Simulation of the second half of the 20th Century using the MGO AGCM P.V. Sporyshev, V.P. Meleshko, T.V. Pavlova Voeikov Main Geophysical Observatory, St.Petersburg, Russia

AMIP-II version of the MGO AGCM Principal approach spectral representation of the main prognostic variables , D, T, q, ln p Model configuration horizontal resolution T30 vertical resolution 14 σ-levels of unequal thickness Parameterization of physical processes spectral treatment of solar and infrared radiative transfer diurnal cycle included vertical turbulent heat, moisture, and momentum exchange Tiedtke convection cloud prediction and precipitation formation gravity wave drag forcing heat and water transfer in 4-layer soil of 3 m depth

Main references Shneerov B.Ye., V.P.Meleshko, V.A.Matyugin, P.V.Sporyshev, T.V.Pavlova, S.V.Vavulin, I.M.Shkol’nik, V.A.Zubov, V.M.Gavrilina, V.A.Govorkova, 2001: The up-to-date version of the MGO global model of general circulation of the atmosphere (version MGO-2). MGO Proceedings, No.550, Shneerov,B.Ye., V.P.Meleshko, V.P.Sporyshev, V.A.Matyugin, T.V.Pavlova, V.M.Gavrilina and V.A.Govorkova, 1999: MGO Atmospheric Global Circulation Model: Current state. MGO Proceedings, No.547, Shneerov, B.E., V.P. Meleshko, A.P. Sokolov, D.A. Sheinin, V.A. Lyubanskaya, P.V. Sporyshev, V.A. Matyugin, V.M. Kattsov, V.A. Govorkova, and T.V. Pavlova, 1997: MGO Global Atmosphere General Circulation and Upper Layer Ocean Model. MGO Proceedings, No.544, Detailed description

Accuracy of the climate simulated by the AMIP-II models Surface Air TemperaturePrecipitation Global RMS (green) and mean (red) differences were averaged over four seasons. Observational data are from Jones et al. (1999), and Xie and Arkin (1997).

Accuracy of the climate simulated by the AMIP-II models Net Radiation (TOA)Net Radiation (Surface) Global RMS (green) and mean (red) differences were averaged over four seasons. Observational data are from Barkstrom et al. (1989), and Darnell et al. (1996).

Experiment design The MGO AGCM at T30L14 resolution was integrated for the period 1949 to 1999 Eleven model simulations with different initial conditions were performed The model was forced by the HadISST1.1dataset (Rayner et al., 2002) For the Caspian and Aral seas, climatic sea temperature and ice cover were used Observed change of greenhouse gazes (CO 2 equivalent) was used. CO 2 concentration was 300 ppmv at January 1949, and it linear increased by 3 ppmv per year Radiative forcings from changes of ozone and volcanic aerosols were not included

Datasets used in the analysis NCEP Reanalysis (Kalnay et al., 1996) CRU surface Air Temperature and Precipitation (Jones et al.,1999; Hulme et al., 1998) Climatologically Aided Interpolation (CAI) of Terrestrial Air Temperature and Precipitation (Willmott and Robertson, 1995; Legates and Willmott, 1990)

Time series of surface air temperature anomalies over continents Globe R=0.88** Northern Hemisphere R=0.87** Tropics (30ºN - 30ºS) R=0.92** Middle Latitudes of NH (60ºN - 30ºN) R=0.64** Annual anomalies of land-surface air temperature (°C) for the period 1950 to 1999, relative to 1961 to The data are from Willmott and Robertson (1995) (blue curve), Jones et al. (1999) (green curve), Kalnay et al. (1996) (violet curve), MGO model ensemble (black curve). The shading shows the scatter of 75% of mean model values. R is the correlation between the blue and black curves. Stars indicate correlations significant at the level of 5% (*) and 1% (**).

Surface air temperature trends (°C/century) NCEP Reanalysis CAI of Terrestrial Air Temperature MGO Model Ensemble Annual surface air trends for the period 1950 to 1999 (°C/century). The data are from Kalnay et al. (1996), Willmott and Robertson (1995), and MGO model ensemble.

Significance levels of the trend coefficients (%) MGO Model Ensemble Experiment 5 NCEP Reanalysis

Time series of precipitation anomalies over continents Globe R=0.58** Northern Hemisphere R=0.55** Tropics (30ºN - 30ºS) R=0.78** Middle Latitudes of NH (60ºN - 30ºN) R=0.20 Annual anomalies of land-precipitation (mm/day) for the period 1950 to 1999, relative to 1961 to The data are from Legates and Willmott (1990) (blue curve) and MGO model ensemble (black curve). The shading shows the scatter of 75% of mean model values. R is the correlation between the blue and black curves. Stars indicate correlations significant at the level of 5% (*) and 1% (**).

Precipitation trends (mm/day per century) CAI of Terrestrial Precipitation MGO Model Ensemble Annual land-precipitation trends for the period 1950 to 1999 (mm/day per century). The data are from Legates and Willmott (1990), and MGO model ensemble.

Significance levels of the trend coefficients (%) CAI of Terrestrial Precipitation MGO Model Ensemble

Teleconnection patternIndexElementDefinition The Southern OscillationSOSLP * (18  S, 149  W)  (12  S, 131  E) The North Atlantic OscillationNAOSLP * AVER(60  N ~ 70  N, 0 ~ 45  W)  AVER(35  N ~ 45  N, 0 ~ 45  W) The Tropical Atlantic Oscillation TAOSLP * (10  S, 5  W)  (20  N, 25  W) The North Pacific patternNPSLP * WAVER(30  N ~ 65  N, 160  E ~ 140  W) The Pacific/North American pattern PNAH500 * ((20  N, 160  W)  (45  N, 165  W) + (55  N, 115  W)  (30  N, 85  W))  2 The Eurasian patternEUH500 * (  (55  N, 20  E) + (55  N, 75  W)  2  (40  N, 145  E))  2 The Western Pacific patternWPH500 * (60  N, 155  E)  (30  N, 155  E) Here SLP* and H500* are the normalized SLP and H500, respectively. WAVER and AVER represent the regional average with and without area weight, respectively. The table is based on Hu et al. (2001).

The Southern Oscillation (SO); R = 0.81 ** The Tropical Atlantic Oscillation (TAO); R = 0.75** The Pacific/North American pattern (PNA); R = 0.50 ** Time series of the teleconnection patterns indices were calculated for the NH winter. The data are from Kalnay et al. (1996) (green curve) and MGO model ensemble (black curve). R is the correlation between the green and black curves. Stars indicate correlations significant at the level of 5% (*) and 1% (**).

The North Pacific pattern (NP); R = 0.34 * The Western Pacific pattern (WP); R = 0.32* The North Atlantic Oscillation (NAO); R = -0.01The Eurasian pattern (EU); R = 0.05 Time series of the teleconnection pattern’s indices were calculated for the NH winter. The data are from Kalnay et al. (1996) (green curve) and MGO model ensemble (black curve). R is the correlation between the green and black curves. Stars indicate correlations significant at the level of 5% (*) and 1% (**).

The Arctic Climate Change (90°N-60°N) CAI of Terrestrial Air Temperature MGO Model Ensemble The Arctic Air Temperature R=0.64** The Arctic Precipitation R=0.22

Precipitation over the Volga River watershed The seasonal circle of the precipitation over the Volga River watershed reproduced by the AMIP-II models and MGO model ensemble. The observational data are from Shver (1976).

The Climate Change over the Volga River watershed Time series of the annual mean temperature Time series of the annual Volga discharge over the Volga watershed (°C)(km 3 /year) The time series of the annual surface air temperature over the Volga watershed, and the annual Volga discharge. The observational data are from Jones et al. (1999) and Mescherskaya et al. (1994).

Conclusions In this study, we analysed the MGO model climate and climate variability in relation to observations and reanalysis datasets. We focused on the model ability to reproduce the observed trends in surface air temperature and precipitation. The model results are consistent with the observations. In particular, the model realistically reproduces the observed temperature rise over continents. The precipitation trends are statistically insignificant over most of the continents with exception for Central Africa and Northern Greenland. But the model trends resemble that observed in the Tropics. An estimation of the model accuracy in simulation of the main Northern Hemisphere teleconnection patterns in the pressure fields was performed as well. The model realistically reproduces the dynamics of the oscillation systems in the Tropics, but it is not so good in the Middle Latitudes. Particular attention was given to the regions of special interest (such as the High Latitudes and the Caspian Sea drainage basin). The model realistically reproduces the observed temperature increase in the regions. But it could not catch the observed regional precipitation variations.