6. Measuring or Modelling?!
• Expensieve
• Mostly in One point (in few
locations)
• Difficult
• Technical Expertise
• Control quality!
• Calibrattion (the Equipment)
• Real Values?
• (Effects of) Unknown
Parameters?
• Ready to Use?
• Using in Model Verification
• ….
• ….
Measurements
7. Measurement or Simulation?!
• Inexpensieve / Cost-effective?
• (Effective) Parameters?
• (Algorithm) Sensitivity
• Validation (Challenge!)
• Computational Resources
• Mathematical Issues
• Bad / Good Model?
• Cost Effective
• Spatial Distribution
• Temporal Distribution
• Understanding the Process
• Desinging / Evaluation
• Generalizable?
• …
Simulation
8. Measurement or Simulation?!
Reliability of
Measurements? Data
Quality Control?
Measurements for
Model Validation
(Which / How)?
Simple or Complex
Model? Good / Bad
Models?
Interaction
(Impact) of the
Data (Quality) and
Model?
Simplifying the
Model? Yes/No?
…
10. Measurement or Simulation?!
(Climate)Models are unreliable.
"[Models] are full of fudge factors that are fitted to the
existing climate, so the models more or less agree with
the observed data. But there is no reason to believe that
the same fudge factors would give the right behaviour in
a world with different chemistry, for example in a world
with increased CO2 in the atmosphere."
(Freeman Dyson)
12. Tools/Software
Commercial Software The Easy Road?!
Free/OS Software The Hard Road?!
The easy road often becomes hard, and the hard road often becomes easy
(Robert Kiyosaki)
15. Parallel Computing
A graphical representation of Amdahl's law. The speed-up of a program from parallelization
is limited by how much of the program can be parallelized. For example, if 90% of the
program can be parallelized, the theoretical maximum speed-up using parallel computing
would be 10x no matter how many processors are used.