The tenth IMSC, Beijing, China, 2007 - International Meetings on ...

2003) with a series of numerical simulations performed by a coupled ocean-atmosphere
general circulation model (CGCM) called by MIROC. Observationally constrained attributable
warming in the 20th century is similar to that estimated with the other CGCMs (Stott et al.,
2006) if the historical changes in carbonaceous aerosols do not considered in MIROC as in the
other CGCMs. When we consider historical changes in carbonaceous aerosols, on the other
hand, observationally constrained attributable warming increases and uncertainties in
attributable anthropogenic signals become larger. Scaled future prediction gets more
uncertainties when we use scaling factors estimated with carbonaceous aerosol forcings. This
implies that the other process, such as carbon cycle, atmospheric chemistry, dynamical
vegetation, etc. might also have significant impact on the past attributable warming and the
scaled future prediction.
Robustness of climate change signals in near term predictions up to the year 2030
Speaker: Hideo Shiogama
Hideo Shiogama
National Institute for Environmental Studies, Tsukuba, Japan
shiogama.hideo@nies.go.jp
Toru Nozawa
National Institute for Environmental Studies, Tsukuba, Japan
Seita Emori
National Institute for Environmental Studies, Tsukuba, Japan
This is the first study to examine whether human contributions to changes in extreme
temperature indices have larger amplitudes than natural variability in near future (up to 2030)
climate prediction. We performed 10 runs of the initial condition perturbed ensemble of a
coupled atmosphere-ocean general circulation model. In the near future, over most land areas,
all 10 runs show agreement in predicting more frequent occurrences of warm nights and warm
days, and less frequent cold nights and cold days, suggesting that human influences in them
have become larger than natural variability. Area weighted fraction of grid boxes where all runs
agree the direction of changes over the land is little sensitive to ensemble sizes (for warm
nights, 96% and 93% for 4 runs and 10 runs, respectively). It was also suggested that the
changes in the frequency of warm and cold extremes are mainly due to shifts in seasonal
mean temperatures. Additionally snow cover affects the frequency of cold extremes in some
areas.
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