, northern China [J]. J. Hydrol., 524: 625−641. doi: 10.1016/j.jhydrol.2015.03.026
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  • 收稿日期:  2021-06-10
  • 录用日期:  2021-12-23
  • 网络出版日期:  2021-12-27
  • 刊出日期:  2023-03-15

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