Modeling Climate Changes
           
Atmosphere is the gaseous phase that surrounds the Earth as layers of blankets and provides necessary supports to life
on Earth. A general composition of atmosphere includes nitrogen (78%), oxygen (21%), other gases (like argon, carbon
dioxide) and a variable amount of water (average around 1%).

Temperature and humidity are two important physical properties of the atmospheric system that come with every weather
forecast. Weather is a daily-basis prediction of the changes of these parameters while climate is a long-term average of
weather. Therefore any climate model has at its very core a weather forecast model and temperature is the main concern in
any prediction.

Commonly climate models often cover time-span of decades to centuries (or even longer) although short-range models
like seasonal climate models are also used. Present day climate models are made to predict changes for the next tens to
hundreds of years and incorporate all the known constituents of atmosphere and Earth’s surface. Though highly interactive
but even certain degrees of uncertainties remain in model predictions.  

Climate System

Climate system encompasses both the atmosphere and the Earth’s surface (land, oceans and ice). The whole system
maintains a balance in receiving solar energy, reflecting part of it back to the space while capturing some within the Earth’s
atmosphere, hence making the planet warm and suitable for life. If all the incoming energy would reflect back to the space
Earth would be a cold planet to live making life impossible. This trapping of infrared radiation which causes a rise of
atmospheric temperature is in fact the “Greenhouse Effect”. Therefore a greenhouse effect is very essential for life on Earth.
Computer models make simulations of this greenhouse effect as part of the whole system and add man-made influences
to it (like the higher rate of CO2 emissions during the last hundreds years).

Energy Balance of Earth
Computer Models

A computer model is a simulation of events or processes for which corresponding mathematical equations are solved
numerically whereby the derivatives of the differential equations are replaced by finite differences that approximate them.
Therefore the modeled area is divided into many small grids. A higher resolution meaning that a 100 m x 100 m grid will
give better approximation of the event than a 500 m x 500 m grid. That is why in a groundwater model areas close to an
extraction well are refined finer than areas farther away from the well. The aim is better approximation of the modeled
results to the observed data.

Present-day Climate Model

Modeling climatic changes incorporates all the key processes operating in the climate system and expresses these
processes in mathematical terms. Each process itself again is calculated from relevant factors associated with it. While
bringing it all together is often needed some kind of attributes to the corresponding variables called co-efficients.

On both empirical and theoretical grounds it is thought that skilful weather forecasts are possible perhaps up to about 14
days ahead. At first sight the prospect for climate prediction, which aims to predict the average weather over timescales of
hundreds of years into the future, if not more does not look good! However the key is that climate predictions only require
the average and statistics of the weather states to be described correctly and not their particular sequencing (Thorpe,
2005). More advanced climate models like HadGEM1 can make predictions for the next 100 to 1,000 years (Pope, 2007).

While the mid 1970s climate models only included carbon dioxide, solar radiation, and rain, models done in 2007 include
more features like

      
   - clouds,
         - land surfaces,
         - ice,
         - oceans,
         - carbon cycle and
         - chemical reactions in the atmosphere.

Distribution of cloud types, specially improved representation of low-level cloud (supposed to play a key role in climate
system) and representation of ice (e.g., the spatial distribution of ice thickness) have made models more sophisticated and
precise. Therefore the credibility of these very interactive models for future projections has increased many folds.

Uncertainties in Model Predictions

Computer models are always subject to uncertainties to some degrees while simulating the real-world phenomenon. The
accuracy missing is partly due to limitations of our knowledge to the natural processes which are in fact very complex and
partly due to the computing resources available. Better the understanding of the processes involved, higher the levels of
algorithms and more sophistication of computers will ensure higher accuracy of modeled results. Ongoing research in
these fields is hoped to bring substantial improvements in the coming days models.

What’s next?

Models are essential part of the ‘green-campaign’. One such success is the ‘Kyoto Protocol’ whereby industrialized
countries agreed to reduce their collective emissions of greenhouse gases by 5% below 1990 levels by 2008 – 2012. By
protecting the rainforests, developing more eco-friendly technologies, will help balancing back the Earth’s system to a
sound healthier state and save many endangered species from extinction.


                                                                                                                                                  Khaled Mahmud Shams
                                                                                                                                                                 Salzburg
                                                                                                                                                               10.09.2007
                                                                                                                      



References:

Clouds and the Earth’s Radiant Energy System (CERES).
(
http://eospso.gsfc.nasa.gov/ftp_docs/lithographs/CERES_litho.pdf)
Thorpe A.J. (2005): Climate Change Prediction – A challenging scientific problem.
(
http://www.iop.org/activity/policy/Publications/file_4147.pdf)

Pope V. (2007): Models ‘Key to Climate Forecasts’.
(
http://news.bbc.co.uk/2/hi/science/nature/6320515.stm)
___________________________________________________________________
Modeling Climate Change
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