The simulated spatial patterns of the MMD ensemble mean temperatures agree closely with those of the observations throughout the annual cycle. Generally, the simulations are 1°C to 2°C colder than the European Centre for Medium-Range Weather Forecasts 40-year (ERA40) reanalyses with the exception of a cold bias maximum of 6°C to 8°C in the Barents Sea (particularly in winter/spring) caused by overestimated sea ice in this region (Chapman and Walsh, 2007; see also Section 8.3). Compared with earlier model versions, the annual temperature simulations improved in the Barents and Norwegian Seas and Sea of Okhotsk, but some deterioration is noted in the central Arctic Ocean and the high terrain areas of Alaska and northwest Canada (Chapman and Walsh, 2007). The mean model ensemble bias is relatively small compared to the across-model scatter of temperatures. The annual mean root-mean-squared error in the individual MMD models ranges from 2°C to 7°C (Chapman and Walsh, 2007). Compared with previous models, the MMD-simulated temperatures are more consistent across the models in winter, but somewhat less so in summer. There is considerable agreement between the modelled and observed interannual variability both in magnitude and spatial pattern.
The AOGCM-simulated monthly precipitation varies substantially among the models throughout the year but the MMD ensemble mean monthly means are within the range of different observational data sets. This is an improvement compared to earlier simulations (Walsh et al., 2002; ACIA, 2005), particularly from autumn to spring (Kattsov et al., 2007). The ensemble mean bias varies with season and remains greatest in spring and smallest in summer. The annual bias pattern (positive over most parts of the Arctic) can be partly attributed to coarse orography and to biased atmospheric storm tracks and sea ice cover (see Chapter 8). The MMD models capture the observed increase in the annual precipitation through the 20th century (see Section 3.3).