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using fixed SST boundary conditions ( Fig. 4a ). If the ocean were able to maintain these surface fluxes, the sea surface heat balance would allow the observed SSTs to persist. If the ocean component does not supply the expected flux under the atmosphere’s forcing, the SST will drift. Fig . 4. Difference in SSTs for CM3 minus CM2.1 (color) computed from the ensemble means for the two climate models over years 1981–2000. Contours show the difference in surface ocean heat fluxes from the (top) AMIP
using fixed SST boundary conditions ( Fig. 4a ). If the ocean were able to maintain these surface fluxes, the sea surface heat balance would allow the observed SSTs to persist. If the ocean component does not supply the expected flux under the atmosphere’s forcing, the SST will drift. Fig . 4. Difference in SSTs for CM3 minus CM2.1 (color) computed from the ensemble means for the two climate models over years 1981–2000. Contours show the difference in surface ocean heat fluxes from the (top) AMIP
used to calculate the maximum number of nucleated drops. The equation represents the formulation of the activation source term in the cloud drop prognostic equation. Model configuration is similar to the fixed sea surface temperature (SST) simulation presented in Donner et al. (2011 ), except that interannual variability in boundary conditions and forcings are removed to enable shorter simulations. Interannual monthly SSTs are replaced with monthly climatologies for the period 1980
used to calculate the maximum number of nucleated drops. The equation represents the formulation of the activation source term in the cloud drop prognostic equation. Model configuration is similar to the fixed sea surface temperature (SST) simulation presented in Donner et al. (2011 ), except that interannual variability in boundary conditions and forcings are removed to enable shorter simulations. Interannual monthly SSTs are replaced with monthly climatologies for the period 1980
concentrations in AM2 were prescribed following Randel and Wu (1999) . 4. Basic simulation characteristics a. Boundary conditions and integrations AM3 and the land model were integrated with prescribed sea surface temperatures, sea ice coverage, and sea ice albedo to demonstrate their behavior with realistic boundary conditions. These integrations will be contrasted in this section with observations and with simulations in which AM3 served as the atmospheric component of CM3. Observed sea surface
concentrations in AM2 were prescribed following Randel and Wu (1999) . 4. Basic simulation characteristics a. Boundary conditions and integrations AM3 and the land model were integrated with prescribed sea surface temperatures, sea ice coverage, and sea ice albedo to demonstrate their behavior with realistic boundary conditions. These integrations will be contrasted in this section with observations and with simulations in which AM3 served as the atmospheric component of CM3. Observed sea surface
prescribed constant ozone, rather than using a time-varying climatology ( Son et al. 2008 ). In addition, the models had poor stratospheric resolution, with many models having an upper boundary as low as 5 hPa. Since the Brewer–Dobson circulation in the atmosphere rises to at least 1 hPa before turning and affecting the lower stratosphere middle- and high-latitude region, the whole of the stratospheric circulation of the models does not correspond closely with the atmospheric behavior. As a result such
prescribed constant ozone, rather than using a time-varying climatology ( Son et al. 2008 ). In addition, the models had poor stratospheric resolution, with many models having an upper boundary as low as 5 hPa. Since the Brewer–Dobson circulation in the atmosphere rises to at least 1 hPa before turning and affecting the lower stratosphere middle- and high-latitude region, the whole of the stratospheric circulation of the models does not correspond closely with the atmospheric behavior. As a result such
