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Level ol scientific understanding 24. Global, annual-mean radiative forcings due to a number of agents for the period from pre-industrial to present reached. Out of all the systems that we are trying to model into the future, humanity is by far the most complicated and unpredictable. If you want to understand the problem of predicting what will happen in the next hundred years image yourself in 1904 and what you would have predicted the world to be like in 2004. Would you have predicted the explosion of car use or the general availability of flight? Even ten years ago it would have been difficult to predict the budget airlines which allow for such cheap flights throughout Europe and the USA.
So what the IPCC has done is to produce 40 new scenarios of what the future could be like depending on the factors above. Of these there are worst-cases scenarios, which predict an increase of 220% in atmospheric carbon dioxide by 2100, compared with pre-industrial levels, and best-case scenarios which still predict a | 75% increase by 2100 (Figure 25a). Even if the anthropogenic 0
emissions of carbon dioxide are stabilized or even reduced, the 1
c carbon dioxide content in the atmosphere is still expected to |
increase over the next 100 years. Because of these different t economic models or visions of the future, the IPCC has switched f from trying to predict the future to discussing projections and =
possible futures. Bj0rn Lomborg provides an interesting and radical insight to the IPCC's 40 future scenarios in his controversial book The Skeptical Environmentalist (2001).
Seven AOGCMs have been run using selected future carbon dioxide emission scenarios for the IPCC 2001 report to produce global average temperature changes that may occur by 2100. These climate models show that the global mean surface temperature could rise by between 1.4°C and 5.8°C by 2100 (see Figure 25). The topmost curve assumes constant aerosol concentrations beyond 1990, high climate sensitivity, and a significant increase in the emissions of carbon dioxide, and produces an increase of 5.8°C by 2100. The lowest curve assumes constant aerosol concentrations
beyond 1990, but a much lower climate sensitivity, and a slower increase in carbon dioxide emissions, and produces an increase of 1.4°C. What is most worrying is that there is a 4.4°C temperature difference between the IPCC projections in the most extreme estimates. However, it should be noted that all the model predictions show an increase in global temperatures over the next hundred years.
Again, using the different carbon dioxide emission scenarios, the IPCC has projected global mean sea level up to 2100. Taking into account the ranges in the estimate of climate sensitivity and ice-melt parameters, and the emission scenarios, the models project an increase in global mean sea level of between 20 cm and 88 cm (Figure 25). Note that during the first half of the 21st century, the choice of emission scenario has relatively little effect on the |
projected sea-level rise, as most of it is due to the large thermal 0 inertia (i.e. it takes a lot of initial energy to get any noticeable o change in temperature) of the ocean-ice-atmosphere climate |
system. However, it has an increasingly large effect in the latter t part of this century, because of the uncertainty about how the ice f sheets will react and melt. In addition, because of the thermal =
inertia of the oceans, sea level would continue to rise for many centuries beyond 2100, even if concentrations of greenhouse gases were stabilized at that time. What the sea-level calculation does not take into account is the possible melting of the world's ice sheets and glaciers. If the ice sheets completely melted, their contribution to sea-level rise would be as follows: mountain glaciers = 0.3 m, West Antarctic Ice Sheet = 8.5 m, Greenland = 7 m, East Antarctic Ice Sheet = 65 m. What is worrying is that NASA satellite measurements suggest that both Greenland and the West Antarctic Ice Sheets are shrinking. If this produces enough melt-water then we could have some big surprises in store in the future, which will be discussed in Chapter 7. There is also a scientific debate about what happens to both the Greenland and Antarctic Ice Sheets beyond the next hundred years. Some scientists believe what happens in the next hundred years will determine the future of these ice sheets. One prediction suggests that though the Greenland Ice Sheet will not collapse in the next hundred years, global warming will start a process which will be irreversible and Greenland will be ice free within the next thousand years.
One of the best ways to summarize the problems of modelling the global warming future is to review what the sceptics say, as they have many valid points and provide a basis on which our models should be improved.
1. Clouds can have a positive and negative feedback on global climate; how do we know they will not reduce the effects of global warming to a negligible amount?
| As has been the case since the very first IPCC 1990 report, the j| greatest uncertainty in future predictions is the role of the clouds 3 and their interaction with radiation. Clouds can both absorb and reflect radiation, thereby cooling the surface, and absorb and emit long-wave radiation, thus warming the surface. The competition between these effects depends on a number of factors: height, thickness, and radiative properties of clouds. The radiative properties and formation and development of clouds depend on the distribution of atmospheric water vapour, water drops, ice particles, atmospheric aerosols, and cloud thickness. The physical basis of how clouds are represented or parametrized in the AOGCMs has greatly improved through the inclusion of bulk representations of cloud microphysical properties in the cloud water budget equations. However, clouds still represent a significant source of potential error in climate simulations. It is still controversial whether clouds help warm or cool the planet and both situations are found in the various AOGCMs. However, it is interesting that even in those AOGCMs in which clouds cause a cooling effect, this effect is not strong enough to counter the other warming trends.
2. Different models give different results so how can we trust any of them?
This is a frequent response from many people not familiar with modelling, as there is a feeling that somehow science must be able to predict an exact future. However, in no other walk of life do we expect this exactness. For example, you would never expect to get a perfect prediction of which horse will win a race or which football team will emerge triumphant. The truth is that none of the climate models is exactly right. But what they provide is the best estimate that we have of the future. Now this view of the future is strengthened by the use of more than one model, because each model has been developed by different groups of scientists around the world, using different assumptions and different computers, and thus they provide their own particular future prediction. What | causes scientists to have confidence in the model results is that they 0 all roughly predict the same trend in global temperature and sea o level for the next hundred years. Another strength of this approach | is that scientists can also give you an estimation of how confident t they are in the model results and also a range of possible f predictions. The day that scientists give an exact estimate of what = is going to happen and when is the day they will lose all credibility, rather like being told to invest in the USA stock market just before the 1929 crash as stock markets can never go down, or being sold a mortgage in the early 1980s in the UK and being told that there is no way the housing market will crash.
3. Climate models fail to predict abrupt weather conditions.
AOGCMs are not able to predict abrupt weather events because their spatial resolution is too coarse; for example, the whole of the British Isles is represented by ten points. This has led to the accusation by the sceptics that the random or chaotic factors which influence our day-to-day weather must also influence our climate. It has been known since the late 1960s that weather patterns are chaotic, as the Earth's climate system is sensitive to extremely small perturbations in initial conditions. For example, extremely slight changes in air pressure over the USA have an influence on the direction and duration of a hurricane. We all know that this sensitivity limits predictability of detailed weather forecasts to about two weeks; sometimes it feels like two days. However, predictability of climate is not limited in the same way as the prediction of the weather because the longer-term systematic influences on the atmosphere are not reliant on the initial conditions. So the longer-term trends in regional and global climate are not controlled by small-scale influences. However, what the global warming sceptics are correct about is that at present we cannot model 'non-linear events', or so-called abrupt climate changes that may occur in the future. These potential surprises are discussed in Chapter 7.
4. Climate models fail to reconstruct or predict natural variability.
| The global climate system contains cyclic variations which j| occur on a decade or sub-decade timescale. The most famous 3 is El Nino, which is a change in both ocean and atmospheric circulation in the Pacific region occurring every three to seven years and has a major influence on the rest of the global climate. Sceptics argue that climate models have been unable to simulate satisfactorily these events in the past. However, climate models have become increasingly good at reconstructing these past variations in El Nirio-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and related Arctic Oscillation (AO) as there has been an increasing realization that these have a profound impact upon regional climate (see Chapter 6, El Nirfo-Southern Oscillation section for further details). Most models are able to depict these natural variations, picking out particularly the 1976 climate shift which occurred in the Pacific Ocean. All the AOGCMs have predicted outcomes for ENSO and NAO for the next hundred years. However, a lot of improvement is required before there will be confidence in the model predictions. It is, though, testament to the realism of the AOGCMs that they can indeed reconstruct and predict future trends in these short-term oscillations.
5. The thermohaline circulation is not properly characterized in the climate models.
The deep-ocean, or thermohaline, circulation (THC) of the world's oceans is one of the basic building blocks of the coupled Atmosphere-Ocean GCMs, hence the simulations of the thermohaline circulation for the present day and the past are very good. However, uncertainties concerning the modelling of the future of the THC come from the complexities controlling deep-water formation, including the interplay in the large-scale atmospheric forcing between the warming and evaporation in the low latitudes and cooling and increased precipitation at |
high latitudes. In addition, ENSO can play a part by altering 0
the freshwater balance of the tropical Atlantic. Add to this the o uncertainties in the representation both of the small-scale flows | over sills and through narrow straits and of ocean convection, t which further limit the ability of the models to simulate situations f involving substantial change in the THC. Hence most future =
predictions from AOGCMs have a similar THC to the present. As we will see in Chapter 7, this assumption could be completely wrong.
6. AOGCMs fail to reconstruct past climate, particularly the last ice age.
Past climates are an important test for global climate models. The biggest climate shift, for which we have many climate reconstructions, is that of the last ice age, which ended about 10,000 years ago. A comparison between palaeoclimate data for the most extreme stage of the ice age, which occurred 18,000 years ago, suggests that the global climate models are rather conservative. In fact, the best model reconstructions show only three-quarters of the climatic changes reconstructed from proxy data. Instead of invalidating our climate models, it first shows that with the extreme condition of an ice age - sea level 120 m lower, 3 km high ice sheets on America and Europe, atmospheric carbon dioxide a third lower, and atmospheric methane halved - the models can get it about 75% right. The second important observation is that the models are conservative, and they systematically underestimated the climatic changes. This means we can assume that the future climate predictions are also conservative and thus climate change is very likely to be at the top end of the estimates.
7. Galactic cosmic rays (GCRs) are ignored in the current climate models, which invalidates the models.
Galactic cosmic rays are high-energy particles that cause ionization in the atmosphere and may, therefore, affect cloud formation. GCRs vary inversely with solar variability because of the effect of solar og wind. This is an excellent example of how climate science | progresses by discovering new knowledge and, if it is important j| enough, adding it into the climate models. Very little is known 3 about this newly discovered external forcing, GCRs, so research is continuing into this phenomenon to see if it has a large enough effect to be included in the climate models. Unfortunately it affects one of the least well-understood processes in our climate system - that of cloud formation. But the discovery that GCRs may influence climate does not invalidate the climate models, because it is all part of the progressive nature of science. We do not know everything about the climate system and we never will. Our understanding will continually improve as science progresses. Hence, model predictions of the future are continually improving. It should, however, be remembered that these models are based on the present understanding of the climate system and will always change in the future.
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