Modern climate models do a good job of simulating many large-scale features of present-day climate. However, these models contain large numbers of adjustable parameters which are known, individually, to have a significant impact on simulated climate. While many of these are well constrained by observations, there are many which are subject to considerable uncertainty. We do not know the extent to which different choices of parameter-settings or schemes may provide equally realistic simulations of 20th century climate but different forecast for the 21st century.
Varying the parameters
The experiments undertaken by the climateprediction.net team investigate the effect of varying the value of poorly understood parameters in the model on the climate predictions. Some combinations of parameters will not work at all, producing completely unrealistic climate (for example an Earth that boils, freezes, or oscillates between very hot and very cold every couple of years). It is not possible for us to tell beforehand what these combinations will be. The most thorough way to investigate this uncertainty is to run a massive perturbed physics ensemble experiment in which each relevant parameter combination is investigated; thus the perturbed physics ensemble is the central feature of the climateprediction.net project.
What parameters are varied in climateprediction.net?
The following parameters are varied in the climateprediction.net experiment:
- Ice fall speed through clouds – important for the development of clouds and determining type (rain, sleet, hail, snow) and amount of precipitation
- Rate at which cloud droplets convert to rain.
- ‘critical relative humidity’ relates the grid box scale atmospheric humidity to the amount of cloud in that grid box
- The amount of water there is in a cloud to when it starts raining, which is dependent on the condensation nuclei concentration – the more condensation nuclei there are (bits of dust, salt etc. in the atmosphere on which raindrops can form) the smaller the raindrops.
- The rapidity a convective cloud (imagine a plume rising over a power station, or a bit thunder cloud) mixes in clear air from around it.
- Empirically adjusted cloud fraction calculates how much cloud cover there will be when the air is saturated.
- The initial state of the atmosphere – what it looks like when the model starts in 1810.
- The effective radius for ice crystals in clouds – i.e. what radius would they have if they were perfectly spherical. It is important in the radiation scheme, to calculate how much incoming or outgoing radiation is reflected etc.
- These parameters all allow for non-spherical ice particles in the radiation scheme.
- The rate air mixes by turbulence in the boundary layer (the layer of the atmosphere closest to the Earth).
- This has to do with the fact that the ability of turbulence to mix air varies with how stable the air is – the more stable the air, the less turbulent mixing you get.
- transference of momentum and energy between tropical oceans and the air (wind) above them.
- transference of momentum and energy between seas and the air (wind) above them.
- number and size of plant roots in the soil – and, consequently, to how water is taken up from the soil and into the atmosphere by plant transpiration.
- the diffusion of heat from the slab ocean to ice, where there is sea-ice present in the model.
- Gravity waves are waves in the atmosphere for which gravity is the restoring force – think of air passing over a mountain, it is forced upwards over the mountain, and then gravity will pull it back down, resulting in an oscillation (you often see clouds form downstream of mountains as a result). The air particles oscillating in these waves tend to lose energy because of friction (drag), and this energy manifests itself as heat. This parameter determines the lowest model level on which gravity wave drag is applied
- the way that gravity waves are formed as air interacts with surface features, such as mountains.
- the albedo (reflectivity) of sea ice varies with temperature.
- Diffusion coefficients and exponents govern how quickly something spreads through the material it is in – so, for example, if you put a drop of oil dyed purple into a beaker of un-dyed oil, how rapidly the dyed oil mixes with the oil around it until all the beaker has the same colour. Diffusion refers to mixing due to the random motion of particles, rather than turbulent mixing which happens when there are actual vortexes mixing things (which would happen if you stirred the beaker with a spoon). In the case of the atmosphere, the horizontal diffusion coefficient and exponent determines the rate of diffusion of heat from a warm air mass to a cold one.
- The rate at which water vapour diffuses from a very humid air mass to a relatively dry one.