In the last lesson we learnt about Lewis Fry Richardson developing the concept of numerical weather forecasting. In the 1910s and 1920s his idea could not be realised because we did not have sufficient computing power. Today, that computing power exists – indeed of the UK’s top 7 supercomputers, four are at the Metoffice and two at ECMWF (the European Centre for Medium-Range Weather Forecasting). The only one that isn’t used for weather and climate forecasting is at the Atomic Weapons Establishment (and I dread to think what they use it for).

The weather and climate models of today work as Lewis Fry Richardson predicted: they break the Earth and its atmosphere up into little boxes and in each box they predict the change in conditions over a certain defined time step. They then pass that information to neighbouring boxes.

Over time, weather and climate models have become more complex in:

• The range of phenomena that they include in their models (discussed below)
• The size of the boxes and time steps (smaller boxes, smaller time steps)
• The variety of observational data that they bring into the models
• Their handling of uncertainty in the modelling processes and in the observations
• Their ability to predict both overall trends and detail (so moving from making predictions for averages to predictions for specific areas)
• The human and geological behaviour that they can include in the models (fossil fuel burning, deforestation, volcanos etc).

The simplest climate models are “energy balance models” (EBMs). These do what we considered in our thought experiment in lesson 4, extending it as we did in 4b. They generally split the world into rings of latitude. In each ring they consider the energy in (from the sun based on the average amount of sunlight to hit that ring over a day and a year) and the energy out (the reflected sunlight, which depends on the average albedo – that is reflectance, and the thermal infrared Earth emission and thermal infrared emissivity – that is how well it emits that wavelength). The greenhouse effect is included as a temperature increment – the amount that those greenhouse gases cause a temperature rise. Such models can give basic information about the Earth system – and explain the basic temperature changes that we see.

The simple models can also consider some feedback processes. Since 1969 climate models have considered the “sea-ice albedo” feedback. This affects these energy balance equations near the poles. When the temperature of the Earth is cooler, there is more sea ice and that reflects sunlight back to space, reducing the amount of sunlight that heats up the Earth and therefore cooling the Earth further (this was an important feedback mechanism during the ice age). When the temperature of the Earth is warmer, the sea ice melts and the dark sea that is there instead absorbs a much larger fraction of the sun’s light, warning up the Earth further.

Energy Balance Models can also study the impact of changes in the output of the sun (the sun has an 11-year sunspot cycle and is about 0.3 % brighter when there are more sunspots than it is when there aren’t any. During 1650 – 1700 there was a period of time with almost no sunspots (the Observatoire de Paris was taking records daily) and that corresponds to the “Little Ice Age” (though at the same time there were increased volcanic activity and probably a significant regrowth of rainforest in central America after European diseases, introduced by the explorers, wiped out a very large population – both of those factor may also have altered the climate).

However, energy balance models must be superficial when used alone. Instead they are one component of more complex models. The next, and essential, level of sophistication is to add in convection. I mentioned in an earlier lesson that a garden greenhouse does not heat up because of “the greenhouse effect” but because the glass stops the air circulating. We also know that “radiators” in our houses don’t really work by radiating heat, but by setting up circulation patterns in the air in the room (hot air rises). Similar processes happen in the oceans. London (51 degrees latitude North) is much warmer than Ottawa (45 degrees latitude North) because of the gulf stream that transports hot water from central America towards Europe.

Circulation models need to consider the Earth not in latitude bands, but in the small boxes (including boxes on top of each other into the atmosphere and down into the sea) and consider the currents in the ocean and the winds in the atmosphere and how that means water or air is passed from one box to the next. Circulation models also include physical processes in the ocean and atmosphere – how water vapour condenses into clouds and how clouds precipitate into rain and snow. It is circulation models that model “cloud feedback” which we discussed before.

The gulf stream is driven by salt in the sea water. As water travels from the Equator towards the poles, some evaporates, and therefore the remaining water becomes more salty. Salty water has a higher density (is heavy) and sinks and this sinking drives the “conveyor belt”. There’s a nice video from the MetOffice on youtube that explains this.

One topic that has been discussed in the media (and was the basis of a film) is a concerning possible future feedback could be that as the Greenland ice sheet melts, the fresh (not salty) water introduced just at the point where the Gulf Stream sinks, could stop the whole circulation – changing the patterns across the world and, potentially, making Europe colder! The latest IPCC report, however, says that this is “very unlikely”, though there may be changes in how the circulation occurs.

Modern models “coupled climate system models” include more processes, including chemical processes (chemistry in the ocean, in the atmosphere and at the boundary between the ocean and the atmosphere) and biological processes (growth of trees and algae and the chemical and biological changes that creates: e.g. photosynthesis, carbon storage in trees and in the soil, the effects of fire). They also model human effects – from the “heat island” effects of cities to the impact of paving our roads and gardens on the water cycle.

Modern climate models are some of the most complex computer programs in the world, written by huge teams of experts, each concentrating on one small detail, and running on some of the world’s most powerful computers. They are the achievement of huge multidisciplinary teams of physicists, chemists, biologists (and most importantly those working at the cross-over between disciplines: biochemists, biophysicists), computer scientists, engineers and mathematicians. There are approximately 30 teams of scientists who have developed climate models that run on different computers running different codes. Those teams go to conferences together and learn from each other, but each team makes its own decisions about which details to include and how to model them. They also make different decisions about which observational data (the subject of a later lesson) to include.

The Earth System is extremely complicated. Our models are our best attempt to simulate the real Earth. As our science has become more sophisticated, and as our computers have become more powerful, we have been able to include more and more detail into those models. But we must never forget that they are models and not reality in and of themselves.