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1302 JOURNAL OF CLIMATE VOLUME 19

The Physical Properties of the Atmosphere in the New Hadley Centre Global Environmental Model (HadGEM1). Part II: Aspects of Variability and Regional Climate

M. A. RINGER,G.M.MARTIN,C.Z.GREEVES,T.J.HINTON,P.M.JAMES,V.D.POPE,A.A.SCAIFE, AND R. A. STRATTON Hadley Centre for Climate Prediction and Research, Met Office, Exeter, United Kingdom

P. M. INNESS,J.M.SLINGO, AND G.-Y. YANG Centre for Global Atmospheric Modelling, University of Reading, Reading, United Kingdom

(Manuscript received 17 June 2005, in final form 2 December 2005)

ABSTRACT

The performance of the atmospheric component of the new Hadley Centre Global Environmental Model (HadGEM1) is assessed in terms of its ability to represent a selection of key aspects of variability in the Tropics and extratropics. These include midlatitude storm tracks and blocking activity, synoptic variability over Europe, and the North Atlantic Oscillation together with tropical convection, the Madden–Julian oscillation, and the Asian summer monsoon. Comparisons with the previous model, the Third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3), demonstrate that there has been a considerable increase in the transient eddy kinetic energy (EKE), bringing HadGEM1 into closer agreement with current reanalyses. This increase in EKE results from the increased horizontal resolution and, in combination with the improved physical parameterizations, leads to improvements in the representation of Northern Hemisphere storm tracks and blocking. The simulation of synoptic weather regimes over Europe is also greatly improved compared to HadCM3, again due to both increased resolution and other model developments. The variability of convection in the equatorial region is generally stronger and closer to observations than in HadCM3. There is, however, still limited convective variance coincident with several of the observed equatorial wave modes. Simulation of the Madden–Julian oscillation is improved in HadGEM1: both the activity and interannual variability are increased and the eastward propagation, although slower than observed, is much better simulated. While some aspects of the climatology of the Asian summer monsoon are improved in HadGEM1, the upper-level winds are too weak and the simulation of precipitation dete- riorates. The dominant modes of monsoon interannual variability are similar in the two models, although in HadCM3 this is linked to SST forcing, while in HadGEM1 internal variability dominates. Overall, analysis of the phenomena considered here indicates that HadGEM1 performs well and, in many important respects, improves upon HadCM3. Together with the improved representation of the mean climate, this improvement in the simulation of atmospheric variability suggests that HadGEM1 provides a sound basis for future studies of climate and climate change.

1. Introduction to the interannual and beyond. Investigation of such The thorough assessment of a climate model’s per- variability phenomena helps to shed light on the pro- formance requires an examination, not only of its cli- cesses operating within the model and leads to a much matological mean state, but also of its ability to simu- greater understanding of model systematic errors than late variability across a wide range of time scales en- can be gained by simply inspecting time-averaged compassing the diurnal, through the daily and seasonal, fields. This information can then be fed back into the model development process, leading to refined and improved physical parameterizations. Furthermore, such Corresponding author address: Dr. M. A. Ringer, Hadley Cen- tre for Climate Prediction and Research, Met Office, FitzRoy studies also enable us to assess the suitability of the Road, Exeter, EX1 3PB, United Kingdom. model as a tool for investigating the behavior of the real E-mail: [email protected] atmosphere.

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This is the second of two papers documenting the than HadCM3. These developments are outlined in de- performance of the atmospheric component of the tail in Part I. The atmospheric component includes a new Hadley Centre Global Environmental Model new semi-Lagrangian dynamical core together with in- (HadGEM1); the oceanic and sea ice components are creased horizontal and vertical resolutions, an almost described in Johns et al. (2006) and McLaren et al. completely new suite of physical parameterizations, (2005, personal communication, hereafter MCL), re- and additional processes such as the sulfur cycle and spectively. Martin et al. (2006, hereafter Part I) pre- cloud aerosol effects. The ocean model includes several sented a description of the main features of the model new parameterizations and its resolution is improved, and an evaluation of the mean climatology against vari- especially at low latitudes (Johns et al. 2006). ous observational datasets and meteorological reanaly- As in Part I, our analysis is based on both atmo- ses. It was shown that the new dynamical core, in- sphere-only and fully coupled integrations of HadGEM1. creased resolution, and both new and revised physical The atmosphere-only simulations consist of an en- parameterizations lead to considerable improvements semble of runs forced with observed sea surface tem- compared to our previous model, the Third Hadley peratures (SSTs) and sea ice concentrations from the Centre Coupled Ocean—Atmosphere GCM (HadCM3), second Atmospheric Model Intercomparison Project in the basic model variables (temperature, winds, mois- (AMIP-II) (Gates et al. 1999) from 1979 to 1996; the ture, and surface pressure), in cloud and cloud radiative coupled run used here includes historical time-varying effects, in the structure of the tropopause, and in the forcing due to greenhouse gases, ozone, aerosol emis- transport of moisture and tracers. sions, and land surface/vegetation and extends from Here we consider the representation of several spe- 1860 to 2000. Similar integrations of HadCM3 are used cific aspects of variability in HadGEM1. It is clearly to compare the performance of HadGEM1 with its pre- impossible to document the model’s performance over decessor. all time and space scales relevant to the atmosphere, The evaluation of model variability is made primarily and we have therefore chosen to focus on certain key through comparisons with the European Centre for aspects of the climate in the Tropics and midlatitudes. Medium-Range Weather Forecasts (ECMWF) reanaly- This should provide a useful insight into the model’s sis climatologies, the 15-Yr ECMWF Re-Analysis ability to represent atmospheric variability and, to- (ERA-15) (Gibson et al. 1997), and the 40-Yr ECMWF gether with Part I and Johns et al. (2006), aid the in- Re-Analysis (ERA-40) (Uppala et al. 2005) for the terpretation of forthcoming and future studies and pre- same period as the atmosphere-only integrations. dictions made with HadGEM1 within a context of its Note that, as in Part I, we generally refer to the at- limitations and sensitivities. Specifically, in the extratropics we examine Northern mosphere-only versions of HadGEM1 and HadCM3 Hemisphere storm tracks and blocking, the North At- as the Hadley Centre Global Atmospheric Model lantic Oscillation (NAO), and synoptic variability over (HadGAM1) and the Hadley Centre Atmospheric Europe; while in the Tropics we consider equatorial Model (HadAM3), respectively. waves, the Madden–Julian oscillation (MJO), and the Asian summer monsoon (ASM). As in Part I, we assess both atmosphere-only and fully coupled versions of 3. Extratropical variability HadGEM1 and compare its performance to that of a. Energetics HadCM3. The models are evaluated primarily against reanalyses with some other data sources also being used As discussed in Part I, one of the major develop- where appropriate. ments in HadGEM1 has been the move to a completely The rest of this paper is arranged as follows: section new, semi-Lagrangian dynamical core. This brings im- 2 describes the model experiments and validation portant benefits for climate studies, in particular the datasets; section 3 discusses model energetics and the significantly improved representation of advection, but simulation of extratropical variability; section 4 consid- also has implications for the simulation of the variabil- ers tropical variability; and section 5 presents a sum- ity phenomena discussed below, particularly at low mary of the results and the principal conclusions. horizontal resolutions. Previous studies (Chen et al. 1997; Williamson et al. 1998; Williamson and Olson 2. Model description and experimental details 1994) have demonstrated that semi-Lagrangian dynamical cores tend to have less transient eddy activity HadGEM1 includes improved physical parameter- than equivalent Eulerian dynamics at typical climate izations, increased functionality, and higher resolution model resolutions, (ϳ2.5°).

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Ϫ FIG. 1. Zonal mean transient kinetic energy (m2 s 2) for DJF in HadGAM1 (N96) and differences from HadAM3 (N48) and ERA.

The zonal mean transient eddy kinetic energy (EKE) tal resolution (Martin et al. 2004b). Increasing the hori- examined in this study is defined as zontal resolution leads to a considerable reduction in the transient EKE errors in both HadAM3 (Pope and n 1 Stratton 2002) and HadGAM1; results using the stan- EKE ϭ 0.5ͭ ͚ ͓u Ϫ u͑i͔͒2 ϩ ͓␷ Ϫ ␷͑i͔͒2ͮ, n i dard resolutions of the two models are shown here. Using a dynamical core can help to isolate the influence where of the resolution dependence of the dynamics from feedbacks due to physical parameterizations. A study n 1 of the energetics of the semi-Lagrangian dynamical u ϭ ͚ u͑i͒. n i core used in HadGAM1 (Stratton 2004) showed that it behaves in a different way from the Eulerian dynamical Here, the square brackets indicate the zonal mean, i core used in HadAM3 when changing horizontal reso- is the time index, and n is the total number of fields lution from N48 (2.5° ϫ 3.75°) through N96 (1.25° ϫ for the whole period considered: the fields are aver- 1.875°) to N144 (0.883° ϫ 1.25°). The dynamical core aged every 6 h, corresponding to the frequency of tests in both cases were run using Held–Suarez forcing ERA analyses, and the averaging period is over all 17 (Held and Suarez 1994) and using the same dynamical seasons (1979–95). The EKE will thus also include com- settings (e.g., for diffusion) as those used when running ponents due to interannual variability. Figure 1 shows the full model at the different resolutions. Using the the EKE for the December–February (DJF) season semi-Lagrangian core the model is run with no extra for HadGAM1 and HadAM3. Comparison with the explicit diffusion: the semi-Lagrangian scheme is itself reanalyses shows that, while the EKE is underesti- diffusive, and the amount of diffusion depends partly mated in both models, the error is greatly reduced in on the accuracy of the method used to calculate the HadGAM1, largely as a result of the increased horizon- departure point. There is a large increase in kinetic

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FIG. 2. Kinetic energy spectra of the rotational flow at 200 hPa from dynamical core runs in terms of (a) spherical harmonic and (b) zonal wavenumbers. The solid black lines across the plots in (a) and (b) give the n Ϫ 3 and m Ϫ 3 lines, respectively. energy between N48 and N96 (Stratton 2004). With the and confirms that higher wavenumbers (i.e., smaller Eulerian dynamical core the model requires explicit dif- scales) have less energy at lower resolution. However, fusion. In HadAM3 this was chosen to be of a higher even at quite large scales (zonal wavenumbers greater order at N48 than at N96 and N144 (Pope and Stratton than 3 and spherical wavenumbers greater than 9) the 2002). Comparison of the energy spectra of the Eule- semi-Lagrangian dynamical core at N48 has less energy. rian dynamical core (not shown here) shows less of an At N48 the spectrum for waves greater than n ϭ 20 or increase between N48 and N96. The main difference is m ϭ 20 tends to fall rapidly below the theoretical n Ϫ that the global integrated transient kinetic energy at 3orm Ϫ 3 energy spectrum whereas at higher resolu- N48 in the semi-Lagrangian dynamical core is much tions the spectra only start to fall away at much smaller lower than that in the Eulerian dynamical core at the wavenumbers. The behavior of the Eulerian dynamical same resolution. This suggests that at N48 the semi- core at N48 is close to that of the semi-Lagrangian dy- Lagrangian model will be less able to represent features namics at higher resolution up to about spherical and such as storms than the Eulerian model. zonal wavenumbers 20. Increasing the resolution of the Following Laursen and Eliasen (1989), the scale de- semi-Lagrangian dynamical core from N48 to N96 leads pendence of the total kinetic energy is examined by to an increase in the energy across the spectrum but a considering the kinetic energy spectrum of the rota- further increase to N144 (0.883° ϫ 1.25°) only increases tional flow at 200 hPa, calculated by evaluating the the energy above zonal wavenumber 40, that is, in the streamfunction from the model winds. The global tail of the spectrum. streamfunction field at 200 hPa is then broken down The resolution dependence of the transient EKE has into spherical harmonics, giving spherical harmonic clear consequences for the representation of midlati- wavenumbers (n) and zonal wavenumbers (m). The tude variability in HadGEM1. For example, the re- spherical harmonic decomposition allows the kinetic duced transient EKE at N48 means that at this resolu- energy of the different wavenumbers to be analyzed tion the storm tracks are weaker and the frequency of (e.g., Chen and Wiin-Nielsen 1978). Figure 2 shows the blocking in the Atlantic reduced compared to spectra for HadGAM1 from the semi-Lagrangian dy- HadCM3. At N96 the transient eddy activity is in- namical core at different horizontal resolutions to- creased and these aspects of the simulation are conse- gether with the Eulerian dynamical core results for N48 quently improved.

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b. Northern Hemisphere storm tracks that the Atlantic storm track has limited extension into Europe in both models, a feature which is also seen in Much of the day-to-day variability in the Northern the bandpass-filtered analysis. Some improvement in Hemisphere midlatitudes is determined by cyclones HadAM3 is gained by increasing the horizontal resolu- that originate in the western Atlantic and Pacific tion to N96, but the mean cyclone strength still com- Oceans, bringing precipitation and storms toward Eu- pares less favorably with ERA-40 than HadGAM1. rope and North America along paths usually referred to Track analysis of P in HadGEM1 (Fig. 3c) indicates as storm tracks. Moreover, changes in these storm MSL that the storms at the end of the Pacific storm track are tracks, due to either natural variability or climate much stronger than in either the atmosphere-only change, could potentially lead to significant alterations model or the reanalyses. Other features are consistent to continental climate. Assessing their representation in with the bandpass filtering method: for example, the climate models is thus of great interest. storm activity is slightly farther north over the eastern Two methods are commonly used to analyze the rep- Pacific and is linked to the position of the Pacific jet, resentation of storm tracks in GCMs: 2–6-day bandpass which is located farther north in the coupled model. filtering of 500-hPa geopotential heights (Blackmon The main regions of cyclogenesis occur at the west- 1976) and feature tracking of weather systems (e.g., ern ends of the major storm tracks (Fig. 4a); the Hoskins and Hodges 2002 and references therein). Ap- maxima in eddy activity seen in the bandpass-filtered plication of these two techniques to both atmosphere- analysis are located slightly downstream of these areas. only and fully coupled versions of HadGEM1 and The cyclones decay and fill primarily toward the east- HadCM3 was described in Martin et al. (2004b) and the ern ends of the storm tracks where the levels of eddy results shown to be largely consistent. The bandpass- activity decline. The reanalyses also show distinct areas filtered analysis of the atmosphere-only models indi- of high genesis density over North America and the cates that both HadCM3 and HadGEM1 reproduce central Pacific, the former associated with weak storms well the locations of the major centers of activity (over that track across the continent and decay on the north- the central Pacific and western Atlantic) and the east coast, the latter coinciding with an area of lysis (not maxima in strength compared to reanalyses. The low shown) and indicating a region where cyclones decay horizontal resolution of HadCM3 results in an under- and secondary cyclogenesis takes place. These features estimate of the eddy activity (see above) and a slight are generally well represented in both models (Figs. equatorward bias in the position of the major areas of 4b,d), although some deficiencies in the simulations are activity (Pope and Stratton 2002). These errors are apparent. For example, secondary cyclogenesis over the largely corrected in HadGEM1 although the strength of central Pacific is underestimated, particularly in HadAM3 the eddy activity, while significantly improved over the (and is similarly underestimated in this model at N96), Atlantic, is still underestimated over the Pacific despite as is genesis over the North Atlantic and northern Eur- the increased resolution. Coupling the atmospheric asia. In contrast, cyclogenesis over the Mediterranean is models to an ocean results in weaker eddy activity over well represented in both models. In HadGEM1 (Fig. the Atlantic and slightly increased activity over the Pa- 4c) genesis is concentrated over the western Pacific and cific in both cases. there is little secondary cyclogenesis over the eastern Figure 3 shows the mean cyclone strength anomaly Pacific. It is possible that the cold bias in Pacific SSTs derived from feature tracking of mean sea level pres- (Johns et al. 2006) is limiting secondary development.

sure, PMSL, using the methodology described in Hosk- Further insight can be gained by tracking relative ins and Hodges (2002). The reanalyses (Fig. 3a) indi- vorticity. This reveals different characteristics of the cate that the location of the maximum cyclone strength storm tracks as it is able to identify smaller-scale fea-

is slightly poleward of that in eddy activity (Martin et al. tures than the PMSL analysis and produces correspond- 2004b), a feature reproduced in both atmospheric mod- ingly higher track densities. For example, tracking rela- ␰ els (Figs. 3b,d) that also illustrates the different aspects tive vorticity at 500 hPa ( 500) indicates that the Medi- of the storm tracks highlighted by the two analysis terranean storm track is much more marked and methods. There is a tendency for cyclonic centers at the continues through the Middle East and Asia to the start surface to be displaced poleward of the vortex center, of the Pacific track (Fig. 5a). Most of these storms (and

and this is picked out by feature tracking of PMSL, which also those that have their genesis over Mongolia) decay emphasizes the surface features of the storms. Both the over the western Pacific with further cyclogenesis then mean cyclone strength and the extent of the activity are occurring over the mid-Pacific. At this level the most better represented in HadGAM1 than in HadAM3. intense storms over the Pacific occur at the eastern end However, plots of track density (not shown) suggest of the storm track. Analysis of cyclone speed (not

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FIG. 3. Mean cyclone strength anomaly (hPa) from the analysis of PMSL for DJF for the Northern Hemisphere for (a) ERA-40, (b) HadAM3 (N48), (c) HadGEM1 (N96), and (d) HadGAM1 (N96).

shown) indicates that the features slow down as they (Figs. 5b,d). The increased horizontal resolution leads reach the eastern Pacific and the disturbances becom- to an increase in storm intensities in HadGAM1, which ing large in amplitude and quasi-stationary (i.e., low- are in much better agreement with the reanalyses al- frequency eddies). The features identified in the ERA- though still underestimated compared to ERA-40. Cy- ␰ 40 500 analysis are present in both atmospheric models clogenesis over the mid Pacific (not shown) is also

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6 2 Ϫ1 FIG. 4. Genesis density (10 km month ) from the analysis of PMSL for DJF for the Northern Hemisphere for (a) ERA-40, (b) HadAM3 (N48), (c) HadGEM1 (N96), and (d) HadGAM1 (N96).

much better represented in HadGAM1: in HadAM3 it (Fig. 5c), and the majority of cyclogenesis over the Pa- is underestimated at both N48 and N96 resolutions. In cific occurs farther upstream than in both ERA-40 and HadGEM1 the activity over the eastern Pacific is again the atmosphere-only model. Once again, this is likely to slightly farther north than it is in the reanalyses be linked to the SST errors in the coupled model.

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Ϫ Ϫ FIG. 5. Mean cyclone intensity anomaly (10 5 s 1) from the analysis of 500-hPa relative vorticity in DJF for the Northern Hemisphere for (a) ERA-40, (b) HadAM3 (N48), (c) HadGEM1 (N96), and (d) HadGAM1 (N96). c. Northern Hemisphere blocking enon that is created indirectly by the dynamical and physical processes operating within a climate model. Blocking plays a major role in creating some of the The representation of blocking is therefore a useful test extremes of weather experienced at midlatitudes. It is of a model’s ability to represent the atmosphere real- also an important example of an emergent phenom- istically (e.g., d’Andrea et al. 1998).

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FIG. 6. Northern Hemisphere winter and spring mean large-scale blocking frequency for different models against ERA-40. For HadGAM1, five 17-yr ensemble members and, for HadAM3, six 17-yr ensemble members have been analyzed and the results averaged with the range covered by Ϯ1.64 standard deviations shaded in red and blue, respectively. The percentages refer to the hemispheric mean blocking frequency.

Blocking is identified in the climate model simula- definition of large-scale blocking in Pelly and Hoskins tions and reanalyses using an index based on that of that requires blocking identified by the index to extend Tibaldi and Molteni (1990), which diagnoses blocking over at least 15° of longitude. by the presence of geostrophic easterlies in the region The two preferred areas of Northern Hemisphere of the midlatitude storm track at 50°N. Here, we follow blocking are clearly identified in the reanalyses from Pelly and Hoskins (2003) and use a variable latitude to the winter and spring mean large-scale blocking fre- define the location of the storm track. We also use the quencies (Fig. 6) and correspond to the ends of the

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Atlantic and Pacific storm tracks at around 0° and ing longer rather than the events being more frequent. 150°W, respectively. Although HadAM3 does identify Since this difference is more pronounced for the these two regions, there is too much blocking over the shorter-lived events, it appears to be less a result of Euro–Atlantic region in spring and too little over the increased transient eddy reinforcing of the blocking Pacific in winter compared to ERA-40. Additionally, events but rather that the events are more stable in the the Pacific blocking in HadAM3 in spring occurs more atmospheric flow in the models. Comparison of ERA- to the east compared to ERA-40. The HadGAM1 simu- 40 data for the Euro–Atlantic region with the Northern lations represent a clear improvement over HadAM3 Hemisphere as a whole reveals a similar, though re- in all three of these respects. However, HadGAM1 also duced, difference. It is particularly apparent in spring produces more blocking than both ERA-40 and when the effect is especially pronounced in HadAM3. HadAM3 at around 90°E. This appears to be due to This suggests that the models are exaggerating a re- changes in the storm track behavior. As noted in the gional difference and a seasonal change that does ac- previous section, the Atlantic storm track has limited tually occur in the reanalyses. Overall, the behavior in extension into Europe in HadAM3 and HadGAM1 HadGAM1 compares much more favorably with ERA- and, consistent with this, both models have decreased 40 than HadAM3 in this respect (Hinton 2004). genesis in the northeast Atlantic compared to ERA-40. One of the most notable features of HadGEM1 is the In HadGAM1 this is accompanied by increased genesis reduction in blocking over the winter Pacific in the over the Baltic (Fig. 4d): this lies at the start of the coupled model compared to the atmosphere-only secondary storm track, which tracks farther south of the model. Analysis suggests that this is related to the remain Eurasian track in ERA-40. Hinton (2004) found sponse of the model to the cold bias in equatorial Pa- that this shifted the lysis of the cyclones at 90°E farther cific SSTs. In particular, a similar reduction in blocking south, where it could interact with a weak ridge in the over the Pacific during DJF is found in the atmosphere- stationary wave patterns that preconditions the flow to only model when the blocking frequencies for the be more favorable to blocking. The increase in blocking strong La Niña event of 1988–89 are compared with the in this region is also consistent with the reduced genesis variability in all years (Fig. 7). However, this response density in HadGAM1 at 90°E compared to ERA40 and to the 1988–89 La Niña is not seen in ERA-40. This suggests that there exists a mechanism, only in the HadAM3 (Fig. 4). The coupled model, HadGEM1, per- model, whereby the blocking is sensitive to cold SST forms generally less well than its atmosphere-only anomalies in the equatorial Pacific, and sensitivity tests counterpart: the peak in blocking frequency over the are ongoing to investigate this. This result is consistent Pacific is noticeably reduced although the secondary with Ferranti et al. (1994) but, since winter Pacific blocking over Eurasia in winter is also reduced. blocking in HadAM3 is comparable to HadGEM1 and In HadGAM1 the blocking frequency increases with generally less than in HadGAM1, it is not clear whether increasing horizontal resolution (not shown). This is HadAM3 is similarly sensitive. expected, as synoptic-scale variability should increase with resolution, as was confirmed by the increase in transient EKE discussed in section 3a. In particular, d. The North Atlantic Oscillation both Atlantic and Pacific peaks are in better agreement The North Atlantic Oscillation dominates climate in with the reanalyses at N96 compared to N48. It should the Atlantic region and is responsible for about half of also be noted, however, that HadGAM1 performs bet- the interannual variability in northern European sur- ter than HadAM3 at N48 (Martin et al. 2004b), indi- face temperature and about a third of the variability in cating that the improvements seen in Fig. 6 are not Northern Hemisphere temperature (Rodwell et al. solely the result of the increase in resolution between 1999; Hurrell 1996). Positive NAO implies an enhanced the two models. meridional surface pressure gradient over the North We noted earlier that HadAM3 produces a higher Atlantic and hence stronger westerly winds and greater frequency of blocking in the Euro–Atlantic region in advection of warm oceanic air over the cold winter Eu- spring than either ERA-40 or HadGAM1. Analysis of ropean landmass (Hurrell and van Loon 1997). Recent decay times for short-lived (1–3 days) and long-lived decades have shown a large shift toward positive NAO (6–16 days) large-scale blocking events, in all seasons, that is difficult to reproduce in GCMs (Scaife et al. indicates that events persist longer in the models than 2005), and the question of whether twentieth-century in the reanalyses, particularly in HadAM3 for the increases in the NAO and associated changes in re- shorter-lived events. Consequently the difference in gional surface temperature are a result of anthropo- blocking frequencies is due to individual events persist- genic change or natural variability is currently being

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interannual variability in Atlantic surface pressure in the models. This is in good agreement with the observed fraction of 48% and compares favorably with other models, which range between 40% and 66% (Os- born 2004). The time series in Fig. 8 show that realistic interannual variations in the NAO occur in both HadCM3 and HadGEM1. However, current GCMs have difficulty reproducing variability consistent with observed multidecadal variations in the NAO (Osborn 2004; Kuzmina et al. 2005), and it may be that models produce too little power at multidecadal time scales. Figure 9 shows the power spectrum of NAO variations in HadCM3, HadGEM1, and observations. The spectra are similar in shape with peaks at near biennial and multiannual frequencies. Differences occur, however, at longer time scales: there is some sign of reduced variability at longer time scales, especially in HadCM3, although this is not statistically significant at the 95% level and examination of longer time series is needed for this to be confirmed. The NAO is, nonetheless, well reproduced in both amplitude and spectral characteristics in HadGEM1.

e. Synoptic variability over Europe To assess a climate model’s ability to reproduce aspects of synoptic-scale variability, an objective method

FIG. 7. Plots of DJF mean large-scale blocking frequency (black is required. Clearly, there would be advantages in hav- line) for ERA-40 and HadGAM1 with the results from the 1988– ing a fixed set of typical weather patterns to classify the 89 La Niña years shown in red. Gray shading indicates Ϯ1 stan- actual synoptic situation against, providing that a mean- dard deviation of results from each individual year against the ingful set can be constructed. Probably the best classi- mean over all years. Note that HadGAM1 results are taken from the five members of an ensemble of 17-yr runs. fication system available is the Grosswetterlagen (GWL) catalog, originally conceived by Baur et al. (1944), improved upon and later revised by Hess and debated (e.g., Shindell et al. 1999; Selten et al. 2004). It Brezowsky (1977), recently updated by Gerstengabe et is therefore important that models be able to simulate al. (1999), and since maintained by the German NAO variability accurately if we are to reproduce cli- Weather Service (DWD). The 29 GWL regimes are mate variability and predict climate change around the readily identifiable large-scale circulation patterns in- Atlantic basin. volving most of Europe and the northeast Atlantic, Figure 8 shows the NAO in HadCM3, HadGEM1, with the primary focus on central Europe, as illustrated and observed surface pressure (updated from Basnett in James (2005, unpublished manuscript, hereafter J05). and Parker 1997). The NAO patterns in the models and A daily catalog of subjectively assessed GWLs has been the observations are similar in both structure and am- constructed retrospectively back to 1881. The GWL plitude with a difference of around 10 hPa between the types are defined in Table 1, noting that the terms an- positive and negative centers of the NAO dipole and a ticyclonic and cyclonic refer to the local bias over cen- stronger high-latitude center. The two models compare tral Europe within each clearly defined large-scale pat- well with the observed pressure difference of around 10 tern. hPa although in both cases, and especially at lower lati- Here, pattern correlations are used to create an ob- tudes, the modeled NAO is shifted slightly westward jective GWL catalog from ERA-40 data based on the (similar to the positional bias in the storm tracks shown synoptic principles of Hess and Brezowsky (1977). The in Fig. 3) and the northern center is weaker than ob- fields used for this are geopotential heights at 500 hPa served in HadCM3. The NAO also explains 44% of the (GH500) and PMSL. The first stage is to construct cli-

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FIG. 8. The NAO defined as the first EOF of sea level pressure over the Atlantic region in (top) HadCM3, (middle) HadGEM1, and (bottom) observations. The contour plots show the pattern corresponding to one standard deviation in units of Pa and hPa for model and observations, respectively. Corresponding time series of the principal component are shown to the right for 140 years of model integration and 1871–1998 from observations. mate mean composites of these fields for each subjec- and 15 October, respectively. The summer composites tively determined GWL type, separate for the winter use similar sine-function weighting centered on 15 July. and summer half-years. The winter composites are con- Two nested domains are used for the analysis, the structed using a sine-function weighting that has its smaller being a circle of 1500-km radius surrounding maximum on 15 January and decays to zero on 15 April central Europe while the larger is determined by exam-

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compared with two separate 17-yr periods of ERA-40 and, for comparison, a 51-yr sequence of National Cen- ters for Environmental Prediction (NCEP) reanalyses in Table 2. In general terms, all runs possess a quite realistic distribution of GWLs, with all 29 types occurring with a broadly realistic frequency and no systematic differences being immediately apparent. The great- est deviation from the reanalyzed climate is seen with HadAM3, which has the lowest resolution and is the oldest model in developmental terms analyzed here. To test the significance of any differences in the frequency distributions between the models, the mean frequency of each GWL per calendar month for any particular set has been correlated against those from each FIG. 9. Power spectra of the NAO calculated from the principal components shown in Fig. 8. of the other sets. This tests both the general GWL distribution across the 29 types as well as mean seasonal variations within each type. The correlation coefficients ining the mean pattern variances of the 29 GWLs and resulting from each set of 12 ϫ 29 data point pairs are encloses most of the northeast Atlantic and European shown in Table 3. continent. Daily fields, smoothed by a 5-day binomial When comparing with the 51-yr NCEP dataset, the filter, of the ERA-40 or climate simulation are formed correlation coefficients show a very clear increase from and correlated over both domains with the respective HadAM3 to HadGAM1, confirming that advances in GWL composite fields, giving double weight to grid development and resolution of the atmosphere-only points within the inner domain. The highest mean cor- model have resulted in measurable improvement in relation is then used to select the GWL for each day. modeling European synoptic variability. The correlation Finally, since each regime must persist for at least three coefficients are similar in HadGEM1 and HadGAM1. days, according to the original definitions, events last- When comparing the correlations between the two ing for only one or two days in the initial correlation different ERA-40 periods, all models correlate better calculations are filtered out and systematically replaced with the latter 1979–95 period than with the 1962–78 by the most appropriate alternatives, respectively, period. For the atmosphere-only models this might sug- based on comparing relevant correlation values. gest that the modeled responses to 1979–95 external The mean numbers of days of occurrence of each constraints (such as SSTs) are closer to the 1979–95 GWL, expressed as percentages of the total period, in observed variability than to the observed variability of 17-yr ensemble runs of HadGAM1 (N96), HadAM3 the earlier period. In other words, these models are (N48; both 1979–95), and HadGEM1 (N96; 1928–95) is responding in the correct sense to their external forc-

TABLE 1. Definition of the 29 Grosswetterlagen types.

GWL Definition GWL Definition 01 WA Anticyclonic westerly 16 HB High over the British Isles 02 WZ Cyclonic westerly 17 TRM Trough over central Europe 03 WS South-shifted westerly 18 NEA Anticyclonic northeasterly 04 WW Maritime westerly (block east Europe) 19 NEZ Cyclonic northeasterly 05 SWA Anticyclonic southwesterly 20 HFA Scandinavian high, ridge central Europe 06 SWZ Cyclonic southwesterly 21 HFZ Scandinavian high, trough central Europe 07 NWA Anticyclonic northwesterly 22 HNFA High Scandinavia–Iceland, ridge central Europe 08 NWZ Cyclonic northwesterly 23 HNFZ High Scandinavia–Iceland, trough central Europe 09 HM High over central Europe 24 SEA Anticyclonic southeasterly 10 BM Zonal ridge across central Europe 25 SEZ Cyclonic southeasterly 11 TM Low over central Europe 26 SA Anticyclonic southerly 12 NA Anticyclonic northerly 27 SZ Cyclonic southerly 13 NZ Cyclonic northerly 28 TB Low over the British Isles 14 HNA Icelandic high, ridge central Europe 29 TRW Trough over western Europe 15 HNZ Icelandic high, trough central Europe

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TABLE 2. The mean percentage of days of occurrence of each GWL in HadAM3 (AM3), HadGAM1 (GAM), and HadGEM1 (GEM) compared to two 17-yr periods of ERA-40 and a 51-yr period of NCEP reanalyses.

NCEP ERA ERA AM3 GAM GEM NCEP ERA ERA AM3 GAM GEM GWL 1954–2004 1962–78 1979–95 1979–95 1979–95 1928–95 GWL 1954–2004 1962–78 1979–95 1979–95 1979–95 1979–95 WA 7.1 6.7 9.4 4.9 7.1 7.2 HB 3.5 3.0 3.7 2.0 3.4 2.9 WZ 9.9 10.3 10.4 8.5 10.0 9.9 TRM 3.6 3.8 3.8 3.5 3.9 3.2 WS 3.6 3.0 3.5 6.0 3.9 3.8 NEA 2.5 2.4 2.4 1.7 2.0 1.7 WW 5.7 4.5 5.9 9.2 6.5 5.1 NEZ 2.0 2.7 1.4 2.6 2.4 1.5 SWA 4.5 4.3 5.9 3.3 3.2 4.0 HFA 2.3 2.0 2.1 1.7 1.9 1.5 SWZ 3.9 3.8 3.3 4.6 4.2 4.2 HFZ 1.9 2.8 1.5 4.2 2.1 1.2 NWA 4.4 4.7 4.3 2.3 5.7 6.2 HNFA 1.6 1.3 1.3 2.3 1.7 2.0 NWZ 5.9 5.6 5.6 3.7 6.4 6.8 HNFZ 1.6 1.9 1.2 3.2 1.3 1.3 HM 4.4 4.4 4.0 3.4 3.3 4.1 SEA 1.9 2.0 1.5 1.8 1.3 1.6 BM 5.9 5.7 6.9 3.9 6.0 6.6 SEZ 1.9 2.7 1.3 3.2 1.7 2.1 TM 2.2 1.9 2.0 4.0 2.1 1.9 SA 1.5 1.3 1.9 1.7 1.5 2.0 NA 1.5 1.4 1.7 1.8 1.3 1.3 SZ 2.1 2.3 1.7 2.4 1.7 2.2 NZ 2.6 2.4 2.1 1.8 3.3 3.0 TB 2.9 2.7 2.8 4.2 3.1 2.5 HNA 3.0 3.0 3.2 1.9 3.2 3.6 TRW 3.1 3.6 2.9 2.7 2.5 3.4 HNZ 3.1 3.8 2.3 3.6 3.3 3.4

ings. However, HadGEM1 also exhibits this difference 4. Tropical variability across the 1928–95 period analyzed, even though the a. Convectively coupled equatorial waves ocean surface is not constrained in the same way as in the atmosphere-only models. Hence, one would not ex- Tropical convection and equatorial waves, and their pect it to correlate better with either period from ERA- coupled behaviors, are fundamental components of the 40. This may indicate that the 1962–78 period was tropical climate system. A substantial fraction of the rather unusual climatologically. Meanwhile, the corre- large-scale variability in convection at time scales less lations between either ERA-40 set and NCEP are simi- than 30 days is associated with equatorial waves (e.g., lar, suggesting, in turn, that the 1979–95 period may Redelsperger et al. 1998); it is therefore important to also have been rather unusual, albeit very different examine their representation in climate models. from 1962–78. These results highlight the need for long Here, we examine the variability of tropical convec- comparative data periods, owing to the substantial lev- tion in HadGAM1 and HadAM3 through comparisons els of interannual and even interdecadal variability in with high temporal resolution satellite observations of

GWL statistics. infrared window brightness temperatures, Tb [Cloud In summary, HadGAM1 (and HadGEM1) is capable Archive User Service (CLAUS); Hodges et al. 2000]. of reproducing synoptic variability over Europe that is The analysis is for one summer (May through October comparable with reality, at least in terms of weather 1992) using 6-hourly sampled observations and model regime distributions and shows a significant improve- fields. Comparisons with other years indicate that this ment over HadAM3. Further results and full discussion particular season is generally representative of the be- of this work can be found in J05. havior of both models.

TABLE 3. Matrix showing the mean correlation coefficients comparing respective climate mean monthly GWL totals for various pairs of model/observational datasets, as labeled. Each correlation involves 29 GWLs ϫ 12 months data points and indicates the similarity of both the distribution and seasonal cycle of GWL occurrence.

NCEP ERA-40 ERA-40 HadAM3 HadGAM1 HadGEM1 1954–2004 1962–78 1979–95 1979–95 1979–95 1928–95 NCEP 1954–2004 0.815 0.854 0.545 0.745 0.743 ERA-40 1962–78 0.815 0.559 0.413 0.544 0.584 ERA-40 1979–95 0.854 0.559 0.468 0.685 0.687 HadAM3 1979–95 0.545 0.413 0.468 0.582 0.481 HadGAM1 1979–95 0.745 0.544 0.685 0.582 0.860 HadGEM1 1928–95 0.743 0.584 0.687 0.481 0.860

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FIG. 10. (left) Seasonal mean and (right) total standard deviation of Tb (K) for (a),(b) observations, (c),(d) HadAM3, and (e),(f) HadGAM1 for May–October 1992.

The mean and total standard deviation of the Tb sociated with transient, propagating convection the fields are shown in Fig. 10. The brightness temperature standard deviation of Tb is separated into westward and is a useful index of convection and high cloud and the eastward moving components in a zonal wavenumber ␻ ϭ Ϫ ␻ ϭ generally improved simulation of the mean Tb field (k) and frequency ( ) domain with k 2 10 and over the Indian and Pacific Oceans in HadGAM1 is 3 Ϫ 30 days (Fig. 11). Although the HadAM3 simula- consistent with the improved representation of long- tion of off-equatorial (5°–20°) convective variability is wave cloud forcing and International Satellite Cloud quite reasonable, the model performs less well over the Climatology Project (ISCCP) high cloud types in these equator (5°N–5°S) where the variability is much lower areas (Part I). The spatial patterns of the mean fields than observed, especially for the eastward moving, suggest that both models simulate the mean geographi- equatorially centered convection over the Indian cal distribution of tropical convection reasonably well. Ocean–western Pacific region. Averaged over the Consistent with the observations, the areas of largest whole equatorial band between 5°N and 5°S the vari- standard deviation in HadGAM1 are coincident with ance in HadAM3 is only about 39% and 65% of that the areas of strongest convection, indicated by the low- observed for the eastward and westward moving com- est mean values of Tb. The variance in HadGAM1 is, ponents, respectively. The variability in HadGAM1, on however, about 30% greater than the observed value; the other hand, is larger than observed for both west- this contrasts with the HadAM3 simulation, which in- ward and eastward moving convection, consistent with dicates weaker variance over the Indian Ocean and the overestimate in the total standard deviation noted western Pacific convection regions and higher than ob- above. served variance over the nonconvective areas. The spatial distribution of the variance associated To show the fraction of the large-scale variability as- with westward moving convection in HadGAM1 is very

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FIG. 11. Standard deviation of Tb (K) for (left) westward and (right) eastward moving components in the zonal wavenumber–frequency domain for (a),(b) observations, (c),(d) HadAM3, and (e),(f) HadGAM1 for May– October 1992. similar to that observed; the maxima lying off the equa- with various theoretical equatorial modes: equatorial tor are associated with Rossby and mixed Rossby– Rossby (R), mixed Rossby–gravity (MRG), Kelvin, and gravity waves. For eastward moving convection, how- inertio–gravity (IG) waves. It is clear, however, that ever, the modeled variance is less confined to the equa- both HadAM3 and HadGAM1 contain very limited torial region than it is in the observations, where the variability corresponding to these equatorial wave maxima are centered on the equator and are associated modes. Although there is variance associated with with the Kelvin wave. The simulation of the variance Rossby waves, variance related to equatorial Kelvin, associated with the eastward moving, equatorially cen- MRG, and IG waves is almost entirely absent from the tered convection over the Indian Ocean–west Pacific two models. Consistent with the strong variance in region is, nonetheless, much more realistic in HadGAM1 HadGAM1 (Fig. 10), the power spectra without remov- than in HadAM3. ing the background (not shown) indicate that the mod-

The organization of convection by equatorial waves eled Tb in HadGAM1 has stronger power than ob- is examined further by computing the space–time spec- served. This power is, however, more like white noise, tra of Tb (in the zonal wavenumber–frequency domain) is seen everywhere and is not organized in the wave- between 20°N and 20°S for the observations and model number–frequency domain as it is in the observations. simulations (Fig. 12). As described by Wheeler and More detailed examination of the horizontal and ver- Kiladis (1999) and Yang et al. (2003), once the back- tical structures of the equatorial waves in the dynamical ground red spectrum is removed, it is evident from the fields of HadGAM1 (using the method of Yang et al. observations that tropical convection is organized on 2003) indicates that the model overestimates Kelvin preferred space and time scales and that these coincide wave activity in the upper troposphere, particularly

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FIG. 12. Zonal wavenumber–frequency power spectra divided by background power of the symmetric (i.e., odd meridional mode number, n) and antisymmetric (even n) components OLUME of Tb for May–October 1992. (a),(b) Observations, (c),(d) HadAM3, and (e),(f) HadGAM1. The monthly mean has been removed (to remove the seasonal cycle) and the power averaged over 20°N–20°S. Superimposed thin lines in (a) and (b) are the dispersion curves of the odd and even n equatorial waves for the equivalent depths of h ϭ 8, 12, 24, 48, and Ϫ 1 90 m. The curves have been Doppler-shifted with a 3 m s easterly basic state. 19 1APRIL 2006 R I N G E R E T A L . 1319 over the Indian Ocean, but captures well the activity of westward moving MRG waves and mode-1 Rossby waves (characterized by off-equatorial meridional wind variability). However, the activity is too strong in both of these latter two cases, which may be contributing to the appearance of westward propagating features at intraseasonal time scales in the diagnosis of the MJO (see below). b. The Madden–Julian oscillation The variability of the tropical atmosphere–ocean system on intraseasonal time scales is dominated by the Madden–Julian oscillation, which is characterized by an eastward propagation of anomalies in deep convection from the Indian Ocean to the western Pacific. Analysis of the index defined by Slingo et al. (1999), based on 20–100-day filtered zonal mean zonal wind, indicates that the MJO is much more active in HadGEM1 than in HadCM3 (Fig. 13). The mean amplitude of the index is increased (and is actually slightly higher than in ERA), and the model reproduces the large interannual variability seen in the reanalyses, with notable years of strong activity. Furthermore, the seasonality of the MJO, being most active during northern winter and spring, is better captured in HadGEM1 than in HadCM3. The eastward propagation of convection associated with the MJO is often poorly represented in climate

FIG. 14. Lag–lead correlations of bandpass-filtered (20–100 day) OLR with an upper-tropospheric velocity potential index defining the active phase of the MJO at 90°E. (a) Observations, (b) HadCM3, and (c) HadGEM1. The contour interval is 0.1 and negative correlations are shaded.

models (Slingo et al. 1996; Sperber et al. 1997). Figure 14 shows the lag–lead correlations between outgoing longwave radiation (OLR) along the equator and an index of the active phase of the MJO at 90°E. The observations (Fig. 14a) show clear evidence of the propagation of convection from the Indian Ocean about 10–15 days prior to the active phase of the MJO at 90°E, followed by slightly faster propagation out into the West Pacific in the subsequent 10–20 days. There is also a clear signal of suppressed convection over the Indo–Pacific warm pool 20 days before and 20 days after the enhanced convection. This eastward propaga- FIG. 13. Interannual variability in MJO activity, based on an activity index derived from the zonal mean of the upper- tion is not well captured by HadCM3 (Fig. 14b; Inness tropospheric zonal wind, for (top) HadCM3 (red line) and and Slingo 2003): there is only weak evidence of en- HadGEM1 (black line) and (bottom) for ERA-40. hanced convection over the Indian Ocean prior to

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Fig 13 live 4/C 1320 JOURNAL OF CLIMATE VOLUME 19 the active phase of the MJO at 90°E, and the sup- c. The Asian summer monsoon and its variability pressed convection prior to and after the MJO is not The Asian summer monsoon (ASM) is one of the nearly as marked as in the observations. The results major components of the tropical circulation, on which from HadGEM1 (Fig. 14c) suggest a significant im- the economies and livelihood of the populations of In- provement in the simulation of the MJO, consistent dia and Southeast Asia depend heavily. Simulation of with the increased MJO activity. Although the signal of this system and its variability remains a significant chal- enhanced convection over the Indian Ocean is still lenge for many GCMs. As our understanding of this rather weak, the propagation out into the West Pacific, complex phenomenon improves, it is increasingly clear albeit slower than in the observations, is better simu- that atmosphere–ocean interactions have an important lated. Furthermore, the suppression of convection be- role in moderating monsoon variability on a range of fore and after the MJO active phase is more pro- time scales. The relationship between interannual vari- nounced than in HadCM3. Overall, the spatial and ability of the monsoon and the El Niño–Southern Os- temporal structure of the correlations between con- cillation (ENSO) has long been a subject for research vection and MJO activity are much better captured in (see Lau and Nath 2000). However, there is increasing HadGEM1. Hovmöller plots of 20–100-day-filtered ve- interest in the role of the Indian Ocean in monsoon locity potential, OLR, and precipitation (Martin et al. variability as well as its relationship to other tropical 2004a) illustrate such eastward propagating events but areas. also show some westward propagating signals in the Examination of monsoon variability in both atmo- West Pacific. This type of signal was also seen in sphere-only models and coupled models allows any HadCM3 and may be related to the excessive equato- feedbacks on the ocean through the coupled system to rial wave activity over the “Warm Pool” discussed be separated from the forcing of the monsoon by the above. sea surface temperature. We are fortunate to have at- The lag–regressions of OLR and 850-hPa winds onto mosphere-only and coupled versions of the same model the 200-hPa velocity potential at 0°,90°E also confirm available in both HadAM3/CM3 and HadGAM1/ the slightly slow nature of the propagation of the MJO GEM1. Therefore, in this section we examine the mon- in HadGEM1 (Fig. 15), in comparison with HadCM3 soon climatology and its interannual variability in all (Inness and Slingo 2003). In HadGEM1, the OLR sig- four cases. nal seems to slow down over the Maritime Continent Previous versions of the Hadley Centre climate and is only just emerging into the West Pacific on days model have produced a reasonably good simulation of ϩ18 and ϩ24. At this stage the westerly wind burst the ASM, although the monsoon strength (in terms of extends through the region of enhanced convection, both circulation and precipitation) has been rather consistent with observations. Overall, the spatial pat- overestimated and the onset occurs slightly early in tern of the convection and wind anomalies associated comparison with observations (Martin 1999; Martin et with the eastward passage of the MJO is captured bet- al. 2000; Martin and Soman 2000). The low-level winds ter in HadGEM1 than in HadCM3. The convective sig- in HadGAM1 are improved compared with HadAM3, nal shows less of a tendency to split north and south of while those at upper levels are worse. In particular, the the equator and is about 25% stronger. The zonal wind ASM circulation is weaker and more realistic at 850 perturbations associated with the MJO are stronger in hPa but fails to represent the upper-level easterly jet HadGEM1 particularly along the equator, suggesting over the monsoon region (Fig. 16). In addition, the that there may be more stochastic forcing of El Niñoby westerly monsoon jet at 850 hPa extends too far out the MJO in this model: this is presumably related to the into the western Pacific. This is associated with changes fact that the whole MJO convective signal is stronger. in the nature of convection over Indonesia. A general The large spatial scale of the MJO means that its simu- lack of convection over Indonesia (see Part I) is asso- lation by GCMs is likely to rely not only on the speci- ciated with a reduction in subsidence over the neigh- fication of the model physics (primarily the convective boring region to the north, allowing convection to in- parameterization) but also on the interactions between crease over the South China Sea, the Philippines, and the physics and dynamics. Due to the many changes western Pacific, accompanied by low-level convergence to both of these aspects between HadCM3 and and a strengthening of the westerly flow into this re- HadGEM1 the reasons for the improvement of the gion. There is a corresponding increase in rainfall over MJO in HadGEM1 are not immediately obvious. A the western Pacific, while that over the Indian region is more in depth analysis of this aspect of the model’s reduced. Similar monsoon circulations are seen in the performance will form the basis of future work. coupled models, HadCM3 and HadGEM1 (not shown)

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FIG. 15. Evolution of the MJO in HadGEM1 based on lead/lag regression of OLR (shading) and 850-hPa winds with respect to the active phase of the MJO at 90°E. as occur in their atmosphere-only counterparts, but cific in the atmospheric components (see Martin et al. more rainfall occurs over Indonesia in both coupled 2006 for further discussion). models as a result of a warm SST bias in the sea areas The interannual variability of the ASM is measured around the Maritime Continent. This evolves in re- using EOF analysis of June–September seasonal mean sponse to the lack of convection over Indonesia and 850-hPa wind anomalies. Such analysis of ERA (Anna- excessive easterly wind stresses over the equatorial Pa- malai et al. 1999) and NCEP–National Center for At-

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FIG. 16. Horizontal winds at (left) 850 and (right) 200 hPa for June–September from (top) HadAM3, (middle) HadGAM1, and (bottom) ERA. mospheric Research (NCAR) reanalyses (Molteni et al. whole region at 15°N with two centers of cyclonic/ 2003) shows that almost half of the total variance is anticyclonic circulation in the northwest Bay of Bengal divided nearly equally between the first two modes and the South China Sea and alongshore wind anoma- (Figs. 17a,b). One consists of easterly/westerly 850-hPa lies off the coast of Sumatra. wind anomalies across East Asia and southerly/ HadAM3 and HadGAM1 produce very similar dom- northerly anomalies over the eastern Indian subconti- inant modes of variability (Figs. 17c,d). This mode re- nent with increased convergence/divergence over Indo- produces many of the features of the second mode from nesia, western India, and the Arabian Sea; the other is the reanalyses, the main exception being the anomalies associated with westerly/easterly anomalies across the off Sumatra. However, this dominant mode explains at

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FIG. 17. Leading EOFs of seasonal (June–September) 850-hPa wind anomalies from (top) ERA, (middle) HadAM3 and HadGAM1, and (bottom) HadCM3 and HadGEM1. The percentages of variance explained by these EOFs are as follows: ERA (EOF1, 24%; EOF2, 21%), HadAM3 (38%), HadGAM1 (32%), HadCM3 (30%), and HadGEM1 (25%). least 30% of the variance in each model (38% in common features of atmosphere-only models; they HadAM3 and 32% in HadGAM1), with the second have also been seen in more than one version of the EOF in both models explaining around 17% of the vari- ECMWF model (Molteni et al. 2003; Ferranti et al. ance and bearing little resemblance to the other mode 1997), although in those cases the percentage of vari- from the reanalyses. The characteristic dominant mode ance explained by this mode was greater than 50%. and the high percentage of variance that it explains are The coupled models, HadCM3 and HadGEM1, pro-

Unauthenticated | Downloaded 09/27/21 11:10 AM UTC 1324 JOURNAL OF CLIMATE VOLUME 19 duce a similar dominant mode to their atmosphere-only due to the increased horizontal resolution; improve- counterparts, but the dominance of this mode is re- ments to the model’s physical parameterizations also duced and both models now reproduce the alongshore make an important contribution. In the fully coupled anomalies off Sumatra (Figs. 17e,f). These are thought model our analysis suggests that the cold bias in Pacific to be associated with the development of the Indian SSTs (Johns et al. 2006) leads to certain degradations in Ocean dipole, or zonal mode (e.g., Saji et al. 1999). performance: limited secondary cyclogenesis over the Their appearance in the coupled versions of these mod- central Pacific; eastern Pacific storm track activity that els suggests that this is a coupled ocean–atmosphere is too far north (and is linked to the location of the phenomenon. Pacific jet); and a dramatic loss of blocking over the HadAM3 shows significant teleconnections between Pacific during winter. the dominant mode of interannual variability and SSTs A particularly novel study is the evaluation of syn- in the central and eastern Pacific. We find that wind and optic variability over Europe, which assesses the mod- precipitation anomalies in El Niño years are very simi- els’ ability to reproduce the observed distribution of lar to the dominant mode of variability in this model. objectively derived weather regimes corresponding to However, these anomalies are not very realistic com- specific synoptic situations. This analysis demonstrates pared with observations, suggesting that HadAM3 re- that both the atmosphere-only and fully coupled ver- sponds too strongly to both local and remote tropical sions of HadGEM1 are capable of reproducing realistic SST forcing. The teleconnections are rather weak in distributions of these weather regimes. Furthermore, HadGAM1, suggesting that internal variability may be the performance of the model in this respect is signifi- prevalent in this model. However, anomalies in El Niño cantly improved compared to HadCM3, again due both years in HadGAM1 are quite similar to those observed, to the increased resolution and other model develop- suggesting that strong SST forcing can outweigh the ments. internal variability on some occasions. Similar analysis The distribution and variability of convection in the of HadGEM1 shows even weaker monsoon–ENSO deep Tropics are improved in HadGEM1, although the teleconnections. This is related to poor representation variability is overestimated, especially that associated of the overall atmospheric response to tropical SST with westward moving disturbances. More detailed ex- variability, including El Niño, in the coupled model. amination of equatorial wave modes indicates that, in This aspect is discussed further in Johns et al. (2006). common with its predecessor, HadGEM1 contains very limited variability corresponding to the observed 5. Summary and conclusions modes and suggests that some may be almost entirely absent. Analysis of the Madden–Julian oscillation The performance of the atmospheric component of indicates that this important tropical phenomenon is the new Hadley Centre climate model, HadGEM1, has depicted with much greater realism in HadGEM1 com- been assessed by considering its ability to represent sev- pared to HadCM3. Both the mean activity and interan- eral aspects of variability and regional climate. This nual variability are increased and the eastward propa- assessment complements the evaluation of the model’s gation from the Indian Ocean to the western Pacific is mean climatology presented in Martin et al. (2006) and improved considerably. the descriptions of the oceanic and sea ice components Some aspects of the climatology of the Asian summer of HadGEM1 presented in Johns et al. (2006) and monsoon are improved in the atmosphere-only version MCL, respectively. of HadGEM1, although the upper-level winds are too The transient eddy kinetic energy (EKE) in HadGEM1 weak and the precipitation distribution over the west- is increased compared to HadCM3. This considerably ern Pacific and Indonesia is less well simulated than in reduces the error with respect to reanalyses and is HadCM3. The two models show rather similar domi- largely a result of the doubling of the horizontal reso- nant modes of monsoon interannual variability. How- lution, which increases from N48 (2.5° ϫ 3.75°)toN96 ever, in the case of HadCM3, the variability is strongly (1.25° ϫ 1.875°). This increase in the transient EKE linked to SST forcing, while internal variability domi- then makes a significant contribution to the improve- nates in HadGEM1. In spite of this, strong SST forcing ments in the representation of Northern Hemisphere can outweigh the internal variability in HadGEM1 on midlatitude variability seen in atmosphere-only integra- some occasions; the wind and precipitation anomalies tions: the storm tracks are strengthened, as are more in El Niño years are then similar to those observed. complex features such as secondary cyclogenesis, and Thus, in terms of the phenomena considered here, the simulation of blocking is generally improved. It the atmospheric component of HadGEM1 performs should be noted that these developments are not solely well and in many important respects improves upon its

Unauthenticated | Downloaded 09/27/21 11:10 AM UTC 1APRIL 2006 R I N G E R E T A L . 1325 predecessor, HadCM3. This is consistent with both the der Grosswetterlagen Europas 1881–1998 nach P. Hess und assessment of the model’s mean climatology (Martin et H. Brezowsky. 5. Aufl. – Potsdam-Institute f. Klimafolgen- al. 2006) and the quasi-objective measure of perfor- forschung, Potsdam, Germany, 138 pp. Gibson, J. K., P. Kallberg, S. Uppala, A. Hernandez, A. Nomura, mance described in Johns et al. (2006). Although some and E. Serrano, 1997: ERA description. ECMWF Re- deficiencies remain to be resolved, most notably in the Analysis Project Report Series 1, ECMWF, Reading, United coupled model’s simulation of the tropical climate, the Kingdom, 74 pp. combined effect of the many advances in HadGEM1 is Held, I. M., and M. J. Suarez, 1994: A proposal for the intercom- to provide a more realistic representation of the physi- parison of the dynamical cores of the atmospheric circulation model. Bull. Amer. Meteor. Soc., 75, 1825–1830. cal processes operating in the present-day climate and Hess, P., and H. Brezowsky, 1977: Katalog der Grosswetterlagen should lead to more reliable predictions of climate Europas 1881–1976, 3. Verbesserte und ergänzte Aufl. Ber- change. ichte des Deutschen Wetterdienstes 113. Offenbach am Main, Germany. Acknowledgments. The development of HadGEM1 Hinton, T. J., 2004: The representation of Northern Hemisphere represents the work of a large number of people, par- blocking in Hadley Centre climate models. M.Sc. disserta- tion, University of Reading, 84 pp. ticularly those working in “Tiger Teams,” to whom the Hodges, K. I., D. W. Chappell, G. J. Robinson, and G. Yang, authors are indebted. We thank Kevin Hodges for sup- 2000: An improved algorithm for generating global window plying the TRACK analysis software. This work was brightness temperatures from multiple satellite infrared im- supported by the U.K. Government Meteorological agery. J. Atmos. 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