Class images
| How climate models work. From UNEP. | |
| Houghton, J. T., L. G. Meira Filho, B. A. Callander N. Harris, A. Kattenberg, and K. Maskell, 1996: Climate Change 1995. The Science of Climate Change. Cambridge University Press, pp 236-245. | |
| Houghton, J. T., G. J. Jenkins, and J. J. Ephraums, 1990: Climate Change, The IPCC Scientific Assessment. Cambridge University Press. p. 80-89. |
Discussion Summary Unit 2-2 Prepared by: Karen Bandhauer, Deborah Frundle, Krystina Schwartz and Sue VansiceLearning Unit:
In order to understand climate change, we must understand the interactions, which occur in the climate system. Feedback occurs when a change in one climate parameter changes another, which, in turn, causes changes in the initial variable. There is both positive and negative feedback in relation to climate change depending on if they magnify or minimize the parameters effects on climate change. Feedback is incorporated in climate models. The following are examples of feedback:
- Temperature-radiation feedback: Employs the Stefan-Boltzmann equation. Says that an initial increase in energy leads to an eventual decrease in temperature. This is an example of negative feedback.
- Water-vapor/greenhouse feedback: As temperature increases the rate of evaporation increases, which increases the amount of water vapor in the air creating an increased absorption of infrared radiation by the atmosphere, contributing further to the greenhouse effect. The increased greenhouse effect in turn increases the surface temperature causing more evaporation. This cyclic effect is a positive feedback.
- Snow and ice cover / albedo feedback: As the temperature increases, the amount of snow and ice cover decreases, which decreases the albedo effect. This increases the amount of radiation that is absorbed, further raising the temperature and melting more ice, creating a positive feedback.
- Radiative-dynamic coupling: This relationship has the potential for positive or negative feedback.
Climate models use the same laws of physics as weather forecasting over longer periods of time; conservation of energy, conservation of momentum, conservation of mass, and an equation of state that describes the relationship of temperature to pressure and density. When using these laws, three separate equations are needed for water, one for water vapor, liquid water, and cloud-ice particles. Physical processes that occur on too small of a scale or are too complicated are approximated by parameterizations in the climate model. Global climate models must determine values for temperature, wind speed, pressure, density, and concentration of water vapor, liquid water, and ice crystals at each the grid points over the earth (around 50,000 to 150,000) at each time step (typically an hour) for the length of the simulation (30-year period, 262,800 time steps). Typically global climate models have horizontal grid spacing of about 500 km (300 miles), they often preclude Florida, and a single surface grid point will represent all of the surface processes in an area larger than Iowa, which can produce limitations for the models on a local scale. Comparisons of models using parameters like surface pressure are useful to gage their accuracy.
Class Lecture:
Weather is predicted by taking measurements all over the world. Those measurements are fed into a computer, which uses non linear equations to predict the forecast for the next few days. Weather cannot be predicted more then a few days in advance because the uncertainty would add up and the forecast would no longer be accurate. (Pinball model) When using models you need to respect the uncertainties involved. Models show, for instance, what would happen if Co2 were to double? There are two types of models, equilibrium and transient models. With equilibrium models you set the controls and let the model run until equilibrium is reached. For a transient model the changes are more gradual. You start with one setting and gradually change to what you want to see. The equilibrium model is cheaper and faster to run, but is not very realistic do to the world is never in equilibrium. The transient model is more accurate but takes much more time and money. The IPCC (Intergovernmental Panel and Climate Change) uses weather models and in 1995 released the statement that humans contribute to climate change.
Online Dialog:
In the public dialog the question of how greenhouse gases and clouds differ in IR absorption. Throughout the dialog it is determined that greenhouse gases are closer to the Earth than clouds, and that greenhouse gases absorb more energy that higher clouds. This energy absorbed by the greenhouse gases is then held close to the Earth and increases the Earth's temperature. Whereas clouds that are high up in the atmosphere reflect more energy than it absorbs. Since a good portion of the solar energy is reflected back into space, the energy never hits the Earth. Thus, clouds cause a cooling effect. A useful website about this material:
Climate Change and Greenhouse Gases
Another topic briefly discussed in the public dialog was the mean sea-level pressure at 30 degrees south and 30 degrees north during specific months of the year. A student suggest that the difference between the latitudes of 30 degrees north and 30 degrees south during the months of December-February may be caused by the Hardy cells at the 30 degrees north and 30 degrees south deserts. But, is still unanswered why there is a difference in the mean sea-level pressure between the 30 degrees north and 30 degrees south latitudes between the months of June-August.
| Global Ice Volume, Deep Ocean Temperatures, and Climate Surprises | |
| Cloud Radiative Processes, NASA | |
| Fractal Cloud Animations, California | |
| Cess, R. D., et al., 1995: Absorption of solar radiation by clouds: observations vs. models. Science 267, 496-499. | |
| Houghton, J.T., G.J. Jenkins, J.J. Ephraums, eds, 1990: 1990 Intergovernment Panel on Climate Change, Cambridge University Press, 77-80. | |
| Kerr, Richard A., 1995: Darker clouds promise brighter future for climate models. Science 267, 454. | |
| Lashof, D.A., 1989: The dynamic greenhouse: Feedback processes that may influence future concentrations of atmospheric trace gases and climatic change. Climate Change 14, 213-242. | |
| Ramanathan, V., et al., 1995: Warm pool heat budget and shortwave cloud forcing: a missing physics? Science 267, 499-503. |
| SCIENCE AND NONSCIENCE
CONCERNING HUMAN-CAUSED CLIMATE WARMING J. D. Mahlman Geophysical Fluid Dynamics Laboratory/ NOAA, Princeton University, Princeton, New Jersey 08542 | |
| Intergovernmental Papers on Stabilization and Models | |
| Pielke, R. A., Jr., 2001: Room for doubt. Nature 410, 151 | |
| Dickinson, R. E., 1995: Walter Orr Robers Lecuture - Land surface processes and climate modeling. Bulletin of the American Meteorological Society 76, 1445-1448 | |
| Henderson-sellers, A., and K. McGuffie, 1987: A Climate Modeling Primer. John Wiley & Sons. New York. 217 pp. | |
| McGuffie, K., and A. Henderson-Sellers, 1997: A Climate Modelling Primer. Second Edition. John Wiley & Sons. New York. 253 pp. | |
| Kerr, Richard A., 1997: Greenhouse Forecasting Still Cloudy. Science 276, 1040-1042. | |
| Kerr, Richard A., 1997: Model Gets it Right--Without Fudge Factors. Science 276, 1041. | |
| Trenberth, K.,1997: The Use and Abuse of Climate Models. Nature 386, 131-133. | |
| Zeng, Xubin, R.A. Pielke, R. Eykholt, 1990: Chaos in Daisyworld. Tellus 4, 309-318. |