You may not believe this, but the whole of human society operates on knowing the future, particularly the weather. For example, a farmer in India knows when the monsoon rains will come next year and so when to plant his crops, while a farmer in Indonesia knows there are two monsoon rains next year so he can plant crops twice. This is based on their knowledge of the past as the monsoons have always come at about the same time each year in living memory. But such a prediction goes deeper than this as it influences every part of our lives. Our houses are built for the local climate - in England that means central heating but no air conditioning, while in the southern USA it is vice versa. Road, railways, airports, offices, cars, trains, etc. are all designed for the local climate. This is why in the spring of 2003 a centimetre of snow one afternoon effectively shut down London, while Toronto can easily deal with and function with half a metre of snow. In England in 2003 people were complaining about the heat when the temperature touched 100°F for the first time in recorded history, which colleagues of mine both in the USA and Africa found extremely amusing, while Australians go into shock if the temperature drops below 50°F. The problem with global warming is that it changes the rules. The past weather of an area cannot be relied on to tell you what the future will hold. So we have to develop new ways of predicting the future, so that we can plan our lives and so that human society can continue to fully function. So the very simple answer to the chapter title is that we have to model the future.
There is a whole hierarchy of climate models from relatively simple box models to the extremely complex three-dimensional general circulation models (GCMs). Each has a role in examining and furthering our understanding of the global climate system. However, it is the complex three-dimensional general circulation models which are used to predict future global climate. These comprehensive climate models are based on physical laws represented by mathematical equations that are solved using a three-dimensional grid over the globe. To obtain the most realistic simulations, all the major parts of the climate system must be represented in sub-models, including atmosphere, ocean, land surface (topography), cryosphere, and biosphere, as well as the processes that go on within them and between them. Most global og climate models have at least some representation of each of these | components. Models that couple together both the ocean and j| atmosphere components are called Atmosphere-Ocean General 3 Circulation Models (AOGCMs). The development of climate models over the last two decades is shown in Figure 22. Models of different parts of the climate system are first developed separately and then coupled into the comprehensive climate models. For example, the Met Office Hadley Centre model is the first AOGCM which now has a fully coupled 'dynamic vegetation' model. This is important because it has long been known that vegetation has an influence on climate; thus climate changes can affect the vegetation and those changes in vegetation can have an effect on climate. For example, the Amazon rainforest recycles about half the precipitation that falls, maintaining a moist continental interior which would otherwise be dry.
One of the key aspects of climate models is the detail in which they can reconstruct the world; this is usually termed spatial resolution. In general the current generation of AOGCMs have a resolution or detail of the atmosphere of one point every 250 km
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by 250 km in the horizontal and about 1 km in the vertical above the boundary layer. This would mean the atmosphere above the British Isles was represented by only ten points. The resolution of a typical ocean model is about 200-400 m in the vertical and 125-250 km in the horizontal. Equations are typically solved for every simulated 'half hour' of a model run. Many physical processes, such as cloud and ocean convection, of course take place on a much smaller scale than the model can resolve. Therefore, the effects of small-scale processes have to be lumped together and this is referred to as parametrization. Many of these parametrizations are, however, checked with separate 'small-scale-process models' to validate the scaling up of these smaller influences. The reason that the spatial scale is limited is that comprehensive AOGCMs are very complex and use a huge amount of computer time to run. At the moment much of the improvement in computer processing power which has occurred og over the last decade has been used to improve the representation | of the global climate system by coupling more models directly to j| the AOGCMs. It is important to run these models numerous 3 times because, as discussed below, there are many parts of the climate system for which the future parameters are uncertain. For example, the future human greenhouse gas emissions, which are not fixed, as they will depend on many variables, such as the global economy, development of technology, political agreements, and personal lifestyles. Hence, you could produce the most complete model in the world taking two years to simulate the next 100 years, but you would have only one prediction of the future based on only one estimate of future emissions which might be completely wrong. Individual models are therefore run many times with different inputs to provide a range of changes in the future. In fact, the IPCC have consulted the results of multiple runs of 22 different AOGCMs to provide the basis for their predictions. Of course, as computer processing power continues to increase, both this representation of coupled climate systems and the spatial scale will continue to improve. So what are the unknowns and why do we need to run many different model scenarios? Is there not just one view of the future? Unfortunately not, and below each of the unknowns is described in more detail and how it effects our model predictions for the future.
One of the fundamental considerations for the AOGCMs is not whether carbon dioxide influences global temperatures, but rather the extent to which it influences global temperatures. This is not only because of the direct effect of the carbon dioxide but also because of the many secondary influences and other climate feedbacks, such as aerosols, ocean circulation, etc., which may even cool the climate system. The first problem is estimating how much of the anthropogenic carbon dioxide makes it into the |
atmosphere. You will be surprised to know that about half of all 0 our carbon emissions are absorbed by the natural carbon cycle and o do not end up in the atmosphere, but rather in the oceans and the | terrestrial biosphere. This leads us to realize that we need to £
understand the present-day carbon cycle in order to understand f the amount of carbon dioxide that will end up in the =
The Earth's carbon cycle is extremely complicated, with both sources and sinks of carbon dioxide. Figure 23 shows the global carbon reservoirs in GtC (gigatonnes, or 1,000 million tonnes) and fluxes (the ins and outs of carbon in GtC per year). These indicated figures are annual averages over the period 1980-9. It must be remembered that the component cycles have been simplified, and the figures only present average values. The amount of carbon stored and transported by rivers, particularly the anthropogenic portion, is currently very poorly quantified and is not shown here. Evidence is accumulating that many of the fluxes can vary significantly from year to year. In contrast to the static view conveyed in figures like this one, the carbon system is dynamic, and coupled to the climate system on seasonal, inter-annual, and
decadal timescales. The most interesting figure is that the surface ocean takes up just less than half the carbon dioxide produced by industry per year. However, this is one of the most poorly known figures and there is still considerable debate over whether the oceans will continue to be such a large sink or absorber of our pollution. As we will see in Chapter 7, one of the great surprises recently has been the unexpected experimental results which suggest that the Amazon rainforest could be absorbing large quantities of atmospheric carbon dioxide. The key question we need to ask, if indeed this is the case, is: for how long will the oceans and the Amazon rainforest continue to absorb carbon dioxide?
As well as the warming effects of the greenhouse gases, the Earth's climate system is complicated in that that there are also cooling effects (see Figure 24 for the IPCC summary of both warming and cooling effects). This includes the amount of particles in the air (which are technically called aerosols, many of which come from human pollution such as sulphur emissions from power stations) and these have a direct effect on the amount of solar radiation that hits the Earth's surface. Aerosols may have significant local or regional impact on temperature. In fact, the AOGCMs have now factored them into the computer simulations of global warming, and they provide an explanation of why industrial areas of the planet have not warmed as much as previously predicted. Water vapour is a greenhouse gas, but, at | the same time, the upper white surface of clouds reflects solar 0
radiation back into space. This reflection is called albedo - and o clouds and ice have a high albedo and so reflect large quantities | of solar radiation from surfaces on Earth. Predicting what will t happen to the amount and types of clouds, and the extent of f global ice in the future, creates huge difficulties in calculating the = exact effect of global warming. For example, if the polar ice cap melts, the albedo will be significantly reduced, as this ice would be replaced by vegetation or open water, both of which absorb heat rather than reflecting it like white snow or ice. This would produce a positive feedback, enhancing the effects of global warming.
A critical problem with trying to predict future climate is predicting the amount of carbon dioxide emissions that will be produced in the future. This will be influenced by population growth, economic growth, Third World development, fossil-fuel usage, the rate at which we switch to alternative energy, the rate of deforestation, and whether an international agreement to cut emissions is ever
Fossil fuel horning [black carbon)
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