TTL Upwelling driven by Equatorial Waves
L09804 LIUWhat drives the annual cycle in TTL upwelling? ET AL.: START OF WATER VAPOR AND CO TAPE RECORDERS L09804
Liu et al. (2007)
Ortland, D. and M. J. Alexander, The residual mean circula on in the TTL driven by tropical waves, JAS, (in review), 2013.
Figure 1. (a) Seasonal variation of 10°N–10°S mean EOS MLS water vapor after dividing by the mean value at each level. (b) Seasonal variation of 10°N–10°S EOS MLS CO after dividing by the mean value at each level. represented in two principal ways. The first is by the area of [8]ConcentrationsofwatervaporandCOnearthe clouds with low infrared brightness temperatures [Gettelman tropical tropopause are available from retrievals of EOS et al.,2002;Massie et al.,2002;Liu et al.,2007].Thesecond MLS measurements [Livesey et al.,2005,2006].Monthly is by the area of radar echoes reaching the tropopause mean water vapor and CO mixing ratios at 146 hPa and [Alcala and Dessler,2002;Liu and Zipser, 2005]. In this 100 hPa in the 10°N–10°Sand10° longitude boxes are study, we examine the areas of clouds that have TRMM calculated from one full year (2005) of version 1.5 MLS Visible and Infrared Scanner (VIRS) 10.8 mmbrightness retrievals. In this work, all MLS data are processed with temperatures colder than 210 K, and the area of 20 dBZ requirements described by Livesey et al. [2005]. Tropopause echoes at 14 km measured by the TRMM Precipitation temperature is averaged from the 2.5° resolution NCEP Radar (PR). The year studied is 2005. To generate geo- reanalysis data [Kistler et al.,2001;Randel et al.,2004]in seasonal distributions of deep convection near the tropical 2005. Similarly, the geo-seasonal variation of GEIA CO tropopause, the areas of VIRS cold clouds and PR echoes at surface emission rate in 2005 is averaged in the same 14 km from 10°S–10°Nareaccumulatedin10° longitude 10°N–10°Sand10° longitude boxes in each month. boxes for each month. Geo-seasonal distributions are obtained from the ratio of the accumulated area to total 3. Results area in each box. [7]Thincloudoccurrencenearthetropopauseisobtained [9]Figure2showsthegeo-seasonalvariationsofdeep from SAGE II observations. An algorithm similar to the convection, thin cloud, water vapor, CO, and tropopause SAGE II cloud detecting algorithm developed by Kent et al. temperature. The incidence of cold cloud reaching 210 K [1993] is used, which infers the presence of cloud when the (Figure 2a) shows four persistent longitudinal bands. 1 1.02 mmextinctioncoefficientisgreaterthan0.001kmÀ , These are located over the west Pacific (150°E–180°E), and the ratio of 0.525 mmextinctioncoefficienttothe western Indonesia (90°E–120°E), central Africa (10°E– 1.02 mmextinctioncoefficientisgreaterthan0.95.Subvi- 35°E) and the Amazon (50°W–80°W). The latter three sual clouds near the tropopause are identified from version locations display maximum incidence in Spring and Fall. 6.2 SAGE II data from 1985–2004, excluding the years The disproportionately small area of 20 dBZ radar echoes 1991–1995 which were contaminated by volcanic aerosol reaching 14 km over the West Pacific in Figure 2b is [McCormick et al.,1995].Meancloudoccurrencesare probably due to the relatively smaller or less particles calculated as the percentage of events with clouds in two inside the relatively weak deep convection over the region layers (14–16 km and 16–18 km) from 10°N–10°Sandin [Liu et al.,2007].Notably,thegeo-seasonalpatternin 10° longitude boxes. deep convection is similar to climatology of geo-seasonal
2of6 D06107 ROSENLOF AND REID: TROPICAL LOWER STRATOSPHERIC TRENDS D06107
Figure 10. Tropical HALOE water vapor (tape recorder), 5°S–5°N, plotted versus time. Note the change to lower values of the hygropause at the end of 2000 and the upward propagation of those lower values in subsequent years. function like decrease in temperature is not zonally uniform. the tape recorder signal noted by Mote et al. [1995, 1996]. This is demonstrated in Figure 14, which shows the lagged However, as noted by Rosenlof [1995], the annual cycle in correlation of monthly averaged tropical tropopause temper- tropical tropopause layer temperatures does not correlate atures as a function of longitude with the zonally averaged highly with an annual cycle in zonally averaged tropical HALOE water vapor time series along with a similar SSTs, in that maximum near tropopause temperatures are in anomaly correlation. Tropopause temperatures lead July-August when SSTs are at a minimum, but the minimum 2 months relative to the HALOE water time series to yield tropical tropopause layer temperatures occur in December– the maximum correlation. The correlation is longitudinally January, not in April, when SSTs are at a maximum. For the uniform and on averageWater Vapor and Cold Point Temperatures the correlations coefficient is 0.82 case of zonally averaged anomalies, SST and tropopause for the monthly averageare causally related on many mescales time series correlations. This high temperatures are also not well correlated; the coefficient is correlation is a consequence of the strong annual cycle in 0.23 using NCEP 10°S–10°Ntropopausetemperatures both tropopause temperatures and water vapor and results in À Rosenlof & Reid [2008] • Causes of the annual cycle in water vapor, temperature, and upwelling in the TTL “remain to be clarified” [Randel & Jensen, 2013].
• Causes of recent decadal- scale changes in stratospheric water vapor Figure 11. TheSolomon et al. [2010] 10°N–10°SwatervapormixingratiofromHALOEatthealtitudeoftheaverageprofile minimum in the tropics (black solid, scale on left) and NCEP/NCAR reanalysis zonal average tropopause are poorly understood, yet temperatures (grey dashed, scale on right). The correlation maximizes with a 2-month shift, with water vapor lagging. these changes have
10 of 15 resulted in significant decadal-scale changes in surface warming. • Likely related to changes in TTL upwelling. M. Abalos et al.: Variability in tropical upwelling and correlations with tracers 11509
Upwelling rates at 100hPa
• Schoeberl et al. [2008]: Upwelling rates in TTL based on H2O observa ons ~0.4-0.5 mm/s
• Dima and Wallace [2007] from ERA-40 ~ 0.55 mm/s M. Abalos et al.: Variability in tropical upwelling and correlations with tracers 11509 • Abalos et al [2012]: ERA-Interim; three different methods:
Fig. 3. Time series and mean seasonal cycles of the three upwelling estimates averaged over 18 N–S at 70, 80 and 100 hPa (top to bottom w w w panels). Green: residual circulation ( ⇤), blue:Annual Mean ~ 0.4-0.5 mm/s momentum balance estimate ( m⇤ ), and red: thermodynamic estimate ( Q⇤ ). 11-days running 1 means are applied to the time series. The annualAnnual Cycle ~ a factor of two cycles are calculated as monthly means over 2005–2010 (mm s ).
agreement among these estimates reflects a reasonably good understanding of the seasonal and sub-seasonal variability in tropical upwelling.
3 Co-variations of upwelling, temperatures and tracers
Fig. 3. Time series and mean seasonal cycles of the three upwelling estimates averaged over 18A N–S simple at explanation 70, 80 and for100 the hPa strong (top to correlations bottom between panels). Green: residual circulation (w⇤), blue: momentum balance estimate (wm⇤ ), and red: thermodynamictemperatures estimate and tracers (w inQ⇤ ). the 11-days tropical running lower stratosphere means are applied to the time series. The annual cycles are calculated as monthly means over 2005–2010(Fig. 1) is that (mm they s 1 result). primarily from forcing by tropical upwelling. The origin of this coupling can be appreciated by examining the zonal mean thermodynamic and tracer mixing ratio continuity equations in the TEM formalism (Andrews agreement among theseet al., estimates 1987): reflects a reasonably good understanding of the seasonal and sub-seasonal variability in @T 1 @T v⇤ w⇤S Q (4) tropical upwelling. @t = a @ + Fig. 4. Linear correlations among the time series of the three up- 1 @ z/H @T @ welling estimates as a function of pressure. e v T w T e z/H @z 0 0 a S + 0 0 3 Co-variations of upwelling, " temperatures · and tracers!# @ 1 @ @ v⇤ w⇤ M P L (5) the entire data record. Figure 3 showsA overall simple good explanation agree- @t for= thea @ strong correlations@z + r · + between ment among the time series and the meantemperatures seasonal variation and tracersIn the continuity in the tropical Eq. (5), lowerrepresents stratosphere the zonal mean mix- of the three upwelling estimates, especially(Fig. between 1) isw thatm⇤ and they resulting ratio primarily of the tracer, from forcingM is the by eddy tropical transport term (as w . Inspection of the variability in the time series reveals in Andrews et al., 1987,r Eq.· 9.4.13) and P L is the chem- Q⇤ upwelling. The origin of this coupling can be appreciated by strong similarities among the three estimates,examining showing the nu- zonalical mean production thermodynamic minus loss and rate. tracer Averaging mixing over the tropics merous common fluctuations on a wide range of timescales. and for a given pressure level, these equations state that the ratio continuity equations in the TEM formalism (Andrews Note that the good agreement between wm⇤ and wQ⇤ suggests changes in tropical mean temperature or tracer concentra- that wm⇤ may be accurately calculatedet from al., resolved 1987): eddy tion arise from the combined effects of meridional and verti- fluxes alone. Correlations between the different estimates are cal advection by the residual mean circulation (that is, mean shown in Fig. 4. The correlations among@wT, w and w1 @,T in meridional transport to/from the extra-tropics and upwelling ⇤ m⇤ v⇤ Q⇤ w⇤S Q (4) the tropical lower stratosphere are around@t 0.64–0.76.= a These@ acting+ on the background vertical gradient), eddy transport fairly high correlations between the estimates are encourag- and diabatic heating in the case of temperature or chemical Fig. 4. Linear correlations among the time series of the three up- ing, given the uncertainties described above and1 the very@ dif-z/H sources/sinks@T @ for tracers. Equations (4) and (5) form the ba- welling estimates as a function of pressure. e v T w T ferent approaches followed to compute them.e z/H The degree@z of sis0 for0 oura analysisS + of temperature0 0 and tracer coupling with " · !# @ 1 @ @ www.atmos-chem-phys.net/12/11505/2012/v⇤ w⇤ Atmos.M P Chem.L Phys., 12, 11505–(5)11517, 2012 the entire data record. Figure 3 shows overall good agree- @t = a @ @z + r · + ment among the time series and the mean seasonal variation In the continuity Eq. (5), represents the zonal mean mix- of the three upwelling estimates, especially between w and ing ratio of the tracer, M is the eddy transport term (as m⇤ r · wQ⇤ . Inspection of the variability in the time series reveals in Andrews et al., 1987, Eq. 9.4.13) and P L is the chem- strong similarities among the three estimates, showing nu- ical production minus loss rate. Averaging over the tropics merous common fluctuations on a wide range of timescales. and for a given pressure level, these equations state that the Note that the good agreement between wm⇤ and wQ⇤ suggests changes in tropical mean temperature or tracer concentra- that wm⇤ may be accurately calculated from resolved eddy tion arise from the combined effects of meridional and verti- fluxes alone. Correlations between the different estimates are cal advection by the residual mean circulation (that is, mean shown in Fig. 4. The correlations among w⇤, wm⇤ and wQ⇤ , in meridional transport to/from the extra-tropics and upwelling the tropical lower stratosphere are around 0.64–0.76. These acting on the background vertical gradient), eddy transport fairly high correlations between the estimates are encourag- and diabatic heating in the case of temperature or chemical ing, given the uncertainties described above and the very dif- sources/sinks for tracers. Equations (4) and (5) form the ba- ferent approaches followed to compute them. The degree of sis for our analysis of temperature and tracer coupling with www.atmos-chem-phys.net/12/11505/2012/ Atmos. Chem. Phys., 12, 11505–11517, 2012 32 Ortland et al., Tropical Residual Mean Circulation
32 Ortland et al., Tropical Residual Mean Circulation Our Work: Model Study of Tropical Waves Effects in the TTL • Idealized global primi ve equa on model
• Waves forced by latent hea ng Q(x,y,z,t) derived from observed precipita on 31 Ortland et al., Tropical Residual Mean Circulation • TRMM Rain Rates gridded 0.25ox0.25o and 3-hrly 31 Ortland et al., Tropical Residual Mean Circulation
• Examine tropical waves, wave propaga on and dissipa on 784 • Zonal-mean U and T 785 Figure 1. TRMM heating at 7 km and over four seasons in 2007. constrained to observa ons 30S-30N.
• Compute wave EP-Flux and EP-Flux divergence.
• Compute residual circula on and TTL upwelling driven by the EP-Flux divergence. 784 785 Figure 1. TRMM heating at 7 km and over four seasons in 2007.
705 706 Figure 2. Top: The eddy component of the temperature field and zonal and vertical wind 705 707706 componentsFigure 2. Top: averaged The eddy from component 10S-10N ofand the 2007. temperature The TTL field is and bounded zonal andby the vertical horizontal wind 708707 redcomponents lines. Vertical averaged scale from of the10S-10N vectors and is exaggerated2007. The TTLby a factoris bounded of 1000 by inthe this horizontal and the 709708 followingred lines. figures.Vertical scale Middle: of the The vectors eddy is component exaggerated of by the a factor temperature of 1000 field in this at and 26 hPathe 710709 averagedfollowing over figures. 2007. Middle:Bottom: The The temperature eddy component field at of 100 the hPa temperature averaged over field 2007. at 26 hPa 710 averaged over 2007. Bottom: The temperature field at 100 hPa averaged over 2007. DRAFT 8/19/2013 DRAFT
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Model Annual Mean Compared to Reanalysis Realis c tropopause temperatures and cold pool
100 hPa Temperature lon/lat
OCTOBER 2010 V I R T S E T A L . 3117 OCTOBER 2010 V I R T S E T A L . 3117
Virts705 et al. [2010] 100 706hPa ERA-40 Figure 2. Top: The eddy component of the temperature field and zonal and vertical wind Temperatures 707 components averaged from 10S-10N and 2007. The TTL is bounded by the horizontal 708 red lines. Vertical scale of the vectors is exaggerated by a factor of 1000 in this and the 709 and following figures. Middle: The eddy component of the temperature field at 26 hPa 710 averaged over 2007. Bottom: The temperature field at 100 hPa averaged over 2007. CALIPSO Cirrus above 15km
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FIG. 3. (a) Mean 100-hPa temperature (contours at ...280, 279, 276, 273, ...8C; outermost FIG. 3. (a) Mean 100-hPa temperature (contours at ...280, 279, 276, 273, ...8C; outermost dark contour is 2798C), (b) cloud fraction with base above 15 km (CI 5 0.05), (c) cloud fraction dark contour is 2798C), (b) cloud fraction with base above 15 km (CI 5 0.05), (c) cloud fraction in the 11–12-km layer (without reference to cloud-base altitude; CI 5 0.05), and (d) GPCP in the 11–12-km layer (without reference to cloud-base altitude; CI 5 0.05), and (d) GPCP precipitation (CI 5 1.5 mm day21). Latitude resolution is 58, with values every 2.58; longitude precipitation (CI 5 1.5 mm day21). Latitude resolution is 58, with values every 2.58; longitude resolution is 108. resolution is 108.
basic state depicted in Figs. 2 and 3. We will show that basic state depicted in Figs. 2 and 3. We will show that 4. Temporal variations in TTL cirrus: A the variations about the mean state are also character- the variations about the mean state are also character- planetary-scale perspective ized by geometrically simple, equatorially symmetric ized by geometrically simple, equatorially symmetric patterns with analogous Kelvin and Rossby wave sig- In this section, we investigate the relationship be- patterns with analogous Kelvin and Rossby wave sig- In this section, we investigate the relationship be- natures and a strong inverse relationship between TTL tween TTL cirrus and its planetary-scale environment. natures and a strong inverse relationship between TTL tween TTL cirrus and its planetary-scale environment. cirrus cloud fraction and 100-hPa temperature in the We begin by showing the spatial patterns obtained by cirrus cloud fraction and 100-hPa temperature in the We begin by showing the spatial patterns obtained by equatorial belt. We will argue that these features con- correlating time series of filtered cloud fraction with equatorial belt. We will argue that these features con- correlating time series of filtered cloud fraction with stitute further evidence of in situ TTL cirrus formation bases above 15 km in 1083108 boxes throughout the stitute further evidence of in situ TTL cirrus formation bases above 15 km in 1083108 boxes throughout the in regions of ascent associated with convectively forced tropics with selected reference time series of atmo- in regions of ascent associated with convectively forced tropics with selected reference time series of atmo- equatorial planetary waves. Hence, the evidence pre- spheric variables at specified locations. Figure 4 shows equatorial planetary waves. Hence, the evidence pre- spheric variables at specified locations. Figure 4 shows sented in these papers consistently suggests that tropi- correlations between 100-hPa temperatures from the sented in these papers consistently suggests that tropi- correlations between 100-hPa temperatures from the cal convection induces TTL cirrus not so much directly, ERA-Interim analyses averaged over five reference cal convection induces TTL cirrus not so much directly, ERA-Interim analyses averaged over five reference through the spreading of the anvils of convective boxes (outlined in black) and the gridded cloud index through the spreading of the anvils of convective boxes (outlined in black) and the gridded cloud index clouds, as indirectly, by forcing patches of planetary- throughout the tropics. The reference boxes have been clouds, as indirectly, by forcing patches of planetary- throughout the tropics. The reference boxes have been scale ascent within the stably stratified layer above the chosen to represent the three areas of maximum TTL scale ascent within the stably stratified layer above the chosen to represent the three areas of maximum TTL cloud tops. cirrus occurrence—Africa, the Maritime Continent and cloud tops. cirrus occurrence—Africa, the Maritime Continent and 714 713 712 711 etn drvd rm RM anal aeae oe fu saos n 07 Ti figure This 2007. in simulation withbackground windsequaltozero. shows theresultsfor seasons four over averaged rainfall, TRMM from derived heating 3 Figure DRAFT DRAFT DRAFT DRAFT 32 Ortland et al., Tropical Residual Mean Circulation . EP-flux (vectors) and its divergence (contours) for equatorial waves forced by by forced waves equatorial for (contours) divergence its and (vectors) EP-flux . 721 720 719 718 717 vr or esn i 20. hs iue hw te eut fr h smlto with simulation the for results the shows figure This 2007. to zero. background windsequal in seasons four over averaged rainfall, TRMM from derived heating by forced waves equatorial for (contours) iue 5 Figure 34 DRAFT DRAFT DRAFT DRAFT 3/26/2013 Ortland et al., Tropical Residual Mean Circulation
Pressure (hPa) . Residual mean circulation (vectors) and the residual mean vertical velocity velocity vertical mean residual the and (vectors) circulation mean Residual . Model Results: Tropical Waves Only with U=0 EP Flux and Flux Divergence (le ) and Residual Circula on and Upwelling (right) La tude
3/26/2013
La tude
716 715 714 713 712 711 etn drvd rm RM anal aeae oe fu saos n 07 Ti figure This 2007. in simulation withbackground windsequaltozero. shows theresultsfor seasons four over averaged rainfall, TRMM from derived heating 3 Figure DRAFT DRAFT DRAFT DRAFT 32 Figure 4. Figure DRAFT DRAFT DRAFT DRAFT 33 Ortland et al., Tropical Residual Mean Circulation Ortland et al., Tropical Residual Mean Circulation . EP-flux (vectors) and its divergence (contours) for equatorial waves forced by by forced waves equatorial for (contours) divergence its and (vectors) EP-flux . Same as Fig. 3, for the simulation with background winds derived fromNCEP. forthe simulationwithbackground windsderived as Fig. 3, Same 723 722 721 720 719 718 717 Figure 6. Figure 35 DRAFT DRAFT DRAFT DRAFT vr or esn i 20. hs iue hw te eut fr h smlto with simulation the for results the shows figure This 2007. to zero. background windsequal in seasons four over averaged rainfall, TRMM from derived heating by forced waves equatorial for (contours) iue 5 Figure 34 DRAFT DRAFT DRAFT DRAFT 3/26/2013 3/26/2013 Ortland et al., Tropical Residual Mean Circulation Ortland et al., Tropical Residual Mean Circulation
Pressure (hPa) . Residual mean circulation (vectors) and the residual mean vertical velocity velocity vertical mean residual the and (vectors) circulation mean Residual . Same as Fig.5, for the simulation with background winds derived fromNCEP. forthesimulationwithbackground windsderived as Fig.5, Same Tropical Waves Only with Observed Winds U = 0 Winds shi the pa erns downward with slightly weaker upwelling. EP Flux and Flux Divergence (le ) and Residual Circula on and Upwelling (right) La tude 3/26/2013 3/26/2013
La tude /
36 Ortland et al., Tropical Residual Mean Circulation Two-year runs with observed Zonal-Mean Winds 2006-2007 36 Ortland et al., Tropical Residual Mean Circulation The important waves have low phase speeds: Influenced by changes O~5m/s
Time/Height:
QBO
Variable upper troposphere
Time/La tude in TTL: Variable Subtropics
Weak easterly near equator
724 724725 Figure 7. Zonal and monthly mean zonal winds from NCEP for 2006-2007. Top: 725726 FigureVertical 7. profiles Zonal averaged and monthly from 15ºS-15ºN,mean zonal (contour winds from interval NCEP 3 ms for-1); 2006-2007. Bottom: Latitude Top: 726727 Verticalcross sections profiles averaged averaged from from 90-190 15ºS-15ºN, hPa (contour (contour interval interval 4 ms 3-1 ). ms -1); Bottom: Latitude 727 cross sections averaged from 90-190 hPa (contour interval 4 ms-1).
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With U=0, there is variability, but no 39 Ortland et al., Tropical Residual Mean Circulation clear annual cycle.
Seasonal changes in the winds give clear seasonal varia ons in tropical wave driving and upwelling.
733 734 Figure 9. Same as Fig.8, for EP-flux divergence.
735 736 Figure 10. Same as Fig. 8, for vertical residual mean velocity.
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w/Observed winds: No Wind
Sta onary equatorial Rossby waves primarily drive the TTL upwelling.
Transient westward waves much less.
Kelvin waves contribute a small downwelling component close to the equator.
743 744 Figure 12. Same as Fig. 11, for the residual mean vertical velocity.
DRAFT 3/26/2013 DRAFT 732 N. Butchart et al.: Simulations of anthropogenic change in the strength of the Brewer–Dobson circulation (2006) 27:727–741
CMAM FUB−CMAM GISS GISSchem 1 1 1 1
40 40 40 40 ) ) ) ) Pa Pa Pa Pa (h (h (h (h re re re re su su su su es es es es 10 Pr 10 Pr 10 Pr 10 Pr Pressure (hPa) Pressure (hPa) Pressure (hPa)
0.4 0.4 0.4
20 0.4 20 20 20 70 0.0 68 0.0 68 0.0 68 0.0 100 100 100 100 −60 −40 −20 0 20 40 60 −60 −40 −20 0 20 40 60 −60 −40 −20 0 20 40 60 −60 −40 −20 0 20 40 60 Latitude Latitude Latitude Latitude IGCM MAECHAM4chem MRI UM49L 1 1 1 1
40
40 40 40 ) Pa (h P r e s u ( h a ) P r e s u ( h a ) re ssu e Pr ) Pa (h re ssu e 10 10 10 Pr 10 Pressure (hPa) Pressure (hPa) Pressure (hPa) Pressure (hPa) 0.4 0.4 20 20 0.4 0.4 20 63 0.0 20 70 0.0 70 0.0 68 0.0 100 100 100 100 −60 −40 −20 0 20 40 60 −60 −40 −20 0 20 40 60 −60 −40 −20 0 20 40 60 −60 −40 −20 0 20 40 60 Latitude Latitude Latitude Latitude UM64L UM64Lchem UM64LS WACCM 1 1 1 1
40 40 40 40
10 P r e s u ( h a ) 10 P r e s u ( h a ) 10 P r e s u ( h a ) 10 P r e s u ( h a ) Pressure (hPa) Pressure (hPa) Pressure (hPa) Pressure (hPa)
0.4 0.4 20 20 20 0.4 20 0.4 68 0.0 68 0.0 70 0.0 73 0.0 100 100 100 100 −60 −40 −20 0 20 40 60 −60 −40 −20 0 20 40 60 −60 −40 −20 0 20 40 60 −60 −40 −20 0 20 40 60 QBO Effects on TTL Upwelling Latitude Latitude39 Ortland etLatitude al., Tropical Residual Mean CirculationLatitude TTL Upwelling SON Fig. 1 Meridional cross-sections of the annual mean residual1.0 UM64LS. For the transient runs (GISS, GISSchem, UM49L, verticalLocal minimum at the equator velocities for each model. Climatological means are 2006 Hea ng UM64L, UM64Lchem and WACCM) the 10-year mean for shownis associated with enhanced for the 1990s. For the equilibrium experiments results 2007 Hea ng 1991–2000 (1992–2001 for UM49L) is shown. Only the zero were takenKelvin wave drag in the lower- from the run closest to 1990 conditions, i.e. the contour is shown and upwelling regions are shaded. The dotted 1 · CO2 run for CMAM, the ‘‘2000’’ run for FUB-CMAM0.5 curves indicate the strength (right hand ordinate) of the most stratosphere in the –1 includingQBO westerly wind case. both GHG and O3 changes, the ‘‘1997’’ run of the upwelling velocities in mm s at ~ 70 hPa (see horizontal line mm/s IGCM with all GHG changes, the ‘‘2000’’ run of MAE- for precise level for each model) CHAM4chem, the control run for MRI, and 1 · CO2 run for Differences in hea ng pa erns 0 (i.e. differences in wave forcing) modelin different years also create the mean circulation strength appears to be between theSolid = w/2006 QBO wind (westerly) prescribed and predicted ozone climatol- affectedsome differences. by the inclusion of ozone chemistry, though ogies used inDo ed = w/2007 QBO wind (easterly) the two runs than the coupling per se. this is probably more due to systematic differences-0.5 -20 3.3 Trends-10 0 10 20 0.8 711 Butchart et al. [2006] mul -model comparison 712 Figure 13. ResidualIn response mean Mul -Model Mean vertical to the rise velocity in WMGHG averaged concentrations, over SON 2006 all and the TTL 0.4 713 altitudes. Black curves are for TRMM heating from 2006, red from 2007. Solid curves 714 are for NCEP backgroundthe experiments windsUKMO analysis (10-yr mean) from predicted 2006, dashed an increase from 2007. in theThe annualsolid curves show a 0.0 715 local minimum nearmean the equator mass fluxthat likely entering is the the result stratosphere of Kelvin wave (Fig. forcing5), . 716 −0.4 Differences in wave forcing and/or differences in QBO winds in the lowermost stratosphere equivalent to a trend of about 2% per decade. This was −0.8
Vertical velocity (mm/s) due to a strengthening of the Brewer–Dobson circu- −40 −20 0 20 40 could cause differences in tropical upwelling. Latitude lations in the experiments, with the width of the trop- ical upwelling regions remaining largely unaffected by Fig. 2 Dotted lines annual mean residual vertical velocities at climate change (not shown). Eventually, the increase in ~ 70 hPa as in Fig. 1. The thick line is the multi-model mean and the thick dashed line is the 10-year mean (1992–2001) from the mass flux may, however, saturate as the increase in UK Met Office analyzes at 68 hPa mass flux in the UM64LS from 2 to 4 · CO2 is smaller
123
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43 Ortland et al., Tropical Residual Mean Circulation
TTL Upwelling: What is the role of extratropical synop c waves?
Results shown so far eliminated synop c waves. • Sta onary equatorial waves drive the TTL upwelling, and • Synop c waves are transient • Here we isolate transient waves in MERRA
EP FLUX and DIVERGENCE
RESIDUAL CIRCULATION and UPWELLING
• Upwelling driven by synop c waves in 43 Ortland et al., Tropical Residual Mean Circulation current climate lies below the TTL.
• The seasonal cycle of synop c wave-driven upwelling is semi-annual. 828 829 Figure 12. Response of the TEM model to MERRA transient wave forcing. Top: Conclusion is synop c waves are not an 828830 Residual mean vertical velocity, averaged from 15ºS-15ºN; Middle: EP-flux (vectors) and important driver of seasonal varia ons in 829831 Figureits divergence 12. Response (contours); of the Bottom: TEM model Residual to MERRA mean circulation transient (vectors) wave forcing. and residual Top: TTL upwelling. 830832 Residualmean vertical mean velocity vertical (contours). velocity, averaged from 15ºS-15ºN; Middle: EP-flux (vectors) and 831 its divergence (contours); Bottom: Residual mean circulation (vectors) and residual 832 mean vertical velocity (contours).
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828 829 Figure 12. Response of the TEM model to MERRA transient wave forcing. Top: 830 Residual mean vertical velocity, averaged from 15ºS-15ºN; Middle: EP-flux (vectors) and 831 its divergence (contours); Bottom: Residual mean circulation (vectors) and residual 832 mean vertical velocity (contours).
DRAFT 8/19/2013 DRAFT Conclusions: • Annual cycle in TTL upwelling 15S-15N primarily driven by sta onary equatorial Rossby-wave interac ons with upper tropospheric winds. • Kelvin waves contribute a smaller downwelling close to the equator that is modulated by QBO winds in the lowermost stratosphere.
Kelvin wave downwelling
Rossby wave upwelling
2006 2007
Note: Small zonal wind biases in models O ~ 5 m/s could lead to differing conclusions.