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Present and Future of Modeling Global Environmental Change: Toward Integrated Modeling,Eds., T. Matsuno and H. Kida, pp. 49–62.© by TERRAPUB, 2001.

Studies of Climate Variability Using General Circulation Models

Masahide Kimoto

Center for Climate System Research, University of Tokyo,Meguro, Tokyo 153-8904, Japan

Abstract—Some studies on interannual to decadal climate variability usingatmospheric and coupled ocean-atmosphere general circulation models (GCMs)developed at the Center for Climate System Research, University of Tokyo, areintroduced.

The AGCM has been used for numerical experiments to quantify the roleof land-surface feedback in the interannual variability of the Indian Monsoonand remote impacts of sea surface temperature anomalies in the Indian andequatorial eastern Pacific Oceans on an anomalous East Asian summer monsoon.

A coupled upper-ocean-atmosphere GCM has been used to investigatecoupled interannual and decadal variability in the tropical Pacific andextratropical Pacific and Atlantic Oceans. The coupled model shows decadal,quasi-quadrennial, and quasi-biennial sea surface temperature variability inthe Pacific basin. Active involvement of extratropical-subtropical winds andocean heat content in the simulated decadal mode is conspicuous. The coupledGCM also exhibits a decadal ocean-atmosphere mode over the North Atlantic.An experiment using a coupled atmosphere-mixed-layer ocean model revealsthat a positive feedback exists in the North Atlantic atmosphere-ocean system.

INTRODUCTION

General circulation models (GCMs) of the atmosphere and oceans serve as apowerful tool for studying the global climate and its variability. They have beenunder continuous development since the pioneering age of the 1960s. Though farfrom perfect, carefully validated GCMs offer us a valuable opportunity toconduct experiments on the global climate.

The Center for Climate System Research (CCSR) of the University of Tokyoworks on the development of global climate models. In this article, some of thestudies on interannual to decadal climate variability using atmospheric andcoupled ocean-atmosphere general circulation models are introduced.

MODELS

The atmospheric GCM (AGCM) has been developed cooperatively byCCSR and the National Institute for Environmental Studies (NIES) and is calledthe CCSR/NIES AGCM. It is a global spectral model with sigma verticalcoordinate and includes full physics.

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A two-stream k-distribution radiation transfer code developed by Nakajimaet al. (2000) is incorporated in the AGCM. It enables efficient computation of theeffects of trace gases and aerosols as evidenced by the global warming study ofNozawa et al. (2001). Other physical processes included are: a simplifiedArakawa-Schubert (1974) scheme for cumulus convection, the Le Treut and Li(1991) prognostic cloud water scheme, the McFarlane (1987) orographic gravitywave drag (GWD), the Mellor-Yamada (1974) level 2.0 turbulence closurescheme, a bulk scheme for surface fluxes (Louis, 1979; Uno et al., 1995), a multi-layer land surface energy budget treatment, a bucket ground hydrology, and ariver runoff routine model. Details of the AGCM can be found in Numaguti et al.(1997).

A new version of the AGCM currently under development includes a newland-surface model, the Kim-Arakawa GWD scheme, an optional flux-formsemi-Lagrangian advection scheme for tracers, a non-local turbulent mixingscheme, direct and indirect effects of aerosols, a better tuned large-scale andconvective cloud models, etc.

The ocean general circulation model employs Boussinesq and rigid-lidapproximations. In some studies introduced in the following, simplified forms ofthe ocean part are used.

Fig. 1. (a) Time series of June–July–August mean anomalies of the Webster-Yang (1992) broad-scale monsoon index between the years 1979 and 1988. The AGCM result is compared withECMWF and NCEP data. The index is defined as the zonal wind shear between 850 and 200 hPalevels averaged over 40°E–110°E, 5°N–20°N region. (b) Anomalies of March–April–May soilwetness averaged over 3 simulated weak monsoon years. The contour interval is 0.005 with zerolines suppressed. Shaded areas represent regions where the difference between weak and strongmonsoon years is larger than the interannual standard deviation. The unit of soil wetness ism m–1. (c) Anomalies of the broad-scale monsoon index for the composite weak and strongmonsoons in the control integration (soild lines) and the ensemble results (dashed) of theexperiment where the land surface initial conditions are changed. The unit of monsoon index ism s–1.

Studies of Climate Variability Using General Circulation Models 51

MONSOON VARIABILITY

The Asian monsoon system exhibits considerable year-to-year variabilitythat affects significantly the life and economy of the inhabitants. The AGCM hasbeen used to study the interannual variability of the Indian and East Asianmonsoon systems.

Role of land-surface feedback in the interannual variability of Indian monsoons

A statistical correlation between Indian monsoon rainfall and Eurasian snowcover of earlier seasons, originally pointed out by Blanford (1884), was revisitedby Hahn and Shukla (1976) which called much attention to the role of land surfaceprocesses in the interannual variability of Indian monsoons. Some earlier GCMstudies showed a positive impact, but sometimes the experimental setup suffered

Fig. 1. (continued).

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from arbitrariness in specifying anomalous land surface parameters due to thelack of observational information.

Interannual variability in the Indian summer monsoon and related land-surface processes over the Eurasian continent has been investigated by Shen et al.(1998) in a ten-year integration of the CCSR/NIES AGCM. A version withtriangular 21 truncation and 20 vertical levels (T21L20) was integrated with1979–1988 observed sea surface temperatures (SSTs) as a bottom boundarycondition. It is found that the simulated interannual variability in the broad-scalesummer monsoon during this decade shows good correlation with observations(Fig. 1a). Furthermore, distinct precursory signals over the Eurasian landmasshave been found in the simulation; excessive snow and increased soil moistureover Eurasia south of 50°N in the pre-monsoon winter and spring are followed byweaker than normal monsoons (Fig. 1b) and vice versa. More snow and wetground conditions tend to suppress the monsoon development keeping the landsurface cool. Thus, the model results support an active role of land surfaceprocesses in the monsoon variability. However, the 1979–1988 decade was alsocharacterized by a conspicuous swing in the El Niño–Southern Oscillation(ENSO) in the equatorial Pacific, which is known statistically to have a relationto the strength of Indian monsoon.

In order to assess the role of land surface processes more quantitatively, anumerical experiment has been carried out by exchanging the spring-timeEurasian land surface conditions between weak and strong monsoon years whilekeeping the atmospheric initial conditions the same as the control integration(Shen et al., 1998). Note that the initial land conditions were sampled out of themodel’s natural variability avoiding arbitrary specification. This experimentshows that the land surface feedback does contribute to the simulated interannualvariability but is not strong enough to change the sign of the monsoon circulationanomalies (Fig. 1c). It appears that the influence of the ENSO-related SSTanomalies plays a more important role in influencing the simulated monsoon.

The subtropical western Pacific anticyclone and the East Asian summer monsoon

The East Asian countries experienced an extremely wet summer in 1998.More than 150% of the normal rainfall has been observed over a large portion ofEast Asia extending from southern China, and the Korean peninsula to Japan. Arecord-breaking flood occurred over the Changjiang River basin of China andlasted for almost three months. Heavy rainfalls hit the northern and eastern Japanand the Korean peninsula in July and August.

In 1998 summer, the strong 1997/98 El Niño was decaying and a new La Niñawas developing. Concurrently, a warm event similar to that in the Pacific basinoccurred in the Indian Ocean starting from June 1997 through 1998 summer(Webster et al., 1999). Sea surface temperature anomalies (SSTAs) near Sumatraexceeded 2°C. A T42L20 version of the CCSR/NIES AGCM has been integratedwith observed SSTAs in order to understand the anomalies of the 1998 East Asiansummer monsoon.


Figure 2a shows the observed anomalies of the June–July–August (JJA)mean precipitation and winds at 850 hPa for 1998. It is found that the mostconspicuous feature of the 850 hPa circulation was the southwestward intrusionof the western Pacific subtropical high. The resultant anomaly pattern of 850 hPawinds exhibited a strong anticyclonic circulation located over a region extendingfrom the South China Sea to the western Pacific. The low-level circulationfunctions to enhance the moisture transportation from the South China Sea andthe western Pacific to the East Asian countries, thereby activating, strengtheningand maintaining the Baiu/Meiyu front that governs the rainy season of East Asia.

Fig. 2. (a) Observed JJA-mean anomalies of precipitation (shadings; mm day–1) and 850 hPa winds(vectors; ms–1). (b) Same as (a), but for the ensemble simulation with global SSTAs.

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Corresponding to the circulation anomalies, precipitation was deficient overthe tropical and subtropical western Pacific and excessive over the East Asianlandmass to its north. In the Pacific Ocean, inactive ITCZ and resultant rainfalldeficiency extended from the tropical western to the eastern Pacific. This,together with the positive rainfall anomalies over the equatorial eastern Pacificand the tropical southeastern Pacific, was likely to be influenced by both the1997/98 El Niño and the developing 1998/99 La Niña conditions. In addition,unprecedented warming near the island of Sumatra appeared in the summermonths of 1998. Accompanied by the SSTA to the southwest of Sumatra,excessive rainfall anomalies were found.

An ensemble experiment consisting of 10 independent integrations of about4 months from 00UTC of April 21, 22, ..., 30 to the end of August was conductedgiving the observed global monthly SST as the lower boundary condition. Figure2b shows the ensemble mean anomalies of the 850 hPa winds and precipitationfor JJA. The main features of the 1998 East Asian summer monsoon are wellreproduced, except for those in the mid-high latitudes. The low-level anticycloniccirculation anomaly over the subtropical western Pacific and South China Sea iscaptured well by the model. This low-level anticyclonic anomaly was importantin transporting a vast amount of moisture from the southern ocean to the EastAsian landmass during the 1998 summer according to the moisture budgetanalysis. Corresponding to this circulation anomaly, the anomaly pattern ofprecipitation simulated by model also shows general similarities to the observation.Deficient precipitation, i.e., suppressed convective activities, over the subtropicalwestern Pacific and equatorial Pacific are captured well, although the sign of theanomalies in a small region over the South China Sea is reversed. Excessiverainfall is found over an oceanic area to the west of Sumatra and over the EastAsian landmass.

In order to clarify which part of the SSTA was most influential in the EastAsian monsoon, additional ensemble integrations have been carried out retainingvarious regional SSTAs (Shen et al., 2001). In summary, two key regions havebeen identified as most efficient in inducing the western Pacific subsidence andassociated low-level anticyclonic anomalies: the southeastern part of IndianOcean (80°E–135°E, 30°S–EQ), and the tropical Pacific Ocean (135°E–75°W,20°S–20°N). Positive SSTAs over these regions enhanced convection aloft andthe remote subsidence over the western Pacific through modifications of Walkerand local Hadley circulations, respectively. The positive SSTA over the formerregion was the remains of the 1997/98 El Niño, while that over the latter was a partof the Indian Ocean Dipole mode (Saji et al., 1999). The experiment indicates thatthe dual effect caused the persistent and strong low-level anticyclonic anomalyin the subtropical western Pacific and thereby was responsible for the anomalous1998 East Asian summer monsoon. Positive SSTAs over the North Indian Oceanand the South China Sea regions tend to enhance convection aloft, but this wasnot supported by observations. SSTAs over these regions may have been forcedby atmospheric anomalies.


COUPLED INTERANNUAL–DECADAL VARIABILITY

In much of the interannual and longer variability, interactions between theatmosphere and oceans should play important roles. Coupled upper-ocean-atmosphere GCMs have been used to investigate interannual and decadal variabilityin the tropical Pacific and extratropical Pacific and Atlantic Oceans.

Interannual to decadal variability in the Pacific basin

A coupled upper-ocean-atmosphere GCM has been integrated for about 100years to investigate interannual to decadal variability in the Pacific basin. Theatmospheric part of the coupled model employs a T21L20 version. The horizontalresolution of the ocean GCM (OGCM; Kimoto et al., 1997) is 2.0° latitude × 2.5°longitude except in the 20°N–20°S equatorial band, where the latitudinal spacingis 0.5° within 10° from the equator and is increased outside to 20° latitudes. TheOGCM has 20 vertical levels, of which 13 lie in the upper 300 meters. Convectiveadjustment and a level 2.5 turbulence closure scheme are used for the verticalmixing. The computational domain is global but excludes the Arctic Ocean. Themodel does not include sea ice, and the SST is relaxed to the observed climatologyin latitudes higher than 50°. Otherwise, the model employs no flux correction.

Starting from the resting isothermal atmosphere and Levitus’ temperatureand salinity profile with no currents in the ocean, the model has been integratedfor a total of 105 years. The first 10 years were discarded and the resultant 96-yearrecord was analyzed.

The SST is one of the key variables in the large-scale ocean-atmospherevariability. Here, the multi-channel singular spectrum analysis (MSSA; Kimotoet al., 1991; Plaut and Vautard, 1994) is used to extract spatio-temporal patternsof the SST variability. The MSSA is an extension of a more conventionalempirical orthogonal function (EOF) analysis. Out of the sequence of anomalymaps, each of which consists of L grid-point values, the ordinary EOF extractsspatial patterns of dominant variability, usually in the order of decreasingassociated variance. An anomaly map of a one-time level is regarded as the vectorof length L to be analyzed. MSSA regards an M-temporally-lagged sequence ofanomaly maps as the vector, of length M × L, to be analyzed. The analyzed modes,therefore, include not only spatial patterns, but also their temporal evolutions.Both EOF and MSSA extract principal patterns of variability as eigenvectors ofa data covariance matrix. As explained by Vautard et al. (1992), SSA can detectan oscillatory mode as a pair with degenerate eigenvalues. They behave asgeneralized sines and cosines in the time domain. Details of SSA or MSSA canbe found in Vautard et al. (1992) and Allen and Robertson (1996).

In order to avoid making the size of the covariance matrix too big, it isconvenient to apply conventional EOF to the SST field to reduce the spatialdimension by truncation. The EOF analysis was first applied to the Pacific basinmonthly SST anomalies between 36°S and 60°N. Retaining the first 27 amountsto accounting for 80.5% of the domain integrated variance in the original field.The temporal length of the maps, or window width, is taken to be 121 months,

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long enough to enable detection of decadal modes. Slight changes in the windowwidth do not affect the results.

Three oscillatory pairs have been detected: a decadal mode (DC) with a 9-year period (MSSA modes 2 and 3; 7.8% of the total variance), a quasi-quadrennial or ENSO mode (QQ) with a 56-month period (modes 4 and 5; 4.9%),and a quasi-biennial mode (QB) with a 24-month period (modes 6 and 7; 4.1%).Figure 3 shows the contributions of these MSSA modes to the power spectrum ofthe 1st (ordinary) EOF, which accounts for 23.3% of variance and is wellseparated from the following mode with only 6.9%. The shaded spectra indicatethe contributions by the MSSA modes (cf. Vautard et al., 1992). The QQ and QBmodes have also been identified in observational analyses of equatorial SSTA byJiang et al. (1995) and of the Pacific basin SSTA similar to the present study byZhang et al. (1998). The periodicity of the DC mode does not correspond exactlyto the observation, which is not very well-defined, but is generally thought to belonger (e.g., Zhang et al., 1998). However, the spatial pattern of SSTA of the DCmode (Fig. 4a for the phase with maximal tropical and extratropical SSTAs)closely resembles the observed interdecadal mode; the opposite polarity ofanomalies are seen in the equatorial central Pacific and extratropical NorthPacific, the former having a horse-shoe shape in the tropical eastern Pacific andthe latter with an elliptical shape surrounded by anomalies of reversed sign in theeastern half of the ellipse. This corresponds well to the observed climatic shiftoccurring in the mid-1970s (e.g., Nitta and Yamada, 1989; Trenberth, 1990).

Fig. 3. Power spectra of the 1st EOF mode of the Pacific SSTA (solid), its 95% confidence level(dashed), and contributions by the oscillatory MSSA modes (shades).


The aspects of ocean dynamical adjustment can be better visualized byexamining the upper-ocean heat content (OHC). Figure 4b shows temperatureanomalies averaged over the upper 300 m in the ocean in the same phase of theoscillation as Fig. 4a. Inspecting the movie of OHC associated with the DC modeevolution, several characteristics can be noted; a clockwise movement of OHCanomalies (OHCAs) in the extratropical to subtropical North Pacific. This isreminiscent of the interdecadal mode simulated by Latif and Barnett’s (1994)coupled GCM. The subtropical OHC anomalies between 10° and 20°N propagatewestward, then northeastward along the coasts of Taiwan and Japan, then turn

Fig. 4. (a) SSTA (contour) and wind stress (vector) anomalies of the MSSA DC mode, obtained byregressing weakly bandpass filtered monthly anomalies onto the temporal coefficient of MSSAmode 2. (b) Regression pattern similar to (a), but for OHCA onto MSSA mode 2. Labeled linesdenote sections along which temporal evolutions of anomalies are shown in Fig. 5.

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eastward to occupy the central North Pacific centered about 35°N. On the otherhand, the equatorial anomalies have a Kelvin-wave-like eastward propagatingcomponent, similar to that associated with ENSO, but much slower. Interestingly,near the western boundary of the subtropical Pacific near the Phillipines, a partof the subtropical OHC leaks toward the tropics.

These features are conveniently seen in Fig. 5 which shows the timeevolutions of SST and OHC anomalies (regressed with the temporal coefficientof the decadal MSSA mode) along the sections marked in Fig. 4b. Time goesupward and the panel (a) of Fig. 5 is the longitude-time section of the SSTA along32°N. Panel (b) is the latitude-time section of OHCA along 170°W in the centralPacific evidencing subducted midlatitude anomalies propagating southward(latitude is decreasing to the right). Panel (c) follows the OHCA on the 18°Nlatitude line, the east-west direction being reversed. Panel (d) follows theequatorward movement of the OHCA between 22°N and the equator in thewestern Pacific averaged between 130°E and 150°E. Panels (e) and (f) arelongitude-time sections of OHCA and SSTA, respectively, on the equator.

Figure 5 appears to show the existence of a signal pathway from theextratropical ocean surface, through the subsurface of the subtropical and tropicalwestern Pacific oceans, all the way to the surface of the eastern equatorial Pacific(Jin et al., 2001). The return of the signal back to the extratropics may be fairlyeasily accomplished by an “atmospheric bridge” associated with the equatorialSSTA (Lau and Nath, 1996).

Fig. 5. Temporal evolutions of anomalies associated with MSSA mode 2 along the sections labeledin Fig. 4b. The ordinate denotes time in lagged years with respect to an arbitrary origin. (a) SSTAalong 32°N, (b) OHCA along 170°W, (c) OHCA along 18°N (east-west direction reversed), and(d) OHCA averaged between 130°E and 150°E. (e) OHCA and (f) SSTA on the equator.


Figure 4a also shows wind stress anomalies. Comparing with Fig. 4b, onenotes that the east-west oriented subtropical OHCA is sandwiched by theextratropical westerly and off-equatorial and appears to lie on the maximalnegative curl. The associated Sverdrup transport is southward and is consistentwith the subsequent equatorward “leak” of a part of the subtropical OHCAmentioned earlier.

The decadal mode simulated by the coupled GCM appears to show activeinvolvement of both tropical and extratropical ocean-atmosphere systems.Although it bears resemblance to the observed interdecadal mode, the periodappears much shorter (cf. Knutson and Manabe, 1998). The dynamics of the modeshould be better clarified with carefuly designed experiments.

The details of the QQ and QB modes are not shown here, but their spatialpatterns do have substantial resemblance. They seem to be confined more to thetropics than the DC mode. Clarifying the similarity and dissimilarity of thepatterns and dynamics of the three modes of variability is left as a futurechallenge.

Air-sea coupling in the North Atlantic

Watanabe et al. (1999) reported that the coupled GCM described above hasanother air-sea coupled mode over the North Atlantic with a period of about 10years. Spatial patterns of atmospheric and SST anomalies resemble those of anobserved counterpart: the well-known North Atlantic Oscillation (NAO) and atripole SST pattern (Deser and Blackmon, 1993). In midlatitudes, it is generallybelieved that a considerable part of SST anomaly is forced by atmosphericanomalies, in sharp contrast to tropical situations. However, in considering thedynamics of midlatitude decadal ocean-atmosphere variability, Watanabe andKimoto (2000a) pointed out that, in order for an oscillatory mode to survivevarious damping mechanisms, a positive feedback between the ocean andatmosphere is necessary; therefore, a component should exist in which the oceanforces the atmosphere. However, such a component is overwhelmed by theatmosphere-to-ocean forcing in midlatitude; therefore, its detection inobservational data is awkward.

Watanabe and Kimoto (2000b) conducted a series of coupled atmosphere-mixed-layer ocean model experiments to see whether a positive atmosphere-ocean feedback is found over the North Atlantic. A 60-yr integration of a T21L11version of the AGCM coupled with a 50-m deep motionless ocean was carriedout. This coupled run (called CTL) was compared with two other uncoupled runs:one with prescribed midlatitude sea surface temperatures (SSTs) at the climatology(called PS1) and another with daily SSTs derived from the coupled experiment(PS2), respectively. The uncoupled atmosphere in turn forces the slab ocean toobtain SST responses in the PS1 and PS2 runs.

The patterns of maximum atmosphere-ocean covariability show the NAOand tripole SST anomalies both in the coupled and uncoupled fields, indicatinga dominant role of the atmosphere in generating the SST anomalies. On the otherhand, analyses of the temporal variability in the three runs suggest an active role

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of SST anomalies in determining the polarity of the air-sea coupled variabilitylonger than the interannual time scale. A combined analysis of the forcing SST,upper-air height, and the response SST anomalies in the PS2 run identified thata patch of positive SST anomalies in the midlatitude band around 40°N effectivelyexcite the positive phase of the NAO, which in turn reinforces the tripole SSTanomalies (Fig. 6). This relationship has further been confirmed by a 9-memberensemble of an AGCM experiment forced by the SST patch. Because the forcingand response SST anomalies patterns bear a resemblance, these results manifestthe positive feedback at work in the coupled atmosphere-ocean patterns.

The processes responsible for this positive feedback have been elaborated bya series of linear model experiments. The model is a linearized primitive equationwith respect to an arbitrary three-dimensionally varying basic state. This linearmodel has been used (i) to obtain a stationary linear response to a given forcing(Branstator, 1990), and (ii) to simulate feedback due to high-frequency transients

Fig. 6. Heterogeneous regression maps for the leading mode of a singular value decompositionanalysis between 500 hPa height and combined “forcing” and “response” SST fields of the PS2run. (a) 500 hPa height, (b) prescribed forcing SST anomalies which are obtained from CTL, and(c) response SST anomalies calculated in PS2. Contour intervals for SST and height regressionsare 0.1 K and 10 m while the negative contours are dashed. The statistically significant area atthe 95 (99) % level is indicated by the light (dark) shadings.


onto a large-scale flow (a storm track model; Branstator, 1995).In the GCM, the local thermal adjustment of the atmosphere to the SSTAs

results in increased precipitation over the Gulf stream region. Associated diabaticheating given to the linear model yields a positive height response to the east,which highly projects onto the southern part of the NAO. This stationary responsein turn induces a northward deflection in the storm track activity, leading to aneddy vorticity feedback that tends to force the positive phase of the NAO.

CONCLUDING REMARKS

There is no doubt that GCMs provide a powerful experimental tool to studythe climate and its variability. They are comprehensive but far from complete.Therefore, continuous efforts for improvement and validation are necessary. Amodel with mediocre performance may not propose a credible mechanism. At thesame time, however, the output of the state-of-the-art GCMs is as complicated asnature itself. Carefully designed experiments and analyses are necessary to makeintelligent use of them.

Acknowledgments—The work presented here is the result of pleasant collaboration withmany colleagues. Especially, the author thanks Dr. A. Numaguti for developing asubstantial part of the AGCM, and Drs. X. Shen and M. Watanabe for sharing the fun ofthe jigsaw puzzles with him.

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M. Kimoto (e-mail: [email protected])

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