The Pileus Project: Climate Science for Decision Support

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The Pileus Project Climate Science for Decision
Support

• Julie Winkler
• Michigan State University
• February 16, 2006

Funded by the U.S. EPA
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Pileus Project Goals

• Identify, with stakeholder assistance, the
  influence of climate on the Michigan agriculture
  and tourism industries

• Create empirical and physically-based models to
  quantify the impacts of past and projected
  climate variability and change on agriculture and
  tourism in Michigan.

• Develop decision-support tools for weather and
  climate-related risk management

• Build strong stakeholder-research partnerships

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Pileus Project Core Team
Agriculture
Climate
Dr. Jeffrey Andresen Dr. Roy Black
Tourism
Dr. Julie Winkler Dr. Jeffrey Andresen
Tracy Beedy Costanza Zavalloni
Dr. Don Holecek Dr. Sarah Nicholls Dr. Peter
Sousounis
Galina Guentchev Krerk Piromsopa
Lori Martin Charles Shih Jeonghee Noh
Administration/Coordination/Communications Jeanne
Bisanz
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Why call the project Pileus?
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Why Study Climate Variability and Tart (Sour)
Cherries?

• Tart cherries are extremely vulnerable to
  temperature extremes.
• Tart Cherry yields are more variable than those
  for any other agricultural commodity in the U.S
  (0 to 150 in the last 10 years).
• Michigan is the primary producer of tart cherries
  in the U.S. (gt70 of production), and most parts
  of the value chain are in the state.
• The impact of climate on the tart cherry industry
  is not well understood and has not been
  investigated in an industry-wide context.
• Collectively, these factors allow a unique
  opportunity to link expertise in tart cherry
  production, economics, and climate science.

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Approach/Methodology

• Sequential approach used (linkage of multiple
  models) at multiple locations across the Great
  Lakes Region
• Models of tart cherry phenology, yield, and
  economic value chain were developed.
• Two time frames considered historical
  (1960-2003) and projected future (1990-2100).
• Ensemble of climate scenarios employed to
  estimate uncertainty.
• Based on stakeholder input, research results used
  to develop www-based tools for industry.
• Approach designed to be exportable to other
  systems.

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Socioeconomic Scenarios
Value Chain Economic Model(s)
Tart Cherry Simulation Model
Risk Management Decision Making Tools, Policy
Framework
Climate Observations or Scenarios
Land use change scenarios
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Stakeholder Involvement
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Historical Climate Tool

• The Historical Climate Tool provides users with
  access to over 40 years (1960-2002) of daily
  observations for seven climate variables at 15
  stations in the Great Lakes region and three
  nearby large urban areas (Chicago, Milwaukee, and
  Minneapolis). Data can be downloaded into an
  EXCEL file format for further analysis by the
  user. The climate variables are maximum
  temperature, minimum temperature, daily average
  temperature, liquid-equivalent precipitation,
  frozen precipitation, Heat Index and Wind Chill.
• The summary option for the Historical Climate
  Tool allows the user to view climate summary
  statistics in a graphical format for the seven
  climate variables listed above. Users have the
  option to view the climatological normals and
  daily extreme values by month for 1971-2000 or to
  compare recent observations for selected
  stakeholder relevant periods to climatological
  normals.

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Observed Climate Data

• Primary source is State Climatology Office for
  Michigan.
• Data come from cooperative stations and
  first-order stations
• Unique in that the temperature, liquid
  precipitation, and snowfall data have been
  subjected to additional quality-control
  procedures and missing data have been estimated
  from neighboring stations.
• Quality-controlled series for 1960-2000

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1982-1-1 to 1-15
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Future Climates

• Users can create their own scenarios.
• Use a suite of already created scenarios.
• A scenario is an internally consistent and
  plausible future state (Carter et al. 1996). A
  scenario is NOT a forecast or a prediction. A
  scenario is a tool, and the traditional
  starting point for a climate impact assessment.

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Several sources of uncertainty

• Many sources of uncertainty need to be considered
• Cascade of Uncertainty

Source IPCC, 2001
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Ensemble Approach

• Multiple scenarios for each location are used to
  estimate the quantifiable range of uncertainty.

Source IPCC, 2001
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Variables

• Basic variables (maximum temperature, minimum
  temperature, wet/dry days, and liquid-equivalent
  precipitation)
• Daily temporal resolution for multiple locations
• Climate model (GCM) based
• Empirically-derived
• Change in mean may not be very meaningful. More
  important are changes in climate variables
  relevant to an activity or industry
• The basic climate variables (i.e., maximum
  temperature, minimum temperature, and liquid
  precipitation) can be used to derive thresholds,
  spells, snowfall, etc.

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• 15 Locations
• 3 climate parameters
• Tmax
• Tmin
• precipitation
• 4 GCMs
• CCC CGCM2
• HadCM2
• MPI ECHAM4
• NCAR CSM1.2
• 2 Emission scenarios
• A2, B2
• 5 Downscaling methodologies

gt60 scenarios for each climate variable per
location
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gt60 scenarios for each climate variable per
location
2000 daily temperature and precipitation
scenarios for 1990-2100
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Future Scenarios Tool
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Projected change in the number of wet days in a
30-year period
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SUMMER
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SPRING
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Future Work

• Important spatial-temporal dynamics are missing
  from the assessment process
• International trade
• Emerging and/or declining production areas and
  markets
• Flexibility (mid-course adjustments, insurance)

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A International Collaborative Effort

• Ninety percent of world production of tart
  cherries is concentrated in only nine countries
  North America (primarily U.S.) and central Europe
  (primarily Germany and Poland).
• The German and United States industries can be
  considered mature, with a structure
  representative of much of agriculture in the
  developed world (more concentrated production
  with increasing pressure from new competitors)
• The Polish tart cherry industry is developing
  rapidly technological advances have motivated a
  steady increase in production and world trade
  volumes since 1996. Poland is now the world
  leader in tart cherry exports.
• Ukrainian industry is currently struggling with
  conversion to a free-market system. Production
  continues to supply local needs and provide
  regional benefits, but policy and infrastructure
  have constrained new long-term agricultural
  investments including those in tart cherries

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Questions?
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Contact Information

• Jeff Andresen andresen_at_msu.edu
• Julie Winkler winkler_at_msu.edu