Thoughts on Pattern Scaling

During the last week I have been consider ideas put forward at the

Pattern Scaling, Climate Model Emulators and their Application to the new Scenario Process
NCAR, Boulder Colorado, April 23-25 2014

and

Lopez et. la. 2013 Robustness of pattern scaled climate change scenarios for adaption decision support

Major Aims

• "Fit empirical / statistical relation b/w impact relevant climate variables and large scale quantities obtainable through simple models"
• "Run simple models under arbitrary scenarios and recover impact relevant outcomes by applying those relations"

• User Needs
• Impact research
• policy makers
• Social Economic
• higher resolution
• 
  
• Uncertainty
• Handling
• Quantitating 
• sufficiently low uncertainty for outcome information produced to be useful.

Standard Pattern Scaling

• Developed, tested and applied for 20 years
• provide a simplified representation of climate system responses.
• 
  
  • local (or regional) changes in these variables tend to increase linearly with the global warming over the coming century.
  1. local change can be seen as a 'response' to the global warming (GW)
  
  critical assumption is the there is linear relationship b/w a scalar, and a geographical response pattern

Flaws / Concerns

• main climate mechanisms are not linear
• feedback
• timescale in response change
• patterns evolve
• 
  

Uncertainty 

Uncertainty hard to capture

• model uncertainty
• Multimodel ensemble can reduce uncertainty
• scenario uncertainty
• depend on statistical assumption
• analysis of variance 
• map std dev.