Climate Change and Climate Modeling


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Models can be used to simulate climate on a variety of geographical scales and over different periods of time. The basic laws and other relationships necessary to model the climate are expressed as a series of mathematical equations.

Chapter 4: Climate Models, Scenarios, and Projections

The climate however, is a very complex system, and supercomputers are needed for the task. Global climate models have been used extensively to project global warming in the 21 st century due to mankind's greenhouse gas pollution of the atmosphere. Estimates of future increases in greenhouse gases are inputted into the model, which then calculates how the global climate might evolve or respond in the future to the enhanced greenhouse effect. But the fact that a length of kilometres is much too crude to take important processes directly into account—like the small eddies, only a few kilometres in size, in the Gulf Stream and other ocean currents that lead to increased heat and moisture exchange between the sea and the atmosphere.

Many climate models are unable to accurately depict the course of the Gulf Stream, which originates in the Gulf of Mexico and travels northwards along the Florida coast before veering eastwards towards Europe. In a lot of models the current moves much too far to the north due the small eddies not being included.

Ideally we would have a more finely meshed global grid with squares covering no more than ten kilometres. But that would increase the number of individual calculations. Even for climate simulations spanning just a few years, a mainframe computer would need several weeks.

But experts at the AWI have now developed an alternative "unstructured grid".

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This allows the individual grid elements to be scaled down—to roughly ten kilometres—for certain selected regions. While the climate for the entire globe can be modelled using a grid with normal-sized squares, the flexibly adjustable mesh makes it to a certain extent possible to zoom in on specific regions, such as the Gulf Stream.


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The unstructured grid has added an interesting new dimension to climate modelling, which is highly important for the CMIP process. For the atmosphere, on the other hand, we use a conventionally structured model developed at the Max Planck Institute for Meteorology.

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Climate Change and Climate Modeling

But the colleagues at the AWI couple the atmospheric model with their own ocean model, which uses the unstructured grid. The results from the circa 50 climate models , which the AWI and the other CMIP partners are currently feeding into the international database, will be used by numerous other researchers during the next two years. Above all by those experts who are investigating the impact of climate change on people and habitats on our planet. Sample modelling results see graphic online : The mean global temperature trend from to according to the new AWI climate model.

The AWI climate model includes the main natural drivers of the Earth's temperature, such as solar radiation, natural greenhouse gas and aerosol concentrations as well as volcanic aerosols.

Climate Science (Stanford Encyclopedia of Philosophy)

The grey line represents the control run with natural drivers and greenhouse gas concentrations of ppm CO 2 for the year The coloured lines show the possible future development of the mean global temperature depending on the emission scenario. The fluctuations in the lines show the natural variations in the mean global temperature without greenhouse gas emissions. The AWI models have fluctuation range of roughly half a degree Celsius.

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Can Climate Models Predict Climate Change?

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The information you enter will appear in your e-mail message and is not retained by Phys. The main climate system components treated in a climate model are:. Climate models divide the globe into a three-dimensional grid of cells representing specific geographic locations and elevations. Each of the components atmosphere, land surface, ocean, and sea ice has equations calculated on the global grid for a set of climate variables such as temperature.

In addition to model components computing how they are changing over time, the different parts exchange fluxes of heat, water, and momentum. They interact with one another as a coupled system. Grid size is dependent upon the power of the computer that is available to solve these equations. Finer resolution implies a larger number of grid cells and requires a bigger and faster computer to perform the simulation.

Similarly, if grid spacing is farther apart, there are fewer points that are calculated, but the results are also less detailed. Once the simulated time rate of change is computed for example, how fast each particular grid cell is warming or cooling that rate is assumed to hold for some length of time, and the updated values are computed at each grid point according to the previous values and trends.

4.1: The Human Role in Future Climate

Then, calculations start over again for the next time interval. Simulated processes are larger than grid-scale and based on bedrock scientific principles conservation of energy, mass, and momentum. An example of a simulated process is one that represents tropical cyclones and storm activity. Parameterized processes represent more complex processes that are smaller than grid scale so, cannot be physically represented using simpler processes.

Their formulations are guided by fundamental physical principles, but also make use of observational data. An example of a parameterized process is one that represents cloud and aerosol composition. GCMs are critical tools that enable us to improve the understanding and prediction of atmosphere, ocean, and climate behavior. Models allow us to determine the distinct influence of different climate features by providing a way of exploring climate sensitivities with experiments that cannot be performed on the actual earth.

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