Capturing heat islands in climate models
September 9, 2010 | A team of scientists led by NCAR’s Keith Oleson has incorporated urban areas into a global climate model. The development is important because most models used for predicting future climate change do not account for the urban “heat island” effect. The study will be published in the International Journal of Climatology.
Oleson and colleagues used the Community Climate System Model, an NCAR-based model that uses trillions of calculations to simulate the chemical and physical processes that drive Earth’s climate. After inserting a parameterization for urban surfaces into the CCSM’s land surface component, the researchers ran the model from present day to 2100 under the Intergovernmental Panel on Climate Change (IPCC) A2 emissions scenario, which assumes that global fossil fuel emissions will continue to rise at high levels over the coming century.
Results from the modeling experiment show that present-day annual mean urban air temperatures are up to 4°C warmer than temperatures for surrounding rural areas, a finding that is important for verifying the model’s accuracy since scientists already have observational evidence that urban areas are warmer than surrounding rural areas.
The study found that both urban and rural areas warm substantially by the end of this century as emissions rise, with rural areas warming slightly more than urban—resulting in a decrease in the urban-to-rural contrast. In addition, nighttime urban warming is much greater than daytime urban warming, resulting in a reduced diurnal range in temperature compared to rural areas.
“This study demonstrates that climate models need to begin to account for urban surfaces to more realistically evaluate the impact of climate change on people in the environments where they live,” Oleson says.
He cautions that the study does not account for urban growth or changes in urban form or function; nor does it account for changes in the atmosphere other than increased carbon dioxide concentrations, such as aerosols or other kinds of pollution.
[or account for ocean oscillations, clouds, solar UV activity- which is much more variable than previously thought, negative feedback from water vapor, etc. etc.]
You are using an obviously trimmed graph (where, just by looking at it, the high 1998 start point so clearly would skew the regression in favour of a downward trend) as opposed to LONGER timeseries from a peer reviewed paper (Mears and Wentz), whose fundamental upward trend has been replicated countless times in other peer reviewed papers? Why? It is misleading and dishonest.ReplyDelete
The point is none of the GCMs predicted the divergence between CO2 and global temperatures or adequately incorporate natural forcing such as ocean oscillations and the sun. The reason the models failed to predict the actual behavior is because the sensitivity to CO2 is low to zero. see alsoReplyDelete