There are to main obstacles to effective climate change policy:

1. This is a globalproblem without any kind of international organization that can either promote, adopt or enforce policy.
   
   
2. The impacts of climate change disproportionally effect populations which are generally ignored. This leads to the idea of climate change justice or to another called "just sustainability" as it was originally articulated in the early 2000s. Now that has morphed to the term "global justice".
   
   
   
   A lot of the foundation and framework for all of this can be found in the 1987 Brundtland Report -- Our Common Future (World Commission on Environment and Development) -- http://homework.uoregon.edu/pub/class/scipolicy/ocf87.pdf
   
   
   
   
   
   
   
   What about the role of Methane and CO2_e? This is not communicated enough but is a very important part of climate change policy as controlling CO₂ is not sufficient.
   
   
   
   
   
   
   
   What about a Carbon Tax? Is this at all feasible? We do now have a good Global CO₂ monitoring instrument.
   
   
   
   
   
   
   
   
   
   
   
   
   
   Systems Thinking as a regular part of Public Outreach
   
   
   
   

   The Decision Matrix Approach

   
   
   The simplest qualitative form of a decision matrix or a truth table as it was once called, is that the worst possible outcome appears in the bottom right.
   
   
   
   
   
   A 3x3 matrix example is shown below
   
   
   
   
   
   
   
   A qualitative evaluation of most common attributes in a sample of 30 Global Climate Models (GCMS) in terms of model predictions for temperature increase and rainfall increase/decrease.
   
   
   
   Another qualitative example which centers on control and action. Note appopriate use of bottom right corner.
   
   
   
   Now this is a very interesting variant particularly for public outreach as you want to identify the hyopthesis which has the least number of inconsistencies associated with it, as compared to the data. A value of C stands for consistency and is given a score of 0, a value of I is for inconsistency and is given a score of (-1). In this case hypothesis 2 is the most inconsistent, while 1 and 3 are equal.
   
   
   
   Another way to think about this is a matrix form of Impacts, Likelihoods, and assessment of the need for more research and more investment in mitigation/adaptation.