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Mapping Future Heat Waves

G. A. Meehl and C. Tebaldi, “More intense, more frequent and longer lasting heat waves in the 21st century,” Science 305, 994 (2004). BER, NSF

Using a global coupled climate model, Meehl and Tebaldi determined that there is a distinct geographic pattern to future changes in heat waves. Model results for Europe and North America indicate that future heat waves in these areas will become more intense, more frequent, and longer lasting in the second half of the 21st century. Observations and the model show that present-day heat waves over Europe and North America coincide with a specific atmospheric circulation pattern that is intensified by ongoing increases in greenhouse gases, indicating that it will produce more severe heat waves in those regions in the future (Figure 7).

Figure 7. Future simulated changes in worst three-day heat waves are not uniformly distributed geographically but instead show a distinct pattern, as seen for North America and Europe from 2080 to 2099.

Aerosols Influence Radiative Fluxes

J. E. Penner, Y. Chen, and X. Dong, “Observational evidence of a change in radiative forcing due to the indirect aerosol effect,” Nature 427, 231 (2004). BER, NASA

Anthropogenic aerosols enhance cloud reflectivity by increasing the number concentration of cloud droplets, resulting in cooling from the “indirect aerosol effect,” but it has been difficult to determine the impact of these indirect effects on radiative forcing. Penner et al. examined the effect of aerosols on cloud optical properties at two North American sites, determined the cloud optical depth required to fit the observed shortwave downward surface radiation, then used a warm-cloud adiabatic parcel model to simulate cloud optical depth. Good agreement between the simulation and observed surface radiation provided evidence that the indirect aerosol effect has a significant influence on radiative fluxes.

Faster Modeling of Long-Term Climate Evolution

Z. Liu, W. Lewis, and A. Ganopolski, “An acceleration scheme for the simulation of long term climate evolution,” Climate Dynamics 22, 771 (2004). BER

Understanding climate evolution on millennial (and longer) time scales will improve our understanding of past and future global climate changes. Liu et al. used a new acceleration scheme in a coupled ocean-atmosphere model to look at what forces long-term climate evolutions such the one that followed the Last Glacial Maximum 21,000 years ago. This new coordinated acceleration scheme reduces oceanic computation time as much as atmospheric time. For millennial climate evolution, the model produces reasonably good simulations, with an acceleration factor of about 5. For climate evolution of even longer time scales, the acceleration factor can be increased.

More Realistic Precipitation Models

J. Iorio, P. Duffy, B. Govindasamy, and S. Thompson, “Effects of increased resolution on the simulation of daily precipitation statistics in the U.S.,” Climate Dynamics 23, 243 (2004). BER

Changes in precipitation, both daily and seasonal, will account for some of the most important societal impacts of anthropogenic climate change. Increased spatial resolution models are needed to predict these possible effects. Iorio et al. analyzed global climate simulations (performing at a range of spatial resolutions) to assess the effects of horizontal spatial resolution on the ability to simulate precipitation in the continental U.S. By increasing the spatial resolution in the model (CCM3), they obtained more realistic representations of observed present-day precipitation, including both seasonal-mean precipitation and daily precipitation.

Parameterizing Subgrid Processes

J. N. Cole, H. W. Barker, D. A. Randall, M. F. Khairoutdinov, and E. Clothiaux, “Global consequences of interactions between clouds and radiation at scales unresolved by global climate models,“ Geophys. Res. Lett. 32, L06703 (2005). BER

General-circulation models (GCMs), which test hypotheses regarding the Earth’s climate, see the world in terms of 100–500 km grid spacings, which leaves many “subgrid” processes unresolved and in need of parameterization. Cole et al. tested the assumption that accurate domain averages are sufficient for satisfactory simulation of climatic change. They used a 2D cloud system resolving model (CSRM) with a horizontal 4 km grid spacing to investigate whether local interactions between clouds and radiation are important for successful GCM simulations. Results show that the unresolved interactions are at least as important as getting accurate domain averages.