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Modelling in geography
Geographical Perspectives (ENV-4010Y)
University of East Anglia
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Modelling in geography
Types of models o physical o conceptual o statistical o numerical Represents geographical data.
Definition – an abstraction of reality “A simplified structuring of reality which presents supposedly significant features or relationships in a generalised form... such they are valuable in obscuring incidental detail and in allowing fundamental aspects of reality to appear.” Chorley& Hagget (1967) Theory, law, hypothesis, structured idea, a role, a relationship, an equation, a synthesis of data, a word, a graph or hardware arranged for experiments
What is the purpose of a model? To provide an abstracted representation of reality A model is a model of something else rather than the thing itself A model should be as simple as possible, but no simpler (Einstein) Provides insight and understanding Used to make predictions A good model can be tested in the real world Integral part of geography today Types of models 1. Physical models o Scale models - ENV flume tank
o AQnalogues - volcanoes & solar geoengineering 2. Conceptual models - sustainability o Mathematical models 3. Statistical-empirical - satellite NDVI 4. Numerical models o analytical - cooling cup of tea o numerical - climate models Physical models
- Models that are physical systems whose form or observable behaviour both are in some way analogous to those of the actual system of interest Scale model: ENV flume tank Sediment transport in a river Use a flume tank to understand the movement of sediment in a river channel Advantage: experimental control Disadvantage: distortions between the scale of the river channel and that of the flume tank
Physical models Natural analogues: PETM & Climate Change Understand impact of rising CO 2 based on periods in Earth history Relationship between temperature and atmospheric CO 2 concentrations Palaeocene-Eocene Thermal Maximum, 55 Ma ~5 °C global warming Evidence points to a massive release of carbon to the atmosphere Modelling work by Cui et al (2011) shows a release rate of only 0.3-1 PgC yr-
Sustainable
Environment Economic
Viable
Bearable Equitable
Conceptual model: Earth energy balance
Conceptual models – Advantages & Disadvantages Advantages Ways of expressing understanding of a system, idea, or ‘concept’ Are widely used in geography, both physical and human Often a good starting point for building a mathematical model
Disadvantages Without empirical information it can't be tested against independent observations or used to generate predictions Oversimplification fails to convey the complexity and nuances of an issue
Mathematical models
- Use formal equations to represent the relationships between system components Statistical-empirical Calibration models Statistical – consisting of or based on statistics Empirical – derived from or guided by experience or experiment
Numerical Start from first-order theoretical principles and specify mathematical equations from which to deduce the interactions within a system E. Representation ocean currents in a climate model. ( NB: includes statistical- empirical components)
Statistical-empirical Analysis or empirical investigation provides evidence for a relationship between variables Statistical relationship found in the observations, that can then be used to make predictions about future behaviour Parameterization – the process of assigning values to parameters Statistical-empirical: Flood control engineering Equation that relates the dependent variable, e. stream flow Q [ ] to the independent variable, e. rainfall R [].
Difference between the temperature of the tea and the temperature of the surrounding air
Numerical models: Analytical & Numerical Tea example is an example of an analytical model Analytical model: an equation or set of equations based on physical understanding that you can solve , i. what temperature will the tea be at at a particular time. Most problems in geography are too complex to be described by analytical models and are instead modelled numerically Numerical model: takes incremental steps towards the solution. Complex systems, are modelled by a set of interrelated equations that are solved in this small step approach.
Numerical models: climate change
Met Office Hadley Centre UKESM
Issues with modelling in geography: Tools to further understanding Representations of processes Enables understanding of processes to be compared with data and observations Can be refined and improved based on new observations Value of simple models versus complex models Uncertainty , truth? Sensitivity analysis o Alter parameters to investigate if your model is particularly sensitive to small changes in particular parameters
Issues with modelling in geography 1. Validation, induction and emergence o How to test and evaluate a mathematical model? Verification o Ensure there are no ‘bugs’ in the computer code and check the maths is working Validation Compare model outputs against some measurements of the same variables to test the empirical adequacy of the model. E. carbon cycle model – does it match our long term records of atmospheric CO 2?
Philosophy of science critiques: Problem of induction Natural systems are open and dynamic Statistical-empirical describe but do not explain processes 2. Modelling as a unifying tool for the discipline?
Modelling in geography
Module: Geographical Perspectives (ENV-4010Y)
University: University of East Anglia
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