Modelling in Physical Geography

Question 1

what are the 2 definitions of a model?

Answer 1

1. a small scale simplified version of reality. eg- weather map for forecasting.
2. a set of equations expressing the laws that govern the evolution of the system

Question 2

why do we use models?

Answer 2

to understand system behavior, for prediction, for sensitivity analysis

Question 3

what are the 3 types of models?

Answer 3

conceptual / emperical / physical

Question 4

whats a conceptual model?

Answer 4

an outline of how a system works. eg the water cycle, carbon cycle, a glacier model

Question 5

whats an empirical model?

Answer 5

a model based on observations or experiments (data we already have)
eg - glacier surface mass - graph of y+x axis. or a river hydrograph.

Question 6

Whats a physical model?

Answer 6

based on first principles - storage, transfer, mass, conservation. (Uses equations believed to represent the
physical/chemical/biological process governing the
system)
eg- ice sheet modelling, ocean circulation, weather prediction, climate modelling, pollution.

Question 7

EMPIRICAL VS PHYSICAL

Answer 7

Empirical - 
- Based on observations
- Statistical, "black box"
- Works on anything, but often
humans, biology, complex stuff
- Easy to tweak

Physical -

• Based on first principles
• Unambiguous
• Physics, chemistry…
• Either works or it doesn’t

Question 8

whats the modelling process?

Answer 8

problem - conceptual model - mathematical model -

computer code - application

Question 9

What English mathematician, physicist, meteorologist, psychologist pioneered modern mathematical techniques for weather forecasting (Grand Forecast Factory)

Answer 9

Lewis Fry Richardson

Question 10

What are modelling uncertainties?

Answer 10

the machine could be wrong, the theory could be wrong.
numerical precision (1/3 = 0.333333333 INCORRECT)
initial conditions eg state of atmosphere is hard to know
example - double pendulum chaos

Question 11

What are theoretical modelling uncertainties?

Answer 11

THEORETICAL UNCERTAINTIES
structural - process - parameter uncertainties
process uncertainty eg - how does glacier calving work?
parameter uncertainty eg - How much do cloud droplets vary in size?

Question 12

verification and validation questions

Answer 12

• Does the model match the theory?
• Does the theory match reality?
• Model inter-comparison
• Compare with observations
• How close is close enough?

Question 13

SUMMARY

uses and limitations of models -

Answer 13

Uses -
- Models allow to understand
complex systems
- Sensitivity testing
- Prediction

limitations -
- Are only approximation of reality
- Depend on quality of inputs
- Can be "black box" predictors
- Results may match reality but for
wrong reasons