Monitoring & Predicting Climate Change (Cambridge (CIE) AS Environmental Management)
Revision Note
Written by: Alistair Marjot
Reviewed by: Bridgette Barrett
Monitoring & Predicting Climate Change
The ability to monitor and predict climate change is important in order for us to understand the complex dynamics of Earth's climate system and anticipate future changes:
Scientists use various observational techniques, data sources and computational models to monitor past climate trends and forecast future climate scenarios
Difficulties in Monitoring and Predicting Climate Change
Limited historical data:
Reconstruction of past climate conditions relies on sparse historical records, which can sometimes lack detail, such as ice cores, sediment layers and tree rings:
For example, ice core analysis from Antarctica provides insights into atmospheric composition and temperature variations over millennia
However, these records may not always capture detailed regional climate variability or extreme events
Complex climate models:
Future climate projections rely on sophisticated computer models that simulate interactions between the atmosphere, oceans, land surfaces and ice
However, these models always have uncertainties as they attempt to replicate highly complex Earth system processes:
For example, climate models struggle to accurately simulate the behaviour of clouds, which play a crucial role in regulating Earth's energy balance and global temperatures
Uncertainty in feedback mechanisms:
Climate feedback mechanisms, such as the albedo effect and carbon cycle feedbacks, introduce complexities and uncertainties into climate predictions:
For example, melting Arctic sea ice reduces the Earth's albedo, leading to increased absorption of solar radiation and further warming
These feedback loops are challenging to model accurately and may lead to unpredictable climate responses
Time delays:
There is a lag between the emission of greenhouse gases and their impacts on the climate system:
For example, carbon dioxide emissions from fossil fuel combustion can persist in the atmosphere for centuries, contributing to long-term climate change
However, we are only just now starting to feel the full effects of centuries of carbon dioxide emission from fossil fuel combustion (i.e. since the start of the industrial revolution)
Predicting the timing and magnitude of future climate impacts requires careful accounting for these time delays
Data uncertainty and interpretation:
Climate research relies on diverse datasets from various sources, including satellite observations, ground-based measurements and paleoclimate proxies
Discrepancies in data quality, measurement techniques and interpretation methods can lead to uncertainties in climate predictions:
For example, disagreement over temperature reconstructions from tree ring data has caused debates about historical climate variability
Modelling Future Climate Change
It is possible to use existing data relating to global warming to make predictions about global temperatures in the future:
Using data in this way is known as extrapolating from data
Extrapolated data can be used to produce models that show how the climate may change in the future
Global warming predictions can be used to:
Plan for the future, for example:
Building flood defences
Funding scientific research into climate change technologies
Encourage people to change their activities, for example:
Reduce the burning of fossil fuels
Increase the use of renewable energy sources such as solar and wind energy
Reduce meat consumption
The Intergovernmental Panel on Climate Change, or IPCC, is a group of climate scientists around the world that has used existing data to extrapolate how global temperatures might change in the future under different human activity scenarios, for example:
If humans manage to immediately begin reducing fossil fuel use, global temperature change could be limited to around 1 - 1.5 °C
If humans do nothing to change their fossil fuel use, global temperature increase may exceed 4°C
The IPCC data can be added to other computer models on climate change to see how different parts of the world might be affected under the different scenarios
There are limitations to models based on extrapolated data:
The IPCC has produced models based on several emissions scenarios, and we do not know which of these scenarios is most likely:
I.e. we don't know how successful humans will be at cutting greenhouse gas emissions
We do not know whether future technologies will be successful at removing greenhouse gases from the atmosphere e.g. carbon capture technologies may or may not be effective
It is unknown exactly how atmospheric gas concentrations might affect global temperatures
Global climate patterns are complex and therefore predictions are difficult:
It is possible that a certain tipping point in global temperatures could lead to a sudden acceleration in global warming e.g. permafrost melting may cause a sudden increase in atmospheric methane
We don't know exactly how factors other than human activities may affect climate in the future e.g. a volcanic eruption could increase ash in the atmosphere, reflecting radiation back into space and cooling the earth
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