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

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

张星^{1, 2,},
周天军^{1, 2, ,},
张文霞¹,
左萌¹,
张丽霞¹

1.
中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室(LASG), 北京100029
2.
中国科学院大学地球与行星科学学院, 北京100049

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
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- 被引次数: 0
出版历程
- 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

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

Xing ZHANG^{1, 2
,},
Tianjun ZHOU^{1, 2
, ,},
Wenxia ZHANG¹,
Meng ZUO¹,
Lixia ZHANG¹

1.
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
2.
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049

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

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。
- 全球季风 /
- FGOALS-g2模式 /
- FGOALS-g3模式 /
- 海气耦合
Abstract: Based on the observation and reanalysis data, this study systematically evaluates the global monsoon simulated by the new version of the climate system model FGOALS-g3 by applying moisture budget diagnosis and composite analysis. Moreover, this work analyzes the advantages and disadvantages of the new version when compared with FGOALS-g2. Influences of the air–sea coupling process on the simulated results are discussed by comparing with the corresponding atmospheric component model GAMIL. FGOALS-g3 reasonably reproduces the basic characteristics of the climatology of the global monsoon, including the annual mean precipitation as well as circulation, annual cycle modes, monsoon precipitation intensity, and monsoon region. However, the model underestimates the annual mean precipitation over the land monsoon region, overestimates the annual mean precipitation over the ocean region, and the simulated spring–fall asymmetric mode of the annual cycle is stronger in the tropical monsoon region. The results show that the smaller land monsoon region than the observation in FGOALS-g3 is associated with the weaker vertical moisture advection (especially the thermodynamic term) in summer. For the inter-annual variability, FGOALS-g3 can reproduce the drier pattern of the global monsoon during the El Niño year. However, some biases in precipitation anomalies exist in some monsoon regions. For instance, the precipitation in the west African monsoon region is more than normal, and the precipitation in the southwest Indian Ocean is a dipole anomaly, both of which are inconsistent with the observation. Moreover, the precipitation in the northwest Pacific monsoon region is greater than the observation during the El Niño year. There is no weak convergence center in the upper layer of western Africa in the simulation, and the simulated maritime continent is warmer than observation, resulting in the convective center moving westward during the El Niño year. Compared with FGOALS-g2, FGOALS-g3 improves the simulation of monsoon circulation, inter-annual variability of monsoon precipitation, and monsoon–ENSO relationship. When comparing the coupled and uncoupled simulations, most biases in the coupled model originate from the atmospheric model itself, and the air–sea coupling process partially improves the simulation of precipitation and circulation of the Asian–Australian monsoon region and the tropical Indian Ocean. However, the sea surface temperature bias caused by the coupled process enhances the dry bias of the Indian Peninsula and the wet bias of the tropical Indian Ocean.
- Global monsoon /
- FGOALS-g2 model /
- FGOALS-g3 model /
- Air–sea coupling

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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)

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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

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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

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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

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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°)

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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)

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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)

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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

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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

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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-g2	FGOALS-g3
AGCM	GAMIL2～2.8°(128×60) L26	GAMIL3～2°(180×80) L26
OGCM	LICOM 2.0 360×196 L30	LICOM 3.0 360×218 L30
陆面	CLM3128×60 L10+5	CAS-LSM180×80
海冰	CICE4-LASG360×196 L4	CICE 4.0360×218 L4+1
耦合器	CPL6	CPL7
参考文献	(Li et al., 2013)	(Li et al., 2020)

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表 2 GAMIL3和GAMIL2的对比

Table 2. Comparison of GAMIL3 model and GAMIL2 model

		GAMIL2	GAMIL3
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)

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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
		RMSE	PCC	RMSE	PCC	RMSE	PCC
降水	FGOALS-g3	1.48 mm d^–1	0.80	2.18 mm d^–1	0.74	1.81 mm d^–1	0.61
	FGOALS-g2	1.22 mm d^–1	0.80	1.80 mm d^–1	0.80	1.53 mm d^–1	0.69
	GAMIL3	1.33 mm d^–1	0.83	2.23 mm d^–1	0.77	1.33 mm d^–1	0.76
	GAMIL2	1.53 mm d^–1	0.78	2.91 mm d^–1	0.72	1.69 mm d^–1	0.69
850 hPa经向风	FGOALS-g3	1.41 m s^–1	0.97	2.13 m s^–1	0.91	1.47 m s^–1	0.78
	FGOALS-g2	1.96 m s^–1	0.92	2.25 m s^–1	0.88	1.73 m s^–1	0.78
	GAMIL3	1.26 m s^–1	0.97	2.88 m s^–1	0.89	1.35 m s^–1	0.83
	GAMIL2	1.56 m s^–1	0.95	3.15 m s^–1	0.85	1.89 m s^–1	0.76
850 hPa纬向风	FGOALS-g3	0.77 m s^–1	0.84	1.31 m s^–1	0.87	0.91 m s^–1	0.76
	FGOALS-g2	0.83 m s^–1	0.79	1.41 m s^–1	0.81	0.88 m s^–1	0.77
	GAMIL3	0.76 m s^–1	0.85	1.40 m s^–1	0.86	0.85 m s^–1	0.78
	GAMIL2	0.84 m s^–1	0.81	1.62 m s^–1	0.82	1.01 m s^–1	0.74

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