Jour. Korean Earth Science Society, v. 28, no. 3, p. 343 356, June 2007 (w )»-w w w ENSO p «* w w w / w, 561-756 1ƒ 664-14 Characteristics of the Simulated ENSO in a CGCM Byung-Kwon Moon* Division of Science Education/Institute of Science Education, Chonbuk National University, Chonbuk 561-756, Korea Abstract: This paper explored the characteristics of the interannual sea surface temperature (SST) variability in the equatorial Pacific by analyzing the simulated data from a newly coupled general circulation model (CGCM). The CGCM simulates well the realistic ENSO variability as well as the mean climatologies including SST, seasonal cycle, precipitation, and subsurface structures. It is argued that the zonal gradient of SST in the equatorial Pacific is responsible for the over-energetic SST variability near the equatorial western boundary in the model. This variability could also be related to the strong westward propagation of SST anomalies which resulted from the enhanced the zonal advection feedback. The simple two-strip model supports this by sensitivity tests. Analysis of the relationship between zonal mean thermocline depth and NINO3 SST index suggested that the ENSO variability is controlled by the recharge-discharge oscillator of the model. The lead-lag regression result reveals that heat buildup process in the western equatorial Pacific associated with the increase of the barrier layer thickness (BLT) is a precedent condition for El Niño to develop.,fzxpset CGCM, ENSO, El Niño, recharge-discharge oscillator : w»-w w x(cgcm) w ks w (SST) p w. x SST s³ s,,, š w ü d w w. ks d w j SST ks SST y w. d w w SST zonal advection feedback y g SST (westward propagation) ks ƒ ƒ. w two-strip w x ew. s³w d ¾ NINO3 SST - w ùkþ. š z w ƒ w» barrier layer thickness(blt) ƒ w ks ù w.»-w w,,, -»-w w x(atmosphere-ocean coupled general circulation model, CGCM) ³» z x w» w y w w. x» *Corresponding author: moonbk@chonbuk.ac.kr Tel: 82-63-270-2824 Fax: 82-63-270-2802 (primitive equation system) w,» w ³ j swwš. CGCM w w wù El Niño-Southern Oscillation(ENSO) ww (Delecluse et al., 1998). ENSO w (interannual variability) p ks s³ s (Gu and Philander, 1997; Fedorov and Philander, 2000). Mechoso and Coauthors(1995) x ks s³
344 «w. x ks w x (equatorial Pacific cold tongue)ƒ d w wš ùkù e. w û e w d w w w (sea surface temperature, SST)ƒ ùkû. d ùkù (intertropical convergence zone, ITCZ) w. w w CGCM w ks w v w š (AchutaRao and Sperber, 2002). x g wš, x ENSO SST w wš. w ENSO e ks e» ù» ƒ 2 d(~4 ) w ùkù š (Robertson et al., 1995; AchutaRao and Sperber, 2002). ü w Lee(2000), Park(2003) š Kug(2003). p Park(2003) x w x swwš x w ENSO d wš (Park and An, 2004). x d w SST s. š ENSO x x w ùkû. ù ENSO w ks ü d w d w j (Lee Fig. 5.15; Park Fig. 5.6 Fig. 5.11; Kug personal communication). x ENSO w k Meehl et al.(2001) d ùký yw y j w. ks d El Niño s w w w w (Zebiak and Cane, 1987; Latif et al., 1993). yw Noh and Kim (1999) w CGCM ENSO p r š w. Noh and Kim (1999) w. d ùkù s SST w q w» w w two-strip x(an and Jin, 2001) w. š ùkù ENSO (phase change) w ü f wwš w. ENSO ks w w w (Wyrtki, 1975; Jin, 1997a,b). Lee et al.(2006) ks yƒ ks w ENSO y ƒ š w. ù w w ü p w. ks barrier layer depth(blt) yƒ w w w w š š (Maes et al., 2005). d w ENSO w x w w ü BLT w. w w AOCGCM» y x (AGCM) w y x(ogcm).» x w» y x (SNUAGCM) Kim(1999) w. x T42 s w (~2.8 o 2.8 o ) ƒ rp. 20 (σ) d. x Tokyo University CCSR/NIES AGCM(Numaguti et al., 1995)» wš NCAR t (Bonan, 1996) non-local PBL/vertical diffusion scheme(holtslag and Boville, 1993) ƒ.» w Kim(1999) ùkù. w x Geophysical Fluid Dynamical Laboratory (GFDL) Modular Ocean Model2.2 (MOM2.2) w (Rosati and Miyakoda, 1988; Pacanowski, 1995). w 30 o S-50 o N x. û»z w Newtonian damping w sww. w w 1 o w. û w (10 o N-10 o S) 1/3 o š 30 o S 50 o N 3 o ƒw. w j w ENSO w w q w» w. 37 z- t d w 7.5 m, w 1000 m w. yw w Noh and Kim (1999) w. s
»w w w&/40 p 345 Fig. 1. Time-longitude distribution of equatorial SST anomalies for (a) simulation during the model year of 12-30 and (b) observation during 1982-2000. Units are o C. The values greater than 0 o C are shaded. ƒƒ 1 10 8 cm 2 1 10 7 cm 2 s 1.» w v w w v,,, š SST s³ yw.»» d SST w 10» x w š w Levitus(1982) w. CGCM e (numerical integration) 30 w š,» v (spin up) š w z 20 w. (SST, w,,» )»»zt (climate drift)ù (tendency)ƒ ùkù. w (Fig. A1) s³ p ùkþ. w ENSO p r š w. Fig. 1 ks d ùkù SST (anomaly) y š. s³ w. d w SST ùküš. 18-19 SST w 1986-87 w xk š. w 1990-94 ùkù» p 26-29 ùkù. p d w (McPhaden, 1999).
346 «š d w ùkù SST ks y ùkù (Moon, 2004 ). ƒ w j» 0.2 dyne cm 2. ƒ w ks ùk ù t y( t y) wš.,»-w w (mode) w ƒ wš. SST j» 3 o C ù d 4C¾ ùkùš (1982/83 o 1997 ). SST root-mean-square(rms) d ƒƒ 1.4 C o 1.6 C d o 87.5% ùkùš. NINO3(150 o W- 90 o W, 5 o S-5 o N) SST t r 0.85 C o d 1.04 C 81.7% j» o. AchutaRao and Sperber(2002) š 17 w x w SST w. x NINO3 SST t r s³,, ƒƒ 0.51 o C, 0.19 o C, 1.06 o C (AchutaRao and Sperber, 2002 Table 2). x w x NINO3 SST š. d ÿ»» ¼ (Fig. 1b). ù» ùkùš (Fig. 1a). Mobile mode (Mantua and Battisti, 1995)»(~1 year) ENSO d w j š (Jin et al., 2003; Kang et al., 2004). p Kang et al.(2004)» zonal advection feedback(an and Jin, 2001) w. ks SST ƒ (zonal advection feedback thermocline feedback) w ùkù š š.» zonal advection feedback w w SST w. w š SST ƒ ƒw zonal advection feedback w w. SST xk ww xk ùký (Neelin and Jin, 1993). Dewitte et al.(2007) CGCM w x ùkù» x Fig. 2. The root-mean-square (rms) of the SST anomalies from (a) simulation and (b) observation. Units are o C. w w» w. x w w x zonal advection feedback w ùkù w near-annual mode g. w x w yƒ w ùkù j»ƒ d w š w. SST rms s Fig. 2 ùkþ. x ùkù ks rms s d w j» xk. ù d w ùkùš, ks sƒ d j ùküš. d i ù g ù j rms š sww s. š ƒ¾ wš. ùkù d w x Newtonian damping w. w w w rms sƒ ks (~150 o E)¾ s w. p Fig. 1 SST ƒ ks ¾ w. rms ùkù p wš w.
»w w w&/40 p 347 Fig. 3. Power spectrum of the (a) model and (b) the observed NINO3 SST anomalies against red noise (dashed line). The observational SST anomalies during the period of 1950-2000 are used. w x ùkù mobile mode w» SST rp w w. Fig. 3 y w. d NINO3(150 o W-90 o W, 5 o S-5 o N) SST q rp 35-70 month» ùküš (Fig. 3b). 50 month w» d j ùkù 30, 20, 15 month» š., d w» w ùkùš. w x ENSO»ƒ d w ùkù x œm ùkù. p w x 1-2» w q ùkü w (AchutaRao and Sperber, 2002). Mobile mode ƒ w w zonal advection feed š š (Dewitte et al., 2007). SST s rms sƒ ks ¾ sw p SST (westward propagation)w w.» SST ùkù wš w. An and Jin(2001) w w zonal advection feedback thermocline feedback ùkù. Zonal advection feedback SST ww w š (Neelin and Jin, 1993). Zonal advection feedback s³ y w ù SST s y. x d w w w x w» (Fig. A2) SST y d j. w rms s p zonal advection feedback r» w d w SST (-dt/dx) Fig. 4. SST y d j ùküš. p ks ks j ùkùš. s SST r» w w two-strip x(an and Jin, 2001) wš w. x Jin(1997b) strip (off-equatorial) strip š w ƒ strip d ¾ SST w. x SST t Te = c(x)te + γ(x)he + a(x)um ùkù.» Te, he um ƒƒ strip SST, d ¾, š w ùkü. c(x), γ(x) a(x) ƒƒ Newtonian cooling w, d y s ùkü. w w ƒƒ thermocline feedback zonal advection feedback w. Two-strip x l x w w (finite difference method) w w w š (eigen value problem) x w w.
348 «Fig. 4. Longitude distribution of the zonal SST gradient (a(x) = T/ x) for model (solid) and observation (dashed). Units are 10 6 o C cm 1.» l An and Jin (2001) e g. SST y w» w a(x) = T/ x d SST w ƒƒ w (Fig. 4). d a(x) s ks j. p w xƒ d w w ùkù ks a(x) j ùkù š. ƒƒ a(x) w w SST Fig. 5 ùkþ. d a(x) w SST 170 o E ùkù. SST ƒ 140 E¾ š o. p Fig. 1 ùkù ew. SST ƒ d w ks ¾ e ùkù zonal advective feedback d w w» w. ks SST w ùkùš. š w v j wš w x w ùkù w SST w š. El Niño f Moon(2004) w x» e (5-19 year) w x ùkù ENSO f p w. x ENSO - (recharge-discharge oscillator; Jin, Fig. 5. Time-longitude distributions of SST anomalies for the most unstable eigenmode along the equator. (a) The eigenmodes are obtained based on a(x) of model. (b) Same as (a) except a(x) of observational SST. 1997a) p., w x - dw, SST, š d ¾ p w. ks NINO3 SST ks (5 o S-5 N) s³w d o ̃ 90 o (phase difference). ƒ w» 1/4 (phase) ks w (heat content) (charge). z w š (discharge) ƒ w. w w ks s p r š w. y barrier layer thickness
»w w w&/40 p 349 Fig. 6. The time series for the zonal mean thermocline depth anomalies (dashed line) and SST anomalies on NINO3 region (solid). Units are m and o C, respectively. Fig. 8. Time-longitude distributions of barrier layer thickness (BLT) greater than 40 m along the equator during the period of model year 11-30 is shown in shadings. The thick and thin lines indicate the 26 o C-isotherm and SST anomaly, respectively. Note that the only SST anomaly greater than 0.5 o C, i.e., El Niño period, is shown. Fig. 7. Trajectory plot for the zonal mean thermocline depth anomalies (m) and SST anomalies over the NINO3 area ( o C). Note that the arrows indicate the direction. (BLT) y ùkù (Maes et al., 2006). ks NINO3 SST q w» w w [H] T e Fig. 6 ùkþ.» [H] T e ƒƒ s³w d(thermocline) ¾, NINO3 SST w. [H] T e - d [H]ƒ T e 1/4 (phase) j wwš. w (zonal wind stress, τ x) T e ƒ [H]ƒ τ x 1/4 j. d ¾ 0 ƒà š 0 d y. w w sx wš ³x j w. p [H] T e ùkü Fig. 7 mw y w., ([H], T e ) eƒ(0, 0.9) El Niño d».» d ³ (geostrophic relationship) w w š. ([H], T e ) e 2- ww. ([H], T e ) w z w. Lee et al.(2006) d w w ks yƒ ks w ENSO y ƒ š w.» El Niño f w ü y vš w. Maes et al.(2005) Maes et al.(2002) v w ks w (salinity) barrier layer š
350 «Fig. 9. Lead-lag regression maps between the subsurface ocean temperature and the averaged western Pacific (130-180 o E) barrier layer thickness from the -1.25 year lead to +1.75 year lag at 0.25 year intervals. Note that the 0 year (g) and +1 year (k) are corresponding to BLT maximum and El Niño peak, respectively. w. barrier layerƒ ks w ùƒ k. barrier layerƒ ks. barrier layer thickness(blt) y Fig. 8 ùkþ. w» w 26 o C SST (>0.5 o C) wì.» BLT ƒ w ƒƒ 0.5 o C w ù 0.125 kg m ƒw ¾ 3 (Maes et al., 2005). BLT p ƒ ù» ks BLTƒ ƒwš. z BLTƒ wš ks ù w (26 o C ) w ƒ w. 18 w r 17 BLTƒ ƒw 18 BLTƒ wš 26 o C w ks SST ƒ wš. p
»w w w&/40 p 351 d w Maes et al.(2005) w e barrier layer w ewš. ks w barrier layer j w w. z f q w q ƒ w. Barrier layer y r» w ks BLT w z (lead-lag regression analysis) w. Fig. 9 ks (130-180 o E) BLT ks y ùkü. BLT ƒw ¾ ks ü š (Fig. 9a-9g). z d q (Fig. 9k) k., ks BLT w w š z ks k. ks ƒ w»¾ 1. d w w ü y wš.»z f w» w»-w w x w. w x w» y x(snuagcm; Kim, 1999) GFDL Modular Ocean Model(MOM)2.2 x(pacanowski, 1995). w yw ù d m Noh and Kim(1999) x w x ƒw.» x rp x s w T42 š 20d t. w x w û w., w»z w w w q w» w 1/3 o û w. w w w 1 o š.» x w x w w x s³ w. w x 30 e w š z 20 (11-30 model year) w. x» j»z t ùkü. (SST, SST,, w ) s³ s d j. x w w w. NINO3(150 o W-90 o W, 5 o S-5 o N) SST t r 0.85 o C d 81.7% j». Coupled Model Intercomparison Project(CMIP) 17 x w (AchutaRao and Sperber, 2002). ù d ùkù»(~4 year)»(1-2 year) w q ùkþ. x ùkù mobile mode(mantua and Battisti, 1995) y near-annual mode(jin et al., 2003)ƒ (Dewitte et al., 2007). w zonal advection feedback SST ƒ d w w ks d w j SST rms s š. y w» w w two-strip x w. x w SST w d w SST { ks w. p (westward propagation) x ks w ùkû. ù w two-strip x zonal advection feedback w SST»ƒ j (Fig. 5). x ùkù» SST y w zonal advection feedback w. Dewitte et al.(2007) w x ù kù» w w w. x» w v w. x Jin(1997a) - p. s³ d ¾ NINO3 SST w 90 o d yƒ š. ks barrier layer thickness(blt) y ww» w ks BLT y w ü w. z ƒ w» 2 l 1 ¾ ks. BLT
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354 «x w s³ d w r š w. x yw š Noh and Kim(1999) wš. PP scheme(pacanowski and Philander, 1981) w ù d m w w ù (turbulence) š w. PP scheme ùkü (Richardson number) w yw txw. w w k w yw w. ù w w k w ù w yw. wš w k w PP scheme yw w txw d SST w. Noh and Kim(1999) 2 ù w w k d w w ùkü š (Noh et al., 2002). 1. SST SST p r š w. SST» w ùkù» w x sƒw ƒ w. CGCM s³ SST d s, š Fig. A2 ùkþ. x SST s ùküš. d w ks SST ks û w xƒ ewš SSTƒ wš. ù d w w xƒ w w ks ù (warm pool) w wš. w w x ƒ ù xk û jš. š x SST i ù w 3 o C r ùküš (Fig. A2c). d w Û2 o C. (bias) x»-w w x ùkù œm š (Mechoso and Coauthors, 1995). SST s³ s ùkù w š SST d ùkù p. Fig. A3a, A3b, ks SST Fig. A1. A schematic diagram describing the coupling strategy of atmosphere-ocean coupled general circulation model (AOCGCM). The ocean and atmosphere model exchange information (air-sea fluxes and SST) once per simulated day. Model has integrated without any flux correction or restoring. Fig. A2. The annual mean sea surface temperature (SST) for both (a) 20-yr model simulation, and (b) observation (NOAA SST) during the period of 1982-2002. (c) The simulated SST bias relative to the observation.
»w w w&/40 p 355 Fig. A3. Simulated annual mean SST for (a) summer (June- August) and (b) winter (December-February). (c) and (d) are same as (a) and (b), respectively except for observation. Fig. A5. Annual mean precipitation for (a) simulated, (b) observed CMAP data (Xie and Arkin, 1997), and (c) their difference (model minus observation). Units are mm day 1. Fig. A4. Annual cycle along the equator for (a) model and (b) observation. w û wš. j» d ù kùš (Fig. A3c, A3d). w»-w y ùkù y sƒw w t ƒ. Fig. A4 yƒ d ùk ù p ƒš. ù y s d w jš wwš. y (phase) d w 1-2 š. s Fig. A5 ùkþ. s d w. (ITCZ) ùkù. w ks (Asia Monsoon) wš. p w w (East Asia Monsoon) ƒ mm day ü 1. ù d w ~6 mm day 1 wš. p ks ùkù r w x ùkù ƒ w. SST w y d w j. p w ( ùkü ). 2. w ü ks d(thermocline) ü w (equatorial under current) ENSO j w e (Cane, 1992).
356 «Fig. A6. Longitude-depth distribution of subsurface temperature for (a) simulation and (b) SODA. Units are o C. The area between 19.5 and 20.5 o C is shaded to indicate the thermocline. d ü w p r š w. d Simple Ocean Assimilation Data(SODA, Carton et al., 2000) w. d ùkü w y SODA w wš (Fig. A6). x w ü s w yw x (Noh et al., 2002). ks (~90 o W) d ùkù ¾ ƒ 30 m d 50 m w. š ks d w ùkù. w w w x. w ks ù w e š SODA w 1 o C û. š ks (~150 o E) d Fig. A7. The same to Fig. 6 except for zonal current. Units are cm s 1. Area greater than 40 cm s 1 is shaded. ¾ 20 m û ùkùš. w w Fig. A7 ùkþ. w -» ùkù. w j d (Fig. A6) w». w d w w ùkü. ù w ü w ³ ƒ d w š j»ƒ 10 cm s û 1 ùkù. d(0-50 m) w ³ ƒ jš w ùkùš. Coupled Model Intercomparison Project(CMIP) ƒw w s r ƒ SST s d j ƒ ù w ü w ƒ ƒ j ù kù ( w ). w x sƒw» w SST w ü v w w.