The greenhouse effect describes the process by which certain gases trap the heat in the earth’s atmosphere. This natural process enables the earth to be warm enough for us to live on it. Physical principles make it clear that increasing greenhouse gases will increase the temperature of the planet (Australian Academy of Science, 2010).
The enhanced greenhouse effect is the effect of adding extra greenhouse gases from human activities such as the burning of forests, fossil fuel combustion (coal, oil and natural gas) land clearing and agriculture. Greenhouse gases include water vapour, carbon dioxide, methane, nitrous oxide, ozone and chemicals such as chlorofluorocarbons (CFCs)
Global atmospheric concentrations of major greenhouse gases have increased as a result of human activities since the Industrial Revolution began in 1780 and the rate of increase is speeding up. Human activity is rapidly changing the earth’s carbon cycle.
Between 1990 and 2010, fossil fuel carbon dioxide emissions increased by 49 per cent, even after a 1.3 per cent decline in 2009 due to the global financial crisis.
Rapid warming of the planet is causing major changes in the dynamics of the earth’s climate system. Solar radiation and volcanic activity are the two main natural causes of climate forcing but the evidence is extremely strong that the current rate of global warming is not related to either of those causes. Most climate scientists accept that the current rapid global warming is due to greenhouse gas emissions (Australian Academy of Science, 2010).
Evidence for global warming comes from data on increased air and sea temperatures, melting of snow and ice and rises in sea level. Even if greenhouse gases were stabilised at some time in the future, climate change would continue for a long time and the climate may not return to its original conditions (Australian Academy of Science 2010).
Australian scientists have been measuring greenhouse gases at Cape Grim in Tasmania for 50 years, an area considered to have the cleanest air in the world. During this time, the level of CO2 at Cape Grim has increased linearly from 328 to nearly 400 ppm. Scientists also have measurements of ancient air locked in ice from Antarctica, showing the air and oceans contain more CO2 that at any time in the past 800,000 years.
Warming of the atmosphere and oceans cause complex reactions within the global climate system and this is why there is some level of uncertainty and the possibility of sudden climate shocks.
Scientists use all the information they have on the factors influencing global climate to try and determine the likely effects of increased greenhouse gases on these factors. For example if the oceans warm it will impact on ocean currents and atmospheric circulations and change the position of some of the main climate drivers for the South Coast.
Although there are still many gaps in knowledge about what influences climate in Western Australia, the Bureau of Meteorology and CSIRO can put their current knowledge into their models and evaluate them against past climate to increase confidence in the modeling.
Global Climate models (General Circulation Models)
"Essentially, all models are wrong, but some are useful,” is a well-known quote from statistician G.E.P Box in his book with Norman Draper, Empirical Model-Building and Response Surfaces.
It means that mathematical models cannot perfectly represent reality but they can provide information that helps reduce some of the uncertainty.
Climate models are mathematical representations of global climate systems based on the laws of physics. Climate model projections are tools aimed at reducing the uncertainty as to how the climate will respond to increased atmospheric greenhouse gas concentrations.
General Circulation Models represent physical processes in the atmosphere, ocean, cryosphere and land surface and the data put into the models are large-scale distributions of atmospheric temperature, precipitation, radiation, wind, sea temperatures, ocean currents and sea ice cover.
The models are becoming increasingly complex but are also beginning to show more consistent projections. With increasing computing power there is increasing confidence in the models but it should be remembered that they will only simulate the interactions in the climate systems well if there is a good understanding of the processes that govern the climate system.
Models are evaluated by comparing their predictions to current and past climate and these evaluations are providing increasing agreement and confidence. Projections on temperature are less uncertain than those of rainfall.
Confidence in projections is higher for some models than others. However, some of the global climate models do show the changes that have occurred in the broader region of the south-west in terms of atmospheric instability, storm track modes and rainfall
Although the projections are uncertain, the models simulate the patterns of high and low pressure systems in the westerly wind belts quite well. Therefore there is less uncertainty about the projections of a drying climate in the south-west than other climate projections and 90 per cent of the global models in CMIP3 agreed that the south-west will become dryer.
Nevertheless, projections from global climate models need to be regarded with caution, particularly when dealing with climate at the sub-regional scale. It is very important to recognise their limitations.
Confidence in climate model projections decreases at finer scales, because at finer spatial scales the magnitude of natural variability in climate increases and local influences on climate become more significant.
Although the models are not currently specific to particular parts of the South Coast region, there is strong evidence from south-west projections that much of the region needs to adapt to a warmer and dryer climate, or at least to more frequent hot dry seasons.
The CSIRO and Bureau of Meteorology are producing more fine scaled projections. Some of the terms the scientists use in the projection information they provide to NRM groups are outlined below.
Representative Concentration Pathways
Climate projections have to use an estimate of greenhouse gases in the atmosphere at a given time to determine the impact on future climate. The projections depend on the amount of greenhouse gas emissions and therefore on human activities in the future. This is difficult to calculate and climate modellers need to have a consistent set of scenarios.
In the third and fourth Intergovernmental Panel on Climate Change (IPCC) reports, the Special Report on Emissions Scenarios (SRES) was used, which were four narrative storylines labelled A1, A2, B1 and B2. Each storyline represented different demographic, social, economic, technological and environmental developments.
To ensure consistency for modelling and projections, in its fifth report, the IPCC decided to use four representative scenarios. These scenarios give an estimate of the extra heat energy (radiative forcing) from emission of greenhouse gases to 2100. They include a pathway of greenhouse gas concentrations, over time to 2100. Models of the carbon cycle are used to convert emissions into atmospheric concentrations of CO2 in parts per million.
The Representative Concentration Pathways (RCPs) are therefore representative of possible future emissions and concentrations of CO2. They include one early mitigation scenario leading to a very low forcing level with a peak and decline (RCP2.6), a stabilisation before 2100 (RCP4.5) and stabilisation after 2100 (RCP6) and one very high emission scenario where there is little action to reduce greenhouse gas pollution and emissions are still rising (RCP8.5) (Table 1). The advantage of using RCPs is they allow consistency in climate modelling.
Table 1 Representative concentration pathways with different scenarios
|Early Mitigation, with peak and decline before 2100
|Stabilisation before 2100
|Stabilisation after 2100
|Emissions still rising after 2100
Figure 1 Comparison of carbon dioxide concentrations for the 21st century from the RCPs and SRES scenarios. RCP8.5 is closest to A1FI, RCP6 is closest to A1B, RCP4.5 is similar to B1, and RCP2.6 is lower than any of the standard SRES scenarios. The SRES scenarios were used in the third IPCC report. Source: Jubb et al. 2013 (Data from Meinshausen et al 2011 and IPCC TAR WG1 Appendix 2).
Each RCP is a measure of approximate extra radiative forcing in 2100 compared to 1750. Radiative forcing is a measure of the energy absorbed and retained in the lower atmosphere. For an RCP of 8.5, the radiative forcing in 2100 would be 8.5 Watts/m2. That represents the extra warming from greenhouse gas pollution if emissions were still rising at the end of the century. The amount of warming can’t be predicted precisely because other factors could influence the climate systems, but it gives some indication of the consequences of continuing CO2 emissions versus mitigation.
Although the different RCPs don’t show large differences up to 2030 they diverge, particularly after 2100. In other words, even though the climate to mid-century may not be very different under different levels of mitigation, the implications for climate change late in the century and in the next century are much larger.
Climate modeling and particularly climate projections are coordinated through a series of major projects called Coupled Model Intercomparison Projects (CMIP). The ‘Coupled’ refers to the coupling of Ocean General Circulation Models and Atmosphere General Circulation Models. It is now in phase 5 to correspond with the IPCC’s fifth report.
Coupled Model Intercomparison Project Phase 5 (CMIP5)
The Coupled Model Intercomparison Project (CMIP) involves the coordination of a range of climate model experiments and projections. Its objective is to better understand past, present and future climate changes arising from either natural climate variability, or in response to changes as a result of human activities causing increased greenhouse gas emissions.
It collects the output from the global coupled atmosphere general circulation models. Amongst other objectives, CMIP5 provides climate projections out to 2035 and 2100 and beyond. CMIP5 projections include factors that were not included in CMIP3 but which may be important for South Coast Climate. For example CMIP 5 includes ozone hole recovery, which is likely to have an impact on the South Coast climate.
CSIRO and BoM are providing the projections from CMIP 5 to the Regional NRM groups as a tool to assist them in planning for climate change.
Statistical Downscaling and Regional Climate Models
Regional NRM planning requires information at finer spatial scales than provided by the coarse resolution of global climate models. Statistical downscaling is the process used to transform climate information at large scale to higher resolution.
Regional climate models are nested in the global climate model to increase the resolution. The outputs from the global climate model are used as inputs for the regional climate model which contain finer scale information such as land use and topography.
Downscaling does not reduce the uncertainty in the models, but can help to see how well they are behaving in relation to actual temperature and rainfall in a given location, such as a water catchment.
The projections from downscaling must be used with caution as there has been some limited statistical downscaling for small-scale areas of the region in the past. For example Smith et al (2009) used statistical downscaling of the CSIRO Global Climate Model for the Denmark catchment. They found the rainfall distribution in Denmark was different from the actual distribution with the model showing lower rainfall in autumn, winter and spring and higher in summer than the measured rainfall.
The period used can also influence the modeling, because there appears to have been a change in climate drivers from 2000 on the South Coast. Another problem is that different downscaling methods can produce different results.
“It is becoming apparent, however, that downscaling also has serious practical limitations, especially where the meteorological data needed for model calibration may be of dubious quality or patchy, the links between regional and local climate are poorly understood or resolved, and where technical capacity is not in place. Another concern is that high-resolution downscaling can be misconstrued as accurate downscaling.” (Wilby and Dessai, 2010.)
Although the projections for the broader south-west are considered robust, information on local climate influences on the South Coast is more limited so any statistical downscaling provided by CSIRO and BoM needs to be evaluated at a local scale.