气候系统模式FGOALS模拟的南亚夏季风：偏差和原因分析

黄昕; 周天军; 吴波; 陈晓龙

doi:10.3878/j.issn.1006-9895.1805.18131

气候系统模式FGOALS模拟的南亚夏季风：偏差和原因分析

doi: 10.3878/j.issn.1006-9895.1805.18131

黄昕^{1, 2,},
周天军^1, ,,
吴波¹,
陈晓龙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, 北京 100049

基金项目:

国家自然科学基金项目 41420104006

国家自然科学基金项目 41330423

国家自然科学基金项目 41605057

中国科学院"国际伙伴计划-国际大科学计划培育专项"项目 134111KYSB20160031

详细信息

作者简介:
黄昕, 女, 1993年出生, 硕博连读研究生, 主要从事气候模拟和季风研究。E-mail:huangxin@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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出版历程
- 收稿日期: 2018-02-26
- 网络出版日期: 2018-05-15
- 刊出日期: 2019-03-15

South Asian Summer Monsoon Simulated by Two Versions of FGOALS Climate System Model: Model Biases and Mechanims

Xin HUANG^{1, 2
,},
Tianjun ZHOU^{1
, ,},
Bo WU¹,
Xiaolong CHEN¹

1.
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
2.
University of the Chinese Academy of Sciences, Beijing 100049

Funds:

National Natural Science Foundation of China (NSFC) 41420104006

National Natural Science Foundation of China (NSFC) 41330423

National Natural Science Foundation of China (NSFC) 41605057

International Partnership Program of Chinese Academy of Sciences 134111KYSB20160031

摘要

摘要: 本文通过与观测和再分析资料的对比，评估了LASG/IAP发展的气候系统模式FGOALS的两个版本FGOALS-g2和FGOALS-s2对南亚夏季风的气候态和年际变率的模拟能力，并使用水汽收支方程诊断，研究了造成降水模拟偏差的原因。结果表明，两个模式夏季气候态降水均在陆地季风槽内偏少，印度半岛附近海域偏多，在降水年循环中表现为夏季北侧辐合带北推范围不足。FGOALS-g2中赤道印度洋"东西型"海温偏差导致模拟的东赤道印度洋海上辐合带偏弱，而FGOALS-s2中印度洋"南北型"海温偏差导致模拟的海上辐合带偏向西南。水汽收支分析表明，两个模式中气候态夏季风降水的模拟偏差主要来自于整层积分的水汽通量，尤其是垂直动力平流项的模拟偏差。一方面，夏季阿拉伯海和孟加拉湾的海温偏冷而赤道西印度洋海温偏暖，造成向印度半岛的水汽输送偏少；另一方面，对流层温度偏冷，冷中心位于印度半岛北部对流层上层，同时季风槽内总云量偏少，云长波辐射效应偏弱，对流层经向温度梯度偏弱以及大气湿静力稳定度偏强引起的下沉异常造成陆地季风槽内降水偏少。在年际变率上，观测中南亚夏季风环流和降水指数与Niño3.4指数存在负相关关系，但FGOALS两个版本模式均存在较大偏差。两个模式中与ENSO暖事件相关的沃克环流异常下沉支和对应的负降水异常西移至赤道以南的热带中西印度洋，沿赤道非对称的加热异常令两个模式中越赤道环流季风增强，导致印度半岛南部产生正降水异常。ENSO相关的沃克环流异常下沉支及其对应的负降水异常偏西与两个模式对热带南印度洋气候态降水的模拟偏差有关。研究结果表明，若要提高FGOALS两个版本模式对南亚夏季风气候态模拟技巧，需减小耦合模式对印度洋海温、对流层温度及云的模拟偏差；若要提高南亚夏季风和ENSO相关性模拟技巧需要提高模式对热带印度洋气候态降水以及与ENSO相关的环流异常的模拟能力。
- 南亚夏季风 /
- 模式偏差 /
- 气候态与年际变率 /
- FGOALS模式
Abstract: Based on comparison with observational and reanalysis data, we assess the performances of two versions of the IAP/LASG Flexible Global Ocean-Atmosphere-Land System (FGOALS), FGOALS-g2 and FGOALS-s2, in simulating the climatology and interannual variability of South Asian summer monsoon (SASM). Moisture budget analysis is applied to explain the precipitation biases. FGOALS-g2 and FGOALS-s2 both underestimate precipitation over the continental monsoon trough but overestimate precipitation over the adjacent ocean. The northward seasonal migration of continental convergence zone is weaker than observation. The east-west sea surface temperature (SST) biases in the equatorial Indian Ocean (IO) simulated by FGOALS-g2 lead to weak southern intertropical convergence zone (ITCZ) over the eastern equatorial IO, while the south-north SST biases over the IO simulated by FGOALS-s2 result in southwestward shift of the ITCZ. Moisture budget analysis shows that precipitation biases in the FGOALS models are mainly attributed to the convergence of vertically integrated moisture flux biases, especially biases in the vertical dynamic moisture transport term. On the one hand, cold SST biases in the Arabian Sea and the Bay of Bengal along with warm SST biases in the tropical western IO reduce moisture flux over the Indian subcontinent in both models. On the other hand, cold biases of tropospheric temperature in the FGOALS models are most prominent in the upper troposphere over northern India. The FGOALS models also simulate weak longwave cloud radiative effects over the monsoon trough region due to their negative biases of cloud fraction over South Asia. The subsiding branches linked with the reduced meridional tropospheric temperature gradient and strengthened gross moist stability decrease climatological precipitation in the continental monsoon trough region. The FGOALS models cannot reasonably simulate the ENSO-SASM relationship at interannual time scale. The descending branch of the anomalous Walker circulation and corresponding negative precipitation anomalies are shifted to the tropical central-western IO to the south of the equator. The heating anomalies asymmetric about the equator enhance the northward cross-equatorial monsoon circulation and further cause erroneous positive precipitation anomalies over southern India. The shifts of the anomalous Walker circulation and negative precipitation anomalies are associated with the model biases in simulating climatological precipitation over the southern tropical IO. Our results show that reducing IO SST biases, tropospheric temperature biases and cloud biases is necessary for better simulation of mean state SASM by climate system models. On interannual time scale, the reasonable simulation of ENSO-monsoon relationship relies on successful simulation of climatological precipitation over the tropical IO and ENSO related circulation anomalies.
- South Asian summer monsoon /
- Model bias /
- Climatology and interannnual variability /
- FGOALS model

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图 1 70°E~90°E区域平均降水的气候态年循环（阴影，单位：mm d⁻¹）：（a）GPCP；（b）CMAP；（c）FGOALS-g2；（d）FGOALS-s2。其中（b–d）右上角数字表示与GPCP在10°S~30°N、5~9月（虚线框内）内的空间相关系数

Figure 1. Annual cycle climatology for rainfall (shaded, units: mm d⁻¹) averaged between 70°E–90°E from (a) GPCP data, (b) CMAP data, (c) FGOALS-g2 model and (d) FGOALS-s2 model. Numbers in the upper-right corner of (b–d) are pattern correlations with GPCP over 10°S–30°N in May–September (the dashed region in Figs. b, c, d)

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图 2 JJAS（6~9月）季节平均南亚夏季风降水（填色）及850 hPa风场（矢量）的气候态及其偏差。气候态：（a）GPCP/JRA55，（c）FGOALS-g2，（e）FGOALS-s2；相对于GPCP/JRA55的降水（环流）偏差：（b）CMAP/NCEP，（d）FGOALS-g2，（f）FGOALS-s2。（a）右上方两个数字分别是CMAP与GPCP的降水以及NCEP与JRA55的环流在（20°S~40°N，40°E~100°E）内的空间相关系数；（c, e）右上方两个数字分别是相应模式与GPCP的降水以及模式与JRA55的环流在（20°S~40°N，40°E~100°E）内的空间相关系数。降水单位为mm d⁻¹；风场单位为m s⁻¹

Figure 2. Climatology of JJAS (June–July–August–September) seasonal-mean South Asian summer monsoon (SASM) precipitation (color shaded, units: mm d⁻¹) and 850 hPa winds (vectors, units: m s⁻¹) from (a) GPCP/JRA55, (c) FGOALS-g2, (e) FGOALS-s2. Biases of precipitation with respect to GPCP and biases of 850 hPa wind with respect to JRA55: (b) CMAP/NCEP, (d) FGOALS-g2, (f) FGOALS-s2. Numbers in the upper-right corner of (a, c, e) are the pattern correlations of precipitation and 850 hPa winds, respectively, between CMAP/NCEP, FGOALS-g2, FGOALS-s2 with GPCP/JRA55 in (20°S–40°N, 40°E–100°E)

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图 3 JRA55（第一行）资料与FGOALS-g2（第二行）和FGOALS-s2（第三行）模拟的气候态JJAS季节平均的水汽收支各项：（a, b, c）蒸发（E; 单位：mm d⁻¹）；（d, e, f）整层积分水汽通量（V·q; 矢量，单位：m mm d⁻¹）及其散度（$ - \nabla \cdot (\mathit{\boldsymbol{V}} \cdot q) $）；填色，单位：mm d⁻¹）；（g, h, i）水汽垂直平流（$ - \langle \omega {\partial _{\rm{p}}}q\rangle $）; 单位：mm d⁻¹）；（j, k, l）水汽水平平流（$ - \langle \mathit{\boldsymbol{V}} \cdot \nabla q\rangle $; 单位：mm d⁻¹）；（m, n, o）残差项（res; 单位：mm d⁻¹）。（p）气候态JJAS全印度降水（AIR）定量水汽收支（红色为观测及再分析资料，蓝色为FGOALS-g2，绿色为FGOALS-s2，单位：mm d⁻¹）。气候态取1961~1999年平均。AIR为紫色框（7°N~30°N，65°E~95°E）中陆地格点降水

Figure 3. Climatology of JJAS moisture budget components from JRA55 (first line), FGOALS-g2 (second line), and FGOALS-s2 (third line): (a, b, c) Evaporation (E; units: mm d⁻¹); (d, e, f) vertically integrated moisture fluxes (V·q; vectors, units: m mm d⁻¹) and their divergence ($ - \nabla \cdot (\mathit{\boldsymbol{V}} \cdot q) $; color shaded, units: mm d⁻¹); (g, h, i) vertical moisture advection ($ - \langle \omega {\partial _{\rm{p}}}q\rangle $; units: mm d⁻¹); (j, k, l) horizontal moisture advection ($ - \langle \mathit{\boldsymbol{V}} \cdot \nabla q\rangle $; units: mm d⁻¹); (m, n, o) the residual term (res; units: mm d⁻¹). (p) Quantitative moisture budget analysis of All Indian Rainfall (AIR) from observations and reanalysis data in red, FGOALS-g2 model in blue, FGOALS-s2 model in green, units: mm d⁻¹. Climatology is the average over 1979–2005. AIR indicates precipitation over the land points within the purple square in each panel (7°N–30°N, 65°E–95°E)

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图 4 FGOALS-g2（左）和FGOALS-s2（右）相对于GPCP/JRA55气候态的模拟偏差：（a, b）降水偏差（$ \Delta P $; 填色，单位：mm d⁻¹）和整层积分的水汽通量偏差（$ \Delta (\mathit{\boldsymbol{V}} \cdot q)$；矢量，单位：m mm d⁻¹）；（c, d）垂直水汽平流项偏差（$ - \Delta \langle \omega {\partial _{\rm{p}}}q\rangle $; 单位：mm d⁻¹）；（e, f）垂直动力项偏差（$ - \langle \Delta \omega {\partial _{\rm{p}}}q\rangle $; 单位：mm d⁻¹）；（g, h）垂直热力项偏差（$ - \langle \omega \Delta {\partial _{\rm{p}}}q\rangle $; 单位：mm d⁻¹）

Figure 4. Biases of climatological (a, b) precipitation ($ \Delta P $; color shaded, units: mm d⁻¹) and vertically integrated moisture fluxes ($ \Delta (\mathit{\boldsymbol{V}} \cdot q) $; vectors, units: m mm d⁻¹), (c, d) vertical moisture advection term ($ - \Delta \langle \omega {\partial _{\rm{p}}}q\rangle $; units: mm d⁻¹), (e, f) vertical dynamic component ($ - \langle \Delta \omega {\partial _{\rm{p}}}q\rangle $; units: mm d⁻¹), (g, h) vertical thermodynamic component ($ - \langle \omega \Delta {\partial _{\rm{p}}}q\rangle $; units: mm d⁻¹) between simulations of FGOALS-g2 (left)/ FGOALS-s2 (right) and GPCP/JRA55 data

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图 5 相对于HadISST气候态JJAS海表温度的模拟偏差（∆SST，填色，单位K）和相对于JRA55气候态JJAS 850 hPa风场模拟偏差（∆UV850，矢量，单位：m s⁻¹）：（a）FGOALS-g2；（b）FGOALS-s2。相对于JRA55（60°E~100°E）区域平均的气候态JJAS对流层温度（∆ta，填色，单位K）和经圈环流[∆v-wap，矢量，单位Pa s⁻¹经圈环流中的垂直速度×（−150）]模拟偏差：（c）FGOALS-g2；（d）FGOALS-s2。相对于ISCCP气候态JJAS总云量的模拟偏差（∆CF）：（e）FGOALS-g2；（f）FGOALS-s2。相对于CERES-EBAF气候态JJAS大气层顶的云长波辐射通量的模拟偏差（∆LWCRE，单位：W m⁻²）：（g）FGOALS-g2；（h）FGOALS-s2

Figure 5. Biases of simulated climatological JJAS SST relative to HadISST (∆SST, color shaded, units: K) and 850 hPa winds relative to JRA55 (∆UV850, vectors, units: m s⁻¹): (a) FGOALS-g2; (b) FGOALS-s2. Biases of climatological JJAS tropospheric temperature (∆ta, color shaded, units: K) and meridional circulation [∆v-wap, vectors, units: Pa s⁻¹, Omega is multiplied by (−150)] averaged over (60°E–100°E) relative to JRA55: (a) FGOALS-g2; (b) FGOALS-s2. Biases of climatological JJAS total cloud fraction relative to ISCCP (∆CF): (e) FGOALS-g2; (f) FGOALS-s2. Biases of climatological JJAS longwave cloud radiative flux (∆LWCRE) at the top of the atmosphere (TOA) relative to CERES-EBAF (units: W m⁻²): (g) FGOALS-g2; (h) FGOALS-s2

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图 6 标准化的JJAS Niño3.4指数回归的JJAS降水异常（填色，单位：mm d⁻¹）和850 hPa风场异常（矢量，单位：m s⁻¹）的空间分布：（a）GPCP降水，JRA55风场；（b）FGOALS-g2；（c）FGOALS-s2。（d）模式和JRA55在（7°~30°N，65°~95°E）区域内与ENSO相关的降水异常之差（∆δP'）的水汽收支分析（蓝色：FGOALS-g2，绿色：FGOALS-s2）。ENSO相关的降水异常之差由ENSO相关的蒸发异常之差（$ \Delta \delta E' $）、垂直($\Delta \delta - \langle \omega '{\partial _{\rm{p}}}\overline q \rangle $)和水平$ (\Delta \delta - \langle \mathit{\boldsymbol{V'}} \cdot \nabla \overline q \rangle ) $动力项异常之差、垂直$(\Delta \delta - \langle \overline \omega {\partial _{\rm{p}}}q'\rangle ) $和水平$ (\Delta \delta - \langle \mathit{\boldsymbol{\overline V}} \cdot \nabla q'\rangle ) $热力项异常之差及残差项异常之差($ \Delta \delta {\rm{res}} $)贡献。观测中Niño3.4指数来自HadISST海温月资料。（b）和（c）右上角两个数分别表示模式与GPCP/JRA55在（0°N~30°N，60°E~100°E）区域内降水量和850 hPa环流异常的空间相关系数。打点为相关系数通过90%的显著性检验，蓝框为AIR降水范围，红框为WYI风场范围

Figure 6. JJAS seasonal-mean precipitation anomalies (color shaded, units: mm d⁻¹) and 850 hPa winds anomalies (vectors, units: m s⁻¹) regressed onto standardized Niño3.4 index: (a) GPCP precipitation, JRA55 winds; (b) FGOALS-g2; (c) FGOALS-s2. (d) Moisture budget analysis of biases in ENSO-related precipitation anomalies ($\Delta \delta E' $) between models and JRA55 data in region (7°–30°N, 65°–95°E) (blue: FGOALS-g2, green: FGOALS-s2). Biases in ENSO-related precipitation anomalies are contributed by biases in ENSO-related evaporation anomalies ($ \Delta \delta E' $), vertical ($ \Delta \delta - \langle \omega '{\partial _{\rm{p}}}\overline q \rangle $) and horizontal $ (\Delta \delta - \langle \mathit{\boldsymbol{V'}} \cdot \nabla \overline q \rangle ) $ dynamic terms anomalies, vertical $ (\Delta \delta - \langle \overline \omega {\partial _{\rm{p}}}q'\rangle ) $ and horizontal $ (\Delta \delta - \langle \mathit{\boldsymbol{\overline V}} \cdot \nabla q'\rangle ) $ thermodynamic terms anomalies, residual term anomalies ($ \Delta \delta {\rm{res}}$). Observed Niño3.4 index is calculated from HadISST monthly SST data. Numbers in the upper-right corner of (b, c) are the pattern correlations of anomalous precipitation and 850 hPa circulation between FGOALS-g2 or FGOALS-s2 simulations and GPCP/JRA55 data in region (0°–30°N, 60°E–100°E). Dot regions pass the test at a confidence level of > 90%. Blue (red) rectangle: AIR precipitation (WYI winds) region

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图 7 标准化的JJAS Niño3.4指数回归的海表温度异常（填色，单位：K）：（a）HadISST；（c）FGOALS-g2；（e）FGOALS-g2。回归的200 hPa速度势异常（填色，单位：m² s⁻¹）和200 hPa风场异常（矢量，单位：m s⁻¹）：（b）JRA55；（d）FGOALS-g2；（f）FGOALS-g2。打点为相关系数通过90%的显著性检验。（a, c, e）中黑框表示Niño3.4区

Figure 7. Sea surface temperature anomalies (color shaded, units: K) regressed onto standardized JJAS Niño3.4 index: (a) HadISST; (c) FGOALS-g2; (e) FGOALS-s2. 200 hPa velocity potential anomalies (color shaded, units: m² s⁻¹) and 200 hPa wind anomalies (vectors, units: m s⁻¹) regressed onto standardized JJAS Niño3.4 index: (b) JRA55; (d) FGOALS-g2; (f) FOALS-s2. Regions with dots pass the test with a confidence level of > 90%. Black rectangles in (a, c, e) denote the Niño3.4 region

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表 1 1979~2005年观测（OBS）和模式中南亚夏季风降水和环流异常与Niño3.4指数的相关系数，以及观测和模式中与ENSO相关的沃克环流指数

Table 1. Correlation coefficients of the South Asian summer monsoon precipitation and circulation anomalies with Niño 3.4 index from observations (OBS) and models in 1979–2005, along with the ENSO related Walker circulation index from observations and models

	与Niño3.4指数相关系数		沃克环流指数
	AIR-Niño3.4	WYI-Niño3.4	强度/ hPa	位置（下沉支，上升支）
OBS	−0.36	−0.64	−54.2	(105°E, 158°W)
FGOALS-g2	−0.03	0.04	−54.2	(63°E, 145°W)
FGOALS-s2	−0.09	−0.05	−54.2	(63°E, 158°W)

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