In a comment to the last post ( January 20 2009, 14:36 by Ken)
Indeed, water vapor is the major greenhouse gas (GHG) in the atmosphere and responsible for 60% of the natural GHG warming .
The water cycle is complex and has several opposing effects. Almost 90% of the global evaporation occurs from the oceans, reducing their temperature by evaporative cooling. Clouds, snow, and ice cover increase the albedo of the planet , reducing the amount of heat. Water vapor is also increasing absorbed heat through the GH effect.
Before we look at these effects in more detail, I will address the comment, using Ken's parable: This big and complex gorilla, the water cycle, is controlled by a small child, its cousin, called the CO2 cycle. The key term here is "residence time" (RT). For water vapor in the atmosphere the average residence time is nine days. What does this mean?
Imagine building a facility which will vaporize vast amounts of water and release it into the atmosphere. The absorption of heat will increase due to stronger GH effects. In a few days it will rain, and all the water which you added will be back in the rivers and oceans.
Our planet is unique in the known universe for having water under natural conditions in all three phases: as a gas, a liquid, and a solid. Carbon dioxide, in contrast, does not behave this way.
c4s When you add CO2 to the atmosphere, you warm the planet a little bit. The effect is amplified because warmer air holds more water vapor. So raising or lowering CO2 acts as a throttle to raise or lower the really important greenhouse gas, water or H2O.
Like water, carbon dioxide (CO2) is exchanged between the atmosphere, land, and oceans, in the carbon cycle. In contrast to water, its residence time in the atmosphere is hundreds of years. Thus the concentration of CO2 can be treated as an input variable in the models. One can set the CO2 level or its rate of increase to a given value and let the model calculate the effects. The level of water in the atmosphere can not be treated the same way because of its short residence time.
Mathematically speaking, the concentration of CO2 can be treated as independent parameter. In such a simulation run, the model is calculating "what the temperature will be" at given level of CO2 or at a given rate of increase. These different runs are the varied scenarios being considered. The concentration of water is a dependent variable; it should not be forced. The model will calculate its value as determined by the dynamical equilibrium of all cycles. That is the reason you hear more about CO2 when different scenarios are being described.
So, water is not ignored in the models. Its effect was recognised very early in history of the models of climate. In 1862 the English physicist Tyndall wrote that for Earth "water vapor 'is a blanket more necessary to the vegetable life of England than clothing is to man. Remove for a single summer-night the aqueous vapour from the air... and the sun would rise upon an island held fast in the iron grip of frost.' Tyndall needed no equations, but only simple logic, to see, what many since him overlooked: it is at night that the gases are most important in blocking heat radiation from escape, so it is night-time temperatures that the greenhouse effect raises the most."
It was Tyndall first, and then Swedish physicist Arrhenius (1859 - 1927), who created first simple climate models. They incorporated the effects both oxides, of H2O and CO2 .
Arrhenius, realized that the concentration of CO2 was rising due to the burning of fossil fuels. This was at the beginning of the Industrial Revolution. He figured that if industry continued to burn fuel at then current rates, it would take thousands years for the CO2 level to rise high enouh to cause concern. As use of fossil fuels has "progressed," this estimate had to be dramatically revised.
The quotes cited above are from a fascinating book, "The Discovery of Global Warming," which reads like a detective story. Available as a 200 page paperback, on CDrom, or from the Web as pdf files for free, it is highly recommended reading.
There are other GHG gases as well as circulation models of other compounds, but those of energy, water, carbon, oxygen and carbon dioxide are the most important for models of climate. As scientists are getting more data from satellites designed to monitor GHG gases and are refining the physical basis of models, the ability to understand the changes and their causes is improving.
We should remind ourselves that climate models do not actually predict the future. The future depends on economic and political decisions. In posing "what if" questions, models can help us make those decisions.
It is important that before we spend billions of Euros on the environmental tax on carbon emission, on the ETS tax, we have a high degree of confidence in the predictions of these models.
- Simple model applet
- Here is a short summary of the first models of climate.
- Qualitative theory behind a simple model Unless you are totally allergic to even simple equations (the Stefan-Boltzman law), look at these estimates.
- Slightly more complex and more detailed description of the greenhouse effect.