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Coupled Global Climate Change Model 3.1 (T47) Report

Currently, researchers use and cross-examine information gathered from multiple climate

change models to support claims and hypotheses for climate change trends and predictions. Of the

many models used, Coupled Global Climate Change Models (CGCMs) are of the most accurate, since

they simulate global climate change based on combined sets of data generated from separate models.

The CGCM .! (T"#) is a third generation model de$eloped by the Canadian Centre for Climate

Modeling and %nalysis(CCCM%) and run on a &'C *+ $ector supercomputer hich runs on a ne

distributed memory M computer system. The CCCM% is a di$ision of the Climate /esearch ranch

of 'n$ironment Canada. The Canadian go$ernment sponsors 'n$ironment Canada, a business group

stri$ing to conser$e the en$ironment, hich funds researchers and hosts information a$ailable to the

public online, generated by climate models from the CCCM% !,",0 .

The CGCM .! model predicts seasonal and*or annual climate change for a particular region.

The model calculates such change ith $ariable units of total daily precipitation, minimum and

maximum daily temperature, and the mean daily temperature. The CGCM .! is typically used to

compile seasonal or annual mean data into thirty year periods from hich obser$ers ma1e analyses and

predictions. The model also ta1es into account input from measurements of the atmosphere, ocean, sea

ice, coupling(flux ad2ustments), and land. pecific humidities, pressure le$els of the atmosphere,

geopotential heights and mean sea le$el pressure are examples of some necessary $alues incorporated

into certain calculations ithin such parameters. 3, ,0

The coupled nature of the CGCM .! (T"#) stands out from most other climate models. The land

and ocean components are coupled ith the T+ model in order to more accurately simulate the global

climate. Though T"# and T+ may ha$e se$eral similar components, the t o models differ in spatial

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resolution 4 therefore, combined, they pro$ide a broader range of accurate climate data. oth models

are 5uite similar to one another, ho e$er they are fine tuned to a specific region of focus. The T+

$ersion supplies detailed information of 6onal currents in the tropics and some hat reduces problems

ith con$erging meridians in the %rctic. On the other hand, the T"# does a significantly better 2ob atmodeling atmospheric conditions due to the addition of an updated %tmospheric General Circulation

Model. 0,+

n terms of greenhouse gas emissions, the CGCM .! (T"#) is used to obser$e changes in

temperature and precipitation rates, ho e$er, it may also predict trends of greenhouse gases li1e CO3,

ith similar trends from the graphs in loom7s textboo1. 8espite the model7s capabilities 4 from hat

7$e gathered in the little research 7$e performed 4 the T"# model is not often used to measure such

5ualities of greenhouse gases, but rather, it is used more so for analy6ing cyclone genesis potential

and*or other eather phenomenons. ",#,9

The CGCM .! (T"#) model has some robust features hich ma1e it more or less useful in

obser$ing certain patterns of climate change, particularly trac1ing the paths and effects of storms on the

local en$ironment. Though the T"# model lac1s more up-to-date components for ocean and sea ice

modeling, the T+ model ith hich it is coupled ma1es up for the missing computational analyses.

belie$e the model still adds important information to the global climate models already in use, but feel

as though there is room for some modifications. :erhaps there are un1no n reasons for hy such

enhancements ha$e not been made, but for the time being, am una are of any such rationale. There

must be a lot of money in$ol$ed in the de$elopment of such models and funding may be lo or

allocated else here, hich might explain the basis for coupling such models rather than programming

an entirely ne one. ;or hate$er the reason may be, 7m certain that in the coming decade (or 7m

hoping), ne climate models ill be produced ith a higher percentage of accuracy.

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Bibliography:

!. ;lato, G.M. and G. ?arming %symmetry in Climate Change imulations. Geophys. Res. Lett. , 39, !@0-!@9.

3. ;lato, G.M. and Aibler, ?.8. , !@@3> Modelling :ac1 ce as a Ca$itating ;luid. J. Phys.Oceanogr. , 33, +3+-+0!.

. :CC, 3==!> Climate Change 3==!> The cientific asis.