relationships between the east asian-western north pacific monsoon and enso simulated by fgoals-s2

ADVANCES IN ATMOSPHERIC SCIENCES, VOL. 30, NO. 3, 2013, 713–725

Relationships between the East Asian–Western North Pacific

Monsoon and ENSO Simulated by FGOALS-s2

WU Bo∗ (� �) and ZHOU Tianjun (��)

State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,

Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

(Received 15 May 2012; revised 20 December 2012)

ABSTRACT

The relationships between ENSO and the East Asian–western North Pacific monsoon simulated by theFlexible Global Ocean-Atmosphere-Land System model, Spectral Version 2 (FGOALS-s2), a state-of-the-artcoupled general circulation model (CGCM), are evaluated. For El Nino developing summers, FGOALS-s2reproduces the anomalous cyclone over the western North Pacific (WNP) and associated negative precipita-tion anomalies in situ. In the observation, the anomalous cyclone is transformed to an anomalous anticycloneover the WNP (WNPAC) during El Nino mature winters. The model reproduces the WNPAC and associatedpositive precipitation anomalies over southeastern China during winter. However, the model fails to simu-late the asymmetry of the wintertime circulation anomalies over the WNP between El Nino and La Nina.The simulated anomalous cyclone over the WNP (WNPC) associated with La Nina is generally symmetricabout the WNPAC associated with El Nino, rather than shifted westward as that in the observation. Thediscrepancy can partially explain why simulated La Nina events decay much faster than observed. In theobservation, the WNPAC maintains throughout the El Nino decaying summer under the combined effectsof local forcing of the WNP cold sea surface temperature anomaly (SSTA) and remote forcing from basin-wide warming in the tropical Indian Ocean. FGOALS-s2 captures the two mechanisms and reproduces theWNPAC throughout the summer. However, owing to biases in the mean state, the precipitation anomaliesover East Asia, especially those of the Meiyu rain belt, are much weaker than that in the observation.

Key words: coupled general circulation model, tropical air-sea interaction, interannual variability of mon-soon

Citation: Wu, B., and T. J. Zhou, 2013: Relationships between the East Asian–western North Pacificmonsoon and ENSO simulated by FGOALS-s2. Adv. Atmos. Sci., 30(3), 713–725, doi: 10.1007/s00376-013-2103-6.

1. Introduction

The interannual variability of the East Asian–western North Pacific (EA–WNP) monsoon is influ-enced by ENSO, the most dominant interannual vari-ability mode in the tropics (see reviews by Wang andLi, 2004 and Lau and Wang, 2006). Both the methodof influence and its final effects show distinctive season-ally evolving characteristics (Zhang et al., 1999; Chouet al., 2009; Wu et al., 2009a). The seasonal depen-dence is associated with both the inherent seasonalcycle of the monsoon (Huang et al., 2008) and thestrong phase locking of ENSO (Rasmusson and Car-penter, 1982). Many studies have been devoted to the

study of ENSO-monsoon relationships in an individ-ual season, especially in ENSO developing or decayingsummers (e.g. Huang and Wu, 1989; Chang et al.,2000; Wu et al., 2003; Lu, 2005; Ye and Lu, 2011)and mature winters (e.g. Li, 1990; Zhang et al., 1996;Gong and Wang, 1999).

The seasonal dependence of ENSO-monsoon rela-tionships does not mean that we can cut off the link-ages between different seasons. In fact, owing to activeair-sea interactions in the western Pacific warm pool,the effects of ENSO on the EA–WNP monsoon arealways retained by the warm pool ocean and furthermodulate monsoon variability in the following seasons.For example, during El Nino mature winters, El Nino-

∗Corresponding author: WU Bo, [email protected]

© China National Committee for International Association of Meteorology and Atmospheric Sciences (IAMAS), Institute of AtmosphericPhysics (IAP) and Science Press and Springer-Verlag Berlin Heidelberg 2013

714 ENSO-MONSOON RELATIONSHIPS IN FGOALS-S2 VOL. 30

related remote forcing can excite an anomalous anti-cyclone over the WNP (WNPAC) (Wang et al., 2000;Lau et al., 2000). The WNPAC can be coupled withan underlying cold sea surface temperature anomaly(SSTA) through positive wind-evaporation-SST feed-back and maintains until the onset of the WNP sum-mer monsoon (Wang et al., 2003). The retained coldSSTA tends to weaken the WNP summer monsoonduring El Nino decaying summers (Wu et al., 2010a).

The impact of ENSO on the EA–WNP monsoonis not constrained in direct ways, but further compli-cated by the involvement of the tropical Indian Ocean(Wu and Meng, 1998; Kug et al., 2006; Wu et al.,2009a). The tropical Indian Ocean SST tends to evolveto a basin-wide warming after an El Nino mature win-ter owing to El Nino remote forcing (Klein et al., 1999)and local air-sea interactions (Xie et al., 2002; Lauand Nath, 2003). The warming pattern acts as a ca-pacitor that extends the El Nino impact on the EA–WNP monsoon when the warm SSTA in the equatorialcentral-eastern Pacific generally disappears or even in-verses in the following summer (Terao and Kubota,2005; Yang et al., 2007; Li et al., 2008; Wu et al.,2009a; Xie et al., 2009; Huang et al., 2010; Qu andHuang, 2012).

Considering the importance of air-sea interactionprocesses in EA–WNP monsoon variability, manystudies have tried to use coupled general circulationmodels (CGCMs) to predict EA–WNP monsoon vari-ations (e.g. Chowdary et al., 2010; Lee et al., 2011).It has been found that, although the multi-model en-semble shows high prediction skill, the performances ofthe individual models are quite different (Chowdary etal., 2010). The accuracy of prediction should be closelyassociated with the skill of individual models in simu-lating monsoon variability and associated processes.

The main purpose of this paper is to evalu-ate the performance of the Flexible Global Ocean-Atmosphere-Land System model, Spectral Version 2(FGOALS-s2), a CGCM developed by the NationalKey Laboratory of Numerical Modeling for Atmo-spheric Sciences and Geophysical Fluid Dynamics, In-stitute of Atmospheric Physics (LASG/IAP), in sim-ulating the relationship between ENSO and the EA–WNP monsoon. As we know, the previous versionof FGOALS-s shows relatively low skill in this area,mainly owing to the wrong phase locking of the mod-eled ENSO (Wu et al., 2009b). After nearly fiveyears of effort, the model has been improved in var-ious facets, especially in the annual cycle of SST inthe equatorial eastern Pacific and ENSO (Bao et al.,2013). Therefore, it is necessary to carefully assess theENSO-monsoon relationship in the current version ofthe model. The evaluation will offer some information

for further applications of the model in the study ofmonsoon variability or tropical air-sea interactions.

The rest of the paper is organized as follows. In sec-tion 2, the model, experiment, observational dataset,and analysis methods are introduced. The simulatedresults are compared with the observation in section3. Section 4 summarizes the major conclusions.

2. Models, observational datasets and meth-ods

2.1 Models

FGOALS-s2 is a state-of-the-art global coupled cli-mate model developed by the LASG/IAP and includesan atmospheric, ocean, land and ice components.The atmospheric component is version two of theLASG/IAP’s Spectral Atmosphere Model (SAMIL2),with a horizontal resolution of about 2.81◦ (lon)×1.66◦

(lat) and 26 levels in the vertical direction. The oceancomponent is version two of the LASG IAP ClimateOcean Model (LICOM2), with a horizontal resolutionof about 1◦×1◦ in the extratropical zone and 0.5◦×0.5◦

in the tropics, and 30 vertical levels (Liu et al., 2012;Lin et al., 2013). The land component is version threeof the Community Land Model (CLM3) (Oleson etal., 2004), and the ice component is version five of theCommunity Sea Ice Model (CSIM5) (Collins et al.,2006). All four components are coupled by a flux cou-pler module from the National Center for AtmosphericResearch (NCAR) (Collins et al., 2006). A more de-tailed model description and an evaluation of its basicperformance can be found in Bao et al. (2013). In thisstudy, we focus on the ENSO–monsoon relationship.To obtain a large sample size of ENSO events, a 500-year pre-industrial run is used. The run started froma steady ocean state and is a fully free-coupled inte-gration without any external forcing. To reduce thepossible impacts of unsteadiness in the early stages ofintegration, we only analyze the outputs from the last400 years.

2.2 Observational datasets

Observational and reanalysis datasets used toevaluate the model include: (1) precipitation datafrom the Global Precipitation Climatology Project(GPCP) (Adler et al., 2003); (2) SST data from theMet Office Hadley Center’s sea ice and SST dataset(HadISST) (Rayner et al., 2003); and (3) atmo-spheric circulation from the National Centers for En-vironment Prediction–Department of Energy Atmo-spheric Model Intercomparison Project II Reanalysis(NCEP2) (Kanamitsu et al., 2002). All the data coverthe period 1979–2008. The anomalies are calculated

NO. 3 WU AND ZHOU 715

from the 1979–2008 base period in the following anal-ysis.

2.3 Methods

To objectively select ENSO events, we define anENSO index for the model based on the followingsteps. First, an EOF analysis is applied to the SST inthe entire tropical Pacific (10◦N–10◦S, 120◦E–70◦W)for all 400 years of data. A spatial pattern and a cor-responding principal component (PC) are obtained.The zone in the tropical eastern Pacific with the maxi-mum SSTA is selected as the zone to define the ENSOindex. Thus, the area-averaged SSTA in the region(5◦N–5◦S, 160◦–110◦W) is defined as the ENSO in-dex for FGOALS-s2. Next, monthly standard devi-ations of the obtained PC are calculated. It is foundthat five months from September to January (SONDJ)have larger standard deviations than other months.The standard deviation of the SONDJ-mean ENSO in-dex is calculated. Sixty-five years (65 years) with theSONDJ-mean ENSO index larger than 1 standard de-viation (less than −1 standard deviation) are selectedas strong El Nino (La Nina) and referred to as year(0). The following year is referred to as year (1). Simi-larly, we define an Indian Ocean dipole (IOD) index forFGOALS-s as the difference of the SSTA between thewestern (10◦S–10◦N, 45◦–65◦E) and eastern (10◦S–0◦,85◦–105◦E) Indian Ocean.

The Nino3.4 (5◦S–5◦N, 120◦–170◦W) index istaken as the ENSO index for the observation. Fivetypical strong El Nino events (1982, 1991, 1994, 1997and 2002) and five strong La Nina events (1984, 1988,1998, 1999, 2007) are selected. Following the conven-tional definition, the IOD index is defined as the dif-ference of the SSTA between the western (10◦S–10◦N,50◦–70◦E) and eastern (10◦S–0◦, 90◦–110◦E) IndianOcean.

Composite analysis is applied to both the El Ninoand La Nina events, and only composite results areshown. Statistical significance tests for the compositeanalysis are performed using the two-tailed Student’st-test.

3. Results

3.1 Phase locking of ENSO

The temporal evolutions of the composite El Ninoand La Nina are shown in Fig. 1. Though improvedrelative to the previous version, FGOALS-s2 still hassome discrepancies in the simulations of ENSO evolu-tions. In the developing phase, the simulated El Ninoand La Nina develop faster than in the observation,and reach peak phase about three months earlier. Forthe decay phase, the fast damping rate of the simu-

Fig. 1. (a) Temporal evolutions of the composite El Ninoindices in the observation (solid line) and FGOALS-s2(dashed line). (b) As in (a), but for the La Nina com-posite.

lated El Nino is close to that in the observation, whilethe long persistence of the composite La Nina is notreproduced by the model.

Although simulated El Nino has some biases interms of its evolution, its impacts on the mon-soon are analyzed and compared with observationsin the following subsections, based on the fact thatthe magnitudes of the simulated warm SSTA inthe equatorial central-eastern Pacific are reasonablein the three monsoon seasons: June–August (0)[JJA(0)]; December(0)–February(1) [D(0)JF(1)]; andJune–August (1) [JJA(1)]. The model’s performancein simulating the asymmetry between El Nino and LaNina in D(0)JF(1) is also evaluated. For simplicity,we refer to JJA(0), D(0)JF(1) and JJA(1) as ENSOdeveloping summer, mature winter and decaying sum-mer for both the observation and the model, thoughthey are not exact for the latter.

3.2 El Nino developing summer

For the observational composite El Nino, the warmSSTA has established in the equatorial central-easternPacific in JJA(0) (Fig. 2a). It enhances local convec-tion and thus stimulates an anomalous cyclonic cou-plet to its west (Fig. 3a). The anomalous cyclone inthe NH extends further westward and is stronger thanthe southern counterpart, partly due to the climatolog-ical easterly vertical shear over the WNP(Wang et al.,2003). The anomalous cyclone in the WNP enhances


Fig. 2. Composites of SST (shading, units: K) and 200-hPa velocity potential (contour, units: 106 m2 s−1) dur-ing El Nino developing summer (JJA mean) in the ob-servation. (b) As in (a), but for FGOALS-s2. For SST,only values at the 10% significance level are shown.

the convection in situ and intensifies the WNP summermonsoon (Wu et al., 2009a).

The cold SSTA in the southeastern tropical IndianOcean, which is the early stage of an Indian Oceandipole, suppresses local convection (Figs. 2a and 3a).The negative precipitation anomalies over the south-eastern tropical Indian Ocean together with the posi-tive precipitation anomalies over the WNP form a Gillasymmetric mode, characterized by cross-equatorialwind anomalies blowing from the southeastern trop-ical Indian Ocean to the WNP (Gill, 1980; Li et al.,2006; Wu et al., 2009c). The whole structure is re-ferred to as the Philippine-Sumatra pattern, and thepattern is maintained through a series feedback pro-cesses (Wu et al., 2009c). To the west of the Suma-tra, the anomalous southeasterly would strengthen thelocal cold SSTA through enhancing coastal upwellingand upward latent heat flux. The cold SSTA wouldsuppress local convection and thus amplify the south-ern branch of the Philippine-Sumatra pattern. For thenorthern branch, the southwesterly anomalies greatlyenhance upward latent heat flux in the WNP, sinceit is in the same direction as the climatological sur-face wind (Li et al., 2006; Wu et al., 2009c; Wu etal., 2010b). The positive latent heat flux anomaliesdominate the net heat flux anomalies coming into theatmosphere. It warms the atmosphere over the WNPand thus enhances the convection and associated pre-cipitation there (Chou et al., 2009). Meanwhile, theenhanced evaporation also cools the local SST simul-

Fig. 3. (a) Composites of precipitation anomalies (units:mm d−1) during El Nino developing summer (JJA mean)in the observation. The contour values for the precipita-tion anomalies are ±0.5, ±1.5, ±2.5 and ±4. (b) Same as(a), but for 850-hPa wind (units: m s−1) anomalies. (c,d) As in (a, b), but for FGOALS-s2. Shading denotes the10% significance level for precipitation (a, c) and zonalwind (b, d).

taneously (Chou et al., 2009; Wu et al., 2009c).For FGOALS-s2, the El Nino-related warm SSTA

in the equatorial central-eastern Pacific is muchstronger than that in the observation (Fig. 2). Corre-spondingly, the stimulated anomalous positive precip-itation is also stronger, but since its maximum centeris shifted eastward, the strength of the anomalous cy-clonic couplet over the equatorial central-eastern Pa-cific is comparable with the observation (Fig. 3).

For the warm pool region, FGOALS-s2 reproducesthe Philippine–Sumatra pattern, with the positive pre-cipitation anomalies in the WNP, the negative pre-cipitation anomalies in the southern Indian Ocean,and the northward cross-equatorial wind anomalies(Fig. 3b). However, there are some minor differences to


the observation. The positive precipitation anomaliesover the WNP are shifted poleward and extend fur-ther westward relative to the observation. The neg-ative precipitation anomalies are not constrained tothe maritime continent and the southeastern tropicalIndian Ocean, but instead extend westward and east-ward. Its center in the tropical Indian Ocean is shiftedwestward by about 20◦. Meanwhile, unrealistic neg-ative precipitation anomalies are simulated over theSouth Pacific convergence zone (SPCZ).

The biases of the negative precipitation anomaliesare associated with the false simulation of the rela-tionship between IOD and strong El Nino. The rateof concurrence of IOD and strong El Nino events arecounted. For an El Nino event, if the JJA(0) IOD in-dex is less than −0.6 standard deviation, we considerthat the El Nino event occurs along with the IOD. Inthe observation, the rate of the concurrence is 80%(4/5), while in the simulation it is about 17% (11/65).The results indicate that the IOD generally does notoccur along with ENSO in the run. In the observation,the establishment of the IOD is associated with a se-ries of positive air–sea interactions. The cold SSTAto the west of Sumatra suppresses local convectionand thus stimulates an anomalous anticyclone overthe southern tropical Indian Ocean. The southeasterlyanomalies to the northeastern flank of the anomalousanticyclone further intensify the cold SSTA throughenhanced coastal upwelling, surface evaporation andocean vertical mixing (Li et al., 2003). Owing to theloss of the IOD-related air-sea coupling processes inthe southeastern tropical Indian Ocean, the negativeprecipitation anomalies in the warm pool region arecompletely determined by the descending branch ofthe anomalous Walker circulation driven by the warmSSTA in the equatorial central-eastern Pacific. In theobservation, the anomalous descending branch is pri-marily seen in the WNP and tropical eastern IndianOcean, with the center located to the south of themaritime continent (Fig. 2a), while that simulated byFGOALS-s2 is much weaker and expands to a largerarea, and its center is shifted westward, consistentwith the location of the anomalous precipitation center(Figs. 2b and 3b). The failure of the model in simulat-ing the air-sea positive feedback in the tropical IndianOcean should be an important reason for the modelbiases in the WNP.3.3 El Nino and La Nina mature winters and

their asymmetryIn the observation, the WNP is dominated by an

anomalous low-level anticyclone (WNPAC) during ElNino mature winter (Fig. 4a) (Zhang et al., 1996; Wanget al., 2000). The WNPAC, a Rossby-wave response tolocal negative precipitation anomalies, is coupled with

an underlying cold SSTA through wind-evaporation-SST feedback (Figs. 4a and 5a) (Wang et al., 2003).The positive feedback plays an important role in themaintenance of the WNPAC until the onset of theWNP summer monsoon. The WNPAC is a criticalbridge linking El Nino and the East Asian winter mon-soon. The southwesterly anomalies to the northwest-ern flank of the WNPAC transport more moisturepoleward and enhance the precipitation over south-eastern China (Zhang et al., 1996). Meanwhile, theeasterly anomalies to the southern flank of the WN-PAC would stimulate equatorial Kelvin waves thatpropagate eastward and tend to accelerate the decayof the warm SSTA in the equatorial central-easternPacific (Wang et al., 2001).

FGOALS-s2 reproduces the WNPAC and the as-sociated negative precipitation anomalies over south-eastern China, though the center of the WNPAC issomewhat shifted northward relative to that in theobservation (Fig. 4c). The positional bias is causedby the false westward extension of the positive SSTAand precipitation anomalies (Figs. 4c and 5c), which isa common problem for most CGCMs (e.g. Collins etal., 2001; Furevik et al., 2003; Zhou et al., 2008).

Previous studies have found that during the LaNina winter, the low-level anomalous cyclone in theWNP (WNPC) is asymmetric about the WNPAC dur-ing El Nino winter (Wu et al., 2010b). Comparedwith the WNPAC, the WNPC is shifted westwardabout 20◦, and is much weaker (Fig. 4b). Correspond-ingly, the westerly anomalies to the southern flankof the WNPC contract westward relative to the east-erly anomalies during El Nino. Meanwhile, there areno significant precipitation anomalies in southeasternChina (Fig. 4b). The asymmetry is associated withthe following two reasons (Wu et al., 2010b). Firstly,the negative precipitation anomalies over the equato-rial central-eastern Pacific associated with La Nina areshifted westward relative to the positive precipitationanomalies associated with El Nino. Correspondingly,the anticyclonic couplet driven by the negative pre-cipitation anomalies is shifted westward and furtherpushes the WNPC westward (Fig. 4b). The asymme-try of the ENSO-related remote forcing is also demon-strated by the asymmetry of anomalous Walker circu-lation (Fig. 5b). Secondly, the positive SSTA in theWNP associated with La Nina is much weaker thanthe cold SSTA associated with El Nino (Figs. 5a, b).The weaker warm SSTA does not favor the develop-ment of the positive precipitation anomalies and theWNPC. The asymmetry of the SSTA in the WNP re-sults from preceding complicated air–sea interactionsin the warm pool region (Wu et al., 2010b).

The asymmetry of the WNP circulation anomalies


Fig. 4. Left panel: (a) Composites of precipitation (shading, units: mm d−1) and 850-hPa wind (vector,units: m s−1) anomalies during El Nino mature winter (DJF mean) in the observation. (b) As in (a), butfor La Nina. Right panel: As in the left panel, but for FGOALS-s2. For precipitation, only values at the10% significance level are shown.

Fig. 5. As in Fig. 4, but for SST (shading, units: K) and 200-hPa velocity potential (contour, units: 106

m2 s−1) anomalies. For SST, only values at the 10% significance level are shown.


simulated by FGOALS-s2 is not as significant as thatin the observation (Figs. 4c and d). Considering thatthe asymmetry of the precipitation and SST anoma-lies over the equatorial central-eastern Pacific is repro-duced by FGOALS-s2, the bias should be primarilycaused by the failure in the simulation of the asymme-try of the SSTA in the WNP (Figs. 4c, d and 5c, d).It is seen that the cold SSTA in the WNP associatedwith El Nino is even weaker than the warm SSTA asso-ciated with La Nina. Wu et al. (2010b) found that theasymmetry of the SSTA originates from the asymmet-ric SSTA tendencies during the preceding ENSO devel-oping summer. Although both the precipitation andsurface wind anomalies are approximately symmet-ric, the surface latent heat flux anomalies are highlyasymmetric over the key WNP region, owing to thenonlinear relationship between wind speed anomaliesand zonal wind anomalies. FGOALS-s2 fails to simu-late the asymmetry of the latent heat flux anomaliesover the WNP because of the biases of the backgroundmean wind and wind anomalies (figure not shown). Asa result, the model fails to simulate the asymmetry ofSSTA tendency in the WNP during the ENSO devel-oping summer.

Corresponding to the weaker asymmetry in theWNP, the asymmetry of the descending branch ofthe anomalous Walker circulation is also unclear inFGOALS-s2 (Figs. 5c and d), implying that the large-scale anomalous Walker circulation associated withENSO is also modulated by the air-sea interactionsin the warm pool region.

The model bias in simulating the asymmetry of theWNP circulation anomalies between El Nino and LaNina reduces the model skill in the simulations of theEast Asian winter monsoon variability and ENSO evo-lution. In the observation, southeastern China doesnot have significant precipitation anomalies during LaNina mature winter (Fig. 4b), while FGOALS-s2 simu-lates unrealistic negative precipitation anomalies overthis region (Fig. 4d), generally asymmetric about thepositive precipitation anomalies during El Nino winter(Fig. 4c).

The easterly anomalies to the southern flank of theWNPAC tend to stimulate upwelling Kelvin waves,which would accelerate the decay of El Nino. Owingto the spatial shift of the WNPC, the westerly anoma-lies over the equatorial western Pacific are very weakin the observation. The asymmetry of the zonal windanomalies over the equatorial western Pacific tends tocause La Nina to decay slower than El Nino (Fig. 1).FGOALS-s2 does not reproduce the asymmetry of thezonal wind anomalies over the equatorial western Pa-cific (Figs. 4c and d). The discrepancy can partiallyexplain why the model fails to simulate the asymmet-

ric decaying rate between El Nino and La Nina (Fig. 1)

3.4 El Nino decaying summer

In the observation, the WNPAC maintainsthroughout the El Nino decaying summer (Figs. 6d–f). It corresponds to the westward extension of thewestern Pacific subtropical high and has a large im-pact on the precipitation over East Asia (Chang etal., 2000). From June to August, the positive precip-itation anomalies to the north flank of the WNPACmarch northward (Figs. 6a–c), which is associated withthe northward movement of the climatological upper-tropospheric westerly jet (Ye and Lu, 2011). Differentfrom the preceding winter and spring, the maintenanceof the WNPAC during El Nino decaying summer relieson two distinct mechanisms.

During early summer (June), before the onset ofthe WNP summer monsoon trough, the WNPAC ismaintained by an underlying cold SSTA (Fig. 7a),which persists from the preceding winter and spring.However, the cold SSTA is gradually damped by neg-ative feedback; that is, the upward latent heat fluxis weakened by the surface wind anomalies associatedwith the WNPAC and downward surface shortwaveradiation is enhanced by the negative precipitationanomalies (Wu et al., 2010a). In late summer, thecold SSTA in the WNP is completely replaced by thewarm SSTA (Fig. 7c).

During late summer (July and August), the WN-PAC is maintained by remote forcing from the tropicalIndian Ocean (Figs. 7b and c) (Yang et al., 2007; Li etal., 2008; Wu et al., 2009a; Xie et al., 2009; Wu et al.,2010a; Huang et al., 2010). The Indian Ocean basin-wide warming enhances local convection, which stimu-lates atmospheric Kelvin waves to propagate eastward.The atmospheric Kelvin waves cause negative vortic-ity anomalies over the off-equatorial WNP. The neg-ative voriticity anomalies further drive the boundarylayer divergence over the WNP through Ekman pump-ing. However, the boundary layer divergence does notnecessarily suppress the precipitation anomalies. Itis after the establishment of the background monsoontrough in July (Fig. 8b) that the anomalous boundarylayer divergence over the WNP suppresses the precip-itation by decreasing the moisture supply. The nega-tive precipitation anomalies maintain the WNPAC toits west. Owing to the dependence on the backgroundWNP monsoon trough, the contribution of the IndianOcean basin-wide warming to the WNPAC becomesprominent in late summer (Wu et al., 2010a).

It is worth noting that although the WNPAC main-tains throughout summer, its largest impacts on theEast Asian summer monsoon are in June, since thestrongest Meiyu rainfall, which is remarkably modula-


Fig. 6. Composites of precipitation (left panel, units: mm d−1) and 850-hPa wind anomalies (right panel,units: m s−1) during El Nino decaying summer (from June to August) for the observation. Shading denotesthe 10% significance level for precipitation (left panel) and zonal wind (right panel).

Fig. 7. Left panel: Composites of SST anomalies (shading, units: m s−1) during El Nino decaying summer(from June to August) for the observation. Right panel: As in the left panel, but for FGOALS-s2. Thecontours denote the 10% significance level.


Fig. 8. Left panel: Climatological precipitation (shading, units: mm d−1) and 850-hPa wind(vector, units: m s−1) from June to August in the observation. Right panel: As in the leftpanel, but for FGOALS-s2.

ted by the WNP subtropical high, occurs in this month(Wu et al., 2010a).

Owing to the critical role of the background meanstate, we first compare the simulated climatological850-hPa wind and precipitation from June to Augustwith the observation (Fig. 8). FGOALS-s2 reproducesthe gradual establishment and northeastward exten-sion of the WNP monsoon trough, and the northwardmovement of the WNP monsoon rainfall. However, forthe East Asian summer monsoon, the model skill isrelatively low. The simulated Meiyu rain belt is muchweaker than in the observation, while the southerly

component over South China is much stronger.Based on the evaluation of the model climatology,

we further explore model performance in simulatingthe WNPAC as well as the related SSTA and precip-itation anomalies. It is consistent with the observa-tion that the simulated WNPAC maintains from Juneto August (Figs. 9d–f). Meanwhile, FGOALS-s2 re-produces the feature of the cold SSTA in the WNPgradually decaying and evolving to a warm SSTA fromJune to July (Figs. 7d–e). However, model discrepan-cies are also clear. The simulated Indian Ocean basin-wide warming does not maintain throughout the sum-


mer, instead evolving to a dipole pattern in August(Fig. 7f). The decayed basin mode cannot drive power-ful precipitation anomalies as it does in the observation(Fig. 9f). Owing to the WNPAC being maintained inlate summer by remote forcing from the Indian Oceanbasin-wide warming (Wu et al., 2010a), the discrep-ancy of the model in the tropical Indian Ocean causesthe simulated WNPAC in August to be much weakerthan in the observation (Figs. 6f and 9f).

Though the WNPAC is reproduced in June, thecorresponding anomalies of the Meiyu rain belt are farweaker than those in the observation (Figs. 6a and 9a),suggesting substantial impacts of the model climatol-ogy on the ability to simulate the variability. Further-more, the model fails to simulate the northward shiftof the positive precipitation anomalies to the northernflank of the WNPAC from June to August (Figs. 9a–c).

4. Conclusions

The performance of FGOALS-s2 in the simulationof the relationship between ENSO and EA-WNP mon-soon has been systematically evaluated. The El Nino

evolution simulated by the model is analogous to thatin the observation, though it reaches mature phasesomewhat earlier. Based on simulated El Nino evolu-tion, we have assessed the simulated variability of theEA–WNP monsoon during El Nino developing sum-mer, mature winter and decaying summer. Meanwhile,we have also referred to the asymmetry of the winter-time WNP circulation anomalies between El Nino andLa Nina. The major conclusions can be summarizedas follows.

(1) FGOALS-s2 reproduces the anomalous cycloneover the WNP and the enhanced WNP monsoon pre-cipitation during El Nino developing summer. In theobservation, the positive precipitation anomalies overthe WNP are tightly linked to the negative precipita-tion anomalies over the southeastern tropical IndianOcean. They form a Gill pattern asymmetric aboutthe equator. Though the Gill pattern is simulated, itssouthern branch has a large bias. The bias is associ-ated with the underestimation of the occurrence fre-quency of ENSO accompanied by the IOD. The bias ofthe southern branch has passive effects on the precip-itation and circulation anomalies over the WNP mon-

Fig. 9. As in Fig. 6, but FGOALS-s2.


soon region.(2) In El Nino mature winter, the anomalous cy-

clone over the WNP is converted to an anomalousanticyclone (WNPAC). The southwesterly anomaliesto the northwestern flank of the WNPAC transportmore moisture northward and enhance the precipita-tion over southeastern China. During La Nina maturewinter, though an anomalous cyclone (WNPC) is seenover the WNP, it is shifted westward relative to theWNPAC, and is much weaker than the latter. Theasymmetry can explain the asymmetric evolution be-tween El Nino and La Nina; that is, La Nina tends topersist much longer than El Nino. FGOALS-s2 sim-ulates the WNPAC and associated positive precipita-tion anomalies over South China during El Nino win-ter. However, it fails to capture the asymmetry be-tween WNPAC and WNPC and the asymmetric evo-lution between El Nino and La Nina.

(3) In the observation, the WNPAC maintainsthroughout El Nino decaying summer through two dis-tinct mechanisms. In early summer, the WNPAC isdriven by the underlying cold SSTA, while in late sum-mer it relies on remote forcing from the basin-widewarming in the tropical Indian Ocean. The WNPACcauses a belt of positive precipitation anomalies to itsnorthern flank, which is shifted northward from Juneto August, owing to the northward movement of theupper-tropospheric westerly jet. FGOALS-s2 repro-duces the WNPAC throughout the summer and cap-tures the two distinct mechanisms, though some dis-crepancies exist. For example, the basin-wide warmingin the tropical Indian Ocean decays fast and evolvesto a dipole pattern in August. The simulated belt ofpositive precipitation anomalies to the northern flankof the WNPAC is much weaker than observed and isnot shifted northward. This is associated with modelbiases in the mean states.

Acknowledgements. This work was supported by

the Chinese Academy of Sciences Strategic Priority Re-

search Program (Grant No. XDA05110305), the National

Program on Key Basic Research Project (2010CB951904),

the National Natural Science Foundation of China (Grant

Nos. 41005040, 41023002 and 40890054), the National

High-Tech Research and Development Plan of China

(2010AA012302) and the China Meteorological Adminis-

tration (Grant No. GYHY201006019).

REFERENCES

Adler, R. F., and Coauthors, 2003: The version-2global precipitation climatology project 11 (GPCP)monthly precipitation analysis (1979–present). Jour-nal of Hydrometeorology, 4, 1147–1167.

Bao, Q., and Coauthors, 2013: The flexible global ocean-atmosphere-land system model, spctral version 2:FGOALS-s2. Adv. Atmos. Sci., doi: 10.1007/s00376-012-2113-9.

Chang, C. P., Y. S. Zhang, and T. Li, 2000: Interannualand interdecadal variations of the East Asian sum-mer monsoon and tropical Pacific SSTs. Part I: Rolesof the subtropical ridge. J. Climate, 13, 4310–4325.

Chou, C., L.-F. Huang, J.-Y. Tu, L. Tseng, and Y.-C.Hsueh, 2009: El Nino impacts on precipitation in thewestern North Pacific-East Asian sector. J. Climate,22, 2039–2059.

Chowdary, J. S., S.-P. Xie, J.-Y. Lee, Y. Kosaka, and B.Wang, 2010, Predictability of summer northwest Pa-cific climate in 11 coupled model hindcasts: Localand remote forcing. J. Geophys. Res., 115, D22121,doi: 10.1029/2010JD014595.

Collins, M., S. F. B. Tett, and C. Cooper, 2001: Theinternal climate variability of HadCM3, a version ofthe Hadley Centre coupled model without flux ad-justments. Climate Dyn., 17, 61–81.

Collins, W. D., and Coauthors, 2006: The CommunityClimate System Model version 3 (CCSM3). J. Cli-mate, 19, 2122–2143.

Furevik, T., M. Bentsen, H. Drange, I. K. T. Kindem,N. G. Kvamsto, and A. Sorteberg, 2003: Descrip-tion and evaluation of the Bergen climate model:ARPEGE coupled with MICOM. Climate Dyn., 21,27–51.

Gill, A. E., 1980: Some simple solutions for heat-inducedtropical circulation. Quart. J. Roy. Meteor. Soc.,106, 447–462.

Gong, D. Y., and S. W. Wang, 1999: Impacts of ENSOon rainfall of global land and China. Chinese ScienceBulletin.. 44, 852–857.

Huang, R. H., and Y. F. Wu, 1989: The influence ofENSO on the summer climate change in China andits mechanism. Adv. Atoms. Sci., 6, 21–32.

Huang, R., L. Gu, J. Chen, and G. Huang, 2008: Recentprogresses in studies of the temporal-spatial varia-tions of the East Asian monsoon system and theirimpacts on climate anomalies in China. Chinese J.Atmos. Sci., 32, 691–719. (in Chinese)

Huang, G., K. Hu, and S.-P. Xie, 2010: Strengthening oftropical indian ocean teleconnection to the northwestPacific since the mid-1970s: An atmospheric GCMstudy. J. Climate, 23, 5294–5304.

Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J.J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP-DOE AMIP-II reanalysis (R-2). Bull. Amer. Meteor.Soc., 83, 1631–1643.

Klein, S. A., B. J. Soden, and N. C. Lau, 1999: Remotesea surface temperature variations during ENSO: Ev-idence for a tropical atmospheric bridge. J. Climate,12, 917–932.

Kug, J. S., B. P. Kirtman, and I. S. Kug, 2006: Interac-tive feedback between ENSO and Indian Ocean in aninteractive ensemble coupled model. J. Climate, 19,6371–6381.


Lau, N.-C., and M. J. Nath, 2000: Impact of ENSO on thevariability of the Asian-Australian monsoons as sim-ulated in GCM experiments. J. Climate, 13, 4287–4309.

Lau, N.-C., and M. J. Nath, 2003: Atmosphere-oceanvariations in the Indo-Pacific sector during ENSOepisodes. J. Climate, 16, 3–20.

Lau, N.-C., and B. Wang, 2006: Interactions be-tween Asian monsoon and the El Nino-SouthernOscillation. The Asian Monsoon, B. Wang, Ed.,Springer/Praxis Publishing, New York, 478–512.

Lee, S.-S., J.-Y. Lee, K.-J. Ha, B. Wang, and J. Schemm,2011: Deficiencies and possibilities for long-lead cou-pled climate prediction of the Western North Pacific-East Asian summer monsoon. Climate Dyn., 36,1173–1188.

Li. C., 1990: Interaction between anomalous winter mon-soon in East Asian and El Nino event. Adv. Atmos.Sci., 7, 36–46.

Li, S. L., J. Lu, G. Huang, and K. M. Hu, 2008: TropicalIndian Ocean basin warming and East Asian summermonsoon: A multiple AGCM study. J. Climate, 21,6080–6088.

Li, T., B. Wang, C. P. Chang, and Y. S. Zhang, 2003:A theory for the Indian Ocean dipole-zonal mode. J.Atmos. Sci., 60, 2119–2135.

Li, T., P. Liu, X. Fu, B. Wang, and G. A. Meehl, 2006:Spatiotemporal structures and mechanisms of thetropospheric biennial oscillation in the Indo-Pacificwarm ocean regions. J. Climate, 19, 3070–3087.

Lin, P. F., Y. Q. Yu, and H. L. Liu, 2013: Long-termstability and oceanic mean state simulated by thecoupled model FGOALS-s2. Adv. Atmos. Sci., 30(1),doi: 10.1007/s00376-012-2042-7.

Liu, H., P. Lin, Y. Yu, and X. Zhang, 2012: Thebaseline evaluation of LASG/IAP Climate systemOcean Model (LICOM) version 2.0. Acta Meteoro-logica Sinica., 26, 318–329.

Lu, R., 2005: Interannual variation of North China rain-fall in rainy season and SSTs in the equatorial easternPacific. Chinese Science Bulletin, 50, 2069–2073.

Oleson, K. W., and Coauthors, 2004: Technical descrip-tion of the Community Land Model (CLM), NCARTechnical Note, NCAR/TN-461+STR, 173pp.

Qu, X., and G. Huang, 2012: Impacts of tropical IndianOcean SST on the meridional displacement of EastAsian jet in boreal summer. Int. J. Climatol., 23,2073–2080.

Rasmusson, E. M., and T. H. Carpenter, 1982: Varia-tions in tropical sea surface temperature and sur-face wind fields associated with the Southern Oscil-lation/El Nino. Mon. Wea. Rev., 110, 554–584.

Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland,L. V. Alexander, D. P. Rowell, E. C. Kent, and A.Kaplan, 2003: Global analyses of sea surface tem-perature, sea ice, and night marine air temperaturesince the late nineteenth century. J. Geophys. Res.,108, 4407, doi: 10.1029/2002JD002670.

Terao, T., and T. Kubota, 2005: East-west SST contrast

over the tropical oceans and the post El Nino west-ern North Pacific summer monsoon. Geophys. Res.Lett., 32, l15706, doi: 10. 1029/2005GL023010.

Wang, B., and T. Li, 2004: East Asian monsoonand ENSO interaction, East Asian Monsoon. C.-P.Chang, Eds., World Scientific Publishing Company,Singapore, 172–212.

Wang, B., R. G. Wu, and X. H. Fu, 2000: Pacific-EastAsian teleconnection: How does ENSO affect EastAsian climate? J. Climate, 13, 1517–1536.

Wang, B., R. G. Wu, R. Lukas, and S. I. An, 2001: Apossible mechanism for ENSO turnabout. Dynam-ics of Atmospheric General Circulation and Climate,IAP/Academia Sinica, Ed., China MeteorologicalPress, 552–578.

Wang, B., R. G. Wu, and T. Li, 2003: Atmosphere-warm ocean interaction and its impacts on Asian-Australian monsoon variation. J. Climate, 16, 1195–1211.

Wu, B., T. Zhou, and T. Li, 2009a: Seasonally evolv-ing dominant interannual variability modes of EastAsian climate. J. Climate, 22, 2992–3005.

Wu, B., T. Zhou, T. Li, and Q. Bao, 2009b: Interan-nual variability of the Asian-Australian monsoon andENSO simulated by an ocean-atmosphere coupledmodel. Chinese J. Atmos. Sci., 33, 285–299. (in Chi-nese)

Wu, B., T. Zhou, and T. Li, 2009c: Contrast of rainfall-SST relationships in the western North Pacific be-tween the ENSO-developing and ENSO-decayingsummers. J. Climate, 22, 4398–4405.

Wu, B., T. Li, and T. Zhou, 2010a: Relative contributionsof the Indian Ocean and local SST anomalies to themaintenance of the western North Pacific anomalousanticyclone during El Nino decaying summer. J. Cli-mate, 23, 2974–2986.

Wu, B., T. Li, and T. Zhou, 2010b: Asymmetry of atmo-spheric circulation anomalies over the western NorthPacific between El Nino and La Nina. J. Climate, 23,4807–4822.

Wu, G., and W. Meng, 1998: Gearing between the Indo-monsoon circulation and the Pacific-Walker circula-tion and the ENSO. Part I: data analysis. Chinese J.Atmos. Sci., 22, 470–480. (in Chinese)

Wu, R. G., Z. Z. Hu, and B. P. Kirtman, 2003: Evolutionof ENSO-related rainfall anomalies in East Asia. J.Climate, 16, 3742–3758.

Xie, S. P., H. Annamalai, F. A. Schott, and J. P. Mc-Creary, 2002: Structure and mechanisms of South In-dian Ocean climate variability. J. Climate, 15, 864–878.

Xie, S.-P., K. Hu, J. Hafner, H. Tokinaga, Y. Du, G.Huang, and T. Sampe, 2009: Indian Ocean capaci-tor effect on Indo-western Pacific climate during thesummer following El Nino. J. Climate, 22, 730–747.

Yang, J. L., Q. Y. Liu, S. P. Xie, Z. Y. Liu, and L. X. Wu,2007: Impact of the Indian Ocean SST basin modeon the Asian summer monsoon. Geophys. Res. Lett.,34, L02708, doi: 10.1029/2006GL028571.


Ye, H., and R. Lu, 2011: Subseasonal variation in ENSO-related East Asian rainfall anomalies during summerand its role in weakening the relationship between theENSO and summer rainfall in eastern China since theLate 1970s. J. Climate, 24, 2271–2284.

Zhang, R. H., A. Sumi, and M. Kimoto, 1996: Impactof El Nino on the East Asian monsoon: A diagnos-tic study of the ’86/87 and ’91/92 events. J. Meteor.

Soc. Japan, 74, 49–62.Zhang, R. H., A. Sumi, and M. Kimoto, 1999: A diagnos-

tic study of the impact of El Nino on the precipitationin China. Adv. Atmos. Sci., 16, 229–241.

Zhou, T., B. Wu, X. Wen, L. Li and B. Wang, 2008: Afast version of LASG/IAP climate system model andits 1000-year control integration. Adv. Atmos. Sci.,25, 655–672, doi: 10.1007/s00376-008-0655-7.

relationships between the east asian-western north pacific monsoon and enso simulated by fgoals-s2

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