CSSS 2009 Santa Fe-Modeling-Cluster: Difference between revisions
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==Modeling Cluster== | == Modeling Cluster == | ||
Gina La Cerva, Joe Geddes, Regina Clewlow, Ha Nguyen, Christa Brelsford, Adam Wolf | Gina La Cerva, Joe Geddes, Regina Clewlow, Ha Nguyen, Christa Brelsford, Adam Wolf | ||
==== Motivating | ==== Motivating Questions ==== | ||
13) How can we better quantify uncertainty when we are in uncharted territory of the climate system (where change is happening faster and involving feedbacks we don't yet understand? | 13) How can we better quantify uncertainty when we are in uncharted territory of the climate system (where change is happening faster and involving feedbacks we don't yet understand? | ||
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==== Overall | ==== Overall Objectives for Modeling ==== | ||
We agree that human-climate interactions are the most critical area of climate science modeling, because these have feedbacks which can either mitigate warming or amplify the consequences of warming. Furthermore these interactions are largely unexplored in a coupled system where feedbacks can be directly evaluated. | We agree that human-climate interactions are the most critical area of climate science modeling, because these have feedbacks which can either mitigate warming or amplify the consequences of warming. Furthermore these interactions are largely unexplored in a coupled system where feedbacks can be directly evaluated. | ||
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- scaling approaches to evaluate model realism --> implies data against which models can be evaluated | - scaling approaches to evaluate model realism --> implies data against which models can be evaluated | ||
- Crude Look at the Whole (CLAW) | |||
==== Notes on Discussion (21 July 2009) ==== | |||
- normative models vs descriptive models | |||
- macroeconomists largely ignored financial system; recent collapse in finance led to cascading collapse throughout macroeconomy (Ref: Economist article) | |||
- importance of getting assumptions right from the beginning; possibility of using agent based models to avoid having to make as many assumptions | |||
- water rights in Arizona (can't trade them; use or lose); interactions between humans, political system, natural environment | |||
- can use REEDS model to some extent to figure out how to flip grid to include larger amount of renewables | |||
- stranded assets (investments made under old regulatory regime become much less valuable under new rules) | |||
- lock in effects are very imporant; how to get out is hard problem ("buying out" actors who would otherwise have lots of stranded assets) | |||
- how to make a financial product that acts as a catalyst to reduce economic barriers to change (help overcome lock in? | |||
- corn ethanol, Mississippi river as examples of lock in | |||
- What do we really mean by a "regime" of behavior in one of these extremely complex models? How can we recognize a regime when we see one (either in the computer model or when observing the system? | |||
- lock in is related to resilience (ie lock in state is resilient to change) | |||
- models of the political process (eg game theory [see paper on model of climate negotiations], Sam Bowles at SFI) | |||
- validate agent based models using game theory results in simplified situations | |||
- skepticism about game theory | |||
- What can be done (or can be expected to be done) with agent based models that could not be done with other modeling approaches? | |||
--- can it predict a transition path to a new state (eg involving more renewables, etc) that traditional (general equilibrium) economic models don't show | |||
--- need for self reinforcing shift | |||
--- a agent-based models simply change one set of assumptions (about set behavior of agents) for other set (have to argue that these assumptions are better in some way) | |||
- in previous changes (industrial revolution, agriculture) arose spontaneously (or did they) | |||
--- "The Prize" (gov'ts fought to create oil industry?); however once oil industry got going, it was self reinforcing | |||
--- but is the transition to post-fossil fuel economy different (because problem is global warming, not running out of fossil fuels, at least not yet) | |||
- how to get {renewable energy, efficiency, other sustainable practices} to point where they are self reinforcing?; what policies, technologies, cultural change, etc would be needed? | |||
- NREL is interested in incorporating behavioral economics and possibly agent-based models | |||
- Can a few big players shift the system (colloquially, a few more WalMarts)? | |||
- stability of the grid when nondispatchable resources are added in large quantites | |||
- utilities are key agents (large, reactionary) | |||
- cash for clunkers (buying old cars to get them off the road) | |||
--- but what about eg relatively new coal plants in bad site for sequestration that still need to be decommissioned to reach 350 ppm? | |||
- need list of ways people have modeled economy and climate interactions in the past (ie proto lit review, covering neoclassical approaches, etc) | |||
==== A Possible Integrating Outline ==== | |||
Framing question: | |||
What tools can complexity science offer sustainability? and what tools can be developed | |||
-Technology | |||
-Social inputs to climate change | |||
-mechanisms of impact | |||
-integrative | |||
-anything else? | |||
Latest revision as of 21:08, 22 July 2009
Modeling Cluster
Gina La Cerva, Joe Geddes, Regina Clewlow, Ha Nguyen, Christa Brelsford, Adam Wolf
Motivating Questions
13) How can we better quantify uncertainty when we are in uncharted territory of the climate system (where change is happening faster and involving feedbacks we don't yet understand?
14) How do we develop useful integrated models? Are there feedback mechanisms that we don't understand?
27) What methods can be used and developed to quantify interactions between previously developed models of human, physical, and economic systems?
(I think this following question should be taken up by the ecosystem services group:)
31) What technologies or tools are still needed to evaluate environmental impacts?
Overall Objectives for Modeling
We agree that human-climate interactions are the most critical area of climate science modeling, because these have feedbacks which can either mitigate warming or amplify the consequences of warming. Furthermore these interactions are largely unexplored in a coupled system where feedbacks can be directly evaluated.
Several key human-climate interactions:
+ market dynamics that can lead to decarbonized energy technology implementation. tipping points. policy. investment.
- human migration
- increased energy use in adaptation, e.g. use of air conditioning
- infectious disease
Modeling Objectives
Several uses for models were identified, including
- policy evaluation (sensitivity analysis)
- validation
- forecasting and uncertainty analysis
Types of Models
- agent based modeling of markets, investment, policy
- agent based modeling of control systems
- scaling approaches to evaluate model realism --> implies data against which models can be evaluated
- Crude Look at the Whole (CLAW)
Notes on Discussion (21 July 2009)
- normative models vs descriptive models
- macroeconomists largely ignored financial system; recent collapse in finance led to cascading collapse throughout macroeconomy (Ref: Economist article)
- importance of getting assumptions right from the beginning; possibility of using agent based models to avoid having to make as many assumptions
- water rights in Arizona (can't trade them; use or lose); interactions between humans, political system, natural environment
- can use REEDS model to some extent to figure out how to flip grid to include larger amount of renewables
- stranded assets (investments made under old regulatory regime become much less valuable under new rules)
- lock in effects are very imporant; how to get out is hard problem ("buying out" actors who would otherwise have lots of stranded assets)
- how to make a financial product that acts as a catalyst to reduce economic barriers to change (help overcome lock in?
- corn ethanol, Mississippi river as examples of lock in
- What do we really mean by a "regime" of behavior in one of these extremely complex models? How can we recognize a regime when we see one (either in the computer model or when observing the system?
- lock in is related to resilience (ie lock in state is resilient to change)
- models of the political process (eg game theory [see paper on model of climate negotiations], Sam Bowles at SFI)
- validate agent based models using game theory results in simplified situations
- skepticism about game theory
- What can be done (or can be expected to be done) with agent based models that could not be done with other modeling approaches?
--- can it predict a transition path to a new state (eg involving more renewables, etc) that traditional (general equilibrium) economic models don't show
--- need for self reinforcing shift
--- a agent-based models simply change one set of assumptions (about set behavior of agents) for other set (have to argue that these assumptions are better in some way)
- in previous changes (industrial revolution, agriculture) arose spontaneously (or did they)
--- "The Prize" (gov'ts fought to create oil industry?); however once oil industry got going, it was self reinforcing
--- but is the transition to post-fossil fuel economy different (because problem is global warming, not running out of fossil fuels, at least not yet)
- how to get {renewable energy, efficiency, other sustainable practices} to point where they are self reinforcing?; what policies, technologies, cultural change, etc would be needed?
- NREL is interested in incorporating behavioral economics and possibly agent-based models
- Can a few big players shift the system (colloquially, a few more WalMarts)?
- stability of the grid when nondispatchable resources are added in large quantites
- utilities are key agents (large, reactionary)
- cash for clunkers (buying old cars to get them off the road) --- but what about eg relatively new coal plants in bad site for sequestration that still need to be decommissioned to reach 350 ppm?
- need list of ways people have modeled economy and climate interactions in the past (ie proto lit review, covering neoclassical approaches, etc)
A Possible Integrating Outline
Framing question:
What tools can complexity science offer sustainability? and what tools can be developed
-Technology
-Social inputs to climate change
-mechanisms of impact
-integrative
-anything else?