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 im- proved 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. Unauthenticated | Downloaded 09/27/21 11:10 AM UTC JCLI3713 1APRIL 2006 R I N G E R E T A L . 1303 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 dy- namical 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°). Unauthenticated | Downloaded 09/27/21 11:10 AM UTC 1304 JOURNAL OF CLIMATE VOLUME 19 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°).