Developing Human System Modules for Regional Climate Models

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Developing Human System Modules for Regional
Climate Models

• Jessie Cherry
• IARC/INE/ARSC_at_UAF
• Peter Larsen
• GSPP/LBNL_at_UC-Berkeley

Arctic System Modeling Workshop III, University
of Quebec, Montreal, July 2009
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Presentation Outline

• Old school approach to the study of Human
  Dimensions (HD) of Climate Change
• Shortcomings with the old school approach
• Some examples of HD modeling
• Direct integration of HD into regional climate
  modeling (i.e., new school)
• Implementation potential for particular sectors
  and
• Benefits to developing an international HD
  working group for the Arctic.

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General Climate-related Modeling Approaches
Source IPCC, 2007
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Past Treatment of Human Dimensions

• Second (or third-order) modeling runs
• Limited use of downscaled physical projections
• Few examples of model comparison/testing
  platforms and input/output sensitivity analyses
• Weighted index, Delphi, and/or subjective
  approaches are often employed and
• Stakeholder feedback often occurs later on in the
  development process, if at all.

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Examples of Modeling HD Alaska
HD Project Estimating Risk to Alaska Public
Infrastructure from Climate Change (Larsen et
al, 2008)
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Examples of Modeling HD Alaska
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Examples of Modeling HD California
HD Project Estimating Risk to California
Energy Infrastructure from Climate Change
(Sathaye et al, 2009)
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Examples of Modeling HD California
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Past/Current HD Modeling Concerns

• The old school de-coupled HD approach
• creates a strong disconnect between the physical
  modeling and the climate impacts communities
• occasionally ignores stakeholder needs for timely
  policy and decision making
• often misses important feedbacks between human
  agents and the climate system and
• makes it difficult to compare and test
  alternative modeling techniques.

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Some Arctic Human Dimensions.

• Resource Development
• Hazard Response
• Freshwater Supply
• Renewable Energy (wind, hydro, geothermal)
• Commercial and Sport Fishing/Hunting
• Public and Private Infrastructure
• Tourism
• Subsistence Harvest
• Marine Transport
• Human Health

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A New School HD Modeling Proposal.

• Develop Human System Modules directly into the
  Arctic System Modeling platform
• Make these modules portable and transparent
  between different regional models
• Encourage international collaboration
• Focus on producing multiple socioeconomic impact
  measures and
• Facilitate model testing, scenario development,
  stakeholder feedback, etc.

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Some Thoughts on Decision Support/Stakeholder
Feedback

• Turban defines decision support as "an
  interactive, flexible, and adaptable
  computer-based information system, especially
  developed for supporting the solution of a
  non-structured management problem for improved
  decision making. It utilizes data, provides an
  easy-to-use interface, and allows for the
  decision maker's own insights. (Wikipedia, 2009)
• Decision support and ongoing stakeholder feedback
  are very important factors to incorporate if the
  Arctic System Model is going to be successful.
• What metrics will we use to gauge the overall
  performance of this entire Arctic system?

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Some Thoughts on Climate/HD Model Interactions

• Need not occur at each model time step (e.g.,
  hours vs. planning decades)
• One or two-way coupling may be appropriate
  depending on the system (e.g., GHG emissions)
  and
• Socioeconomic data collection and dissemination
  will need to be substantially improved
• Quantifying coupled model uncertainty is very
  important, but difficult to communicate.

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Some Thoughts on Communicating Uncertainty in HD
Impacts
Source Larsen et al (2008)
Three different AOGCMs
Monte-carlo Simulation (varied inputs)
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More Thoughts on Uncertainty in HD Impact
Estimates
Harvard Economics Professor Martin Weitzman noted
in a seminal 2008 paper that fat-tailed
structural uncertainty about climate change,
coupled with a lack of information about
high-temperature damages, can potentially
outweigh the influence of discounting in a
cost-benefit analysis framework.
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What are the Challenges?

• Training and supporting interdisciplinary
  researchers may be the biggest challenge
• Pan-Arctic data collection and management is
  another major challenge
• Stakeholder engagement is time-consuming and
  expensive
• Some research disciplines are further along in
  the evolution of systems modeling and
• User-friendly decision support tools will need
  to be developed in close collaboration with
  stakeholders.

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Why include HD modules directly into the ASM?

• There are (some) appropriate existing regional HD
  models
• We have the computing resources
• We can attempt to minimize miscommunications
  between the physical and social scientists across
  the Arctic
• Its interesting and policy-relevant work at the
  frontiers of research!!!

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Benefits to Developing an International HD
Working Group

• The Arctic countries share many common HD because
  of similar regional climate, geography, history,
  etc.
• The Arctic countries also share common
  vulnerabilities
• HD data is often disparate and difficult to find,
  particularly at the Pan-Arctic level and
• There is considerable experience within various
  Arctic countries in the study of HD, but there is
  less knowledge sharing occurring across countries.

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Questions?
Reminder HD Breakout Session Later Today.
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Additional Information

• International Arctic Research Center at UAF
  www.iarc.uaf.edu
• Alaska Center for Climate Assessment and Policy
  (ACCAP) www.uaf.edu/accap/
• State of Alaska Climate Change Materials
  www.climatechange.alaska.gov
• E.O. Lawrence Berkeley National Laboratory
  www.lbl.gov
• Goldman School of Public Policy
  www.gspp.berkeley.edu
• Note This presentation includes personal views
  of Peter Larsen.

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Climate Change Planning
Walsh Chapman PRISM downscaled multi-model
projections of temperature and precipitation for
AK under various scenarios of Greenhouse Gas
emissions
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Integrated Assessment

• Definition any model which combines scientific
  and socio-economic aspects of climate change
  primarily for the purpose of assessing policy
  options for climate change control (Kelly
  Kolstad, 1998)

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Integrated Assessment Modeling
McGuffie Henderson-Sellers, 2005
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Integrated Assessment Models
McGuffie Henderson-Sellers, 2005
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Example of Human System Module
Goal is to be model independent work with CCSM
and other models/ couplers
Cherry
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Communicating uncertainty
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New Scientific Methodology?
Funtowicz Ravetz, in Ecological Economics, 1991
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Arctic human dimensions

• Oil and Gas Module (spill transport)
• Rural Resilience (wind power potential)
• Coastal Erosion (evolving coastline)
• Freshwater (hydropower, water supply)
• Marine Fisheries (Bering ecosystem)
• Marine Transport (ice cover trajectories)

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BSIERP Lower Trophic Level Ecosystem Model
Predation Losses
Euphausiids
Detritus
14 component Model NPZD-Benthos
Neocalanus
Pseudocalanus
Large microzooplankton
Small microzooplankton
Small Phytoplankton
Large Phytoplankton
Iron
Ammonium
Nitrate
Benthic Detritus
Benthic Infauna
Benthos
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BSIERP
BSIERP Vertically Integrated models
Economic/ecological model
FEAST Higher trophic level model
NPZ-B-D Lower trophic level
ROMS Physical Oceanography
Nested models
BEST
Climate scenarios
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Infrastructure

• Impact of Climate Change on Infrastructure
  study done for Alaska by Peter Larsen and
  collaborators

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Flow Chart of Model Processes
Graphs
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ISER Public Infrastructure Study
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Wind Farm Parameterization for WRF
Adams Keith Modification of the MYJ PBL
scheme Similar work being done commercially by
3TIER, AER, others
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MMS-WRF winds 1
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MMS-WRF winds 2
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MMS-WRF winds 3
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MMS-WRF winds 4
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Hydropower AEA
AEA Energy Atlas, 2007
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Ship track
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Example of Climate-Related Decision Support

• https//rsgis.crrel.usace.army.mil/aedis/