1 / 0

The Wisconsin Initiative on Climate Change Impacts U.W. Program on Climate Change October 20, 2009 Daniel J. Vimont Uni

Nelson Institute for Environmental Studies Center for Climatic Research University of Wisconsin - Madison Understanding Earth’s Past, Present, and Future. Atmospheric and Oceanic Sciences University of Wisconsin - Madison. Center for Sustainability and the Global Environment (SAGE)

anika
Download Presentation

The Wisconsin Initiative on Climate Change Impacts U.W. Program on Climate Change October 20, 2009 Daniel J. Vimont Uni

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Nelson Institute for Environmental Studies Center for Climatic Research University of Wisconsin - Madison Understanding Earth’s Past, Present, and Future Atmospheric and Oceanic Sciences University of Wisconsin - Madison Center for Sustainability and the Global Environment (SAGE) University of Wisconsin, Madison The Wisconsin Initiative on Climate Change ImpactsU.W. Program on Climate Change October 20, 2009Daniel J. VimontUniversity of Wisconsin - Madison
  2. Nelson Institute for Environmental Studies Center for Climatic Research University of Wisconsin - Madison Understanding Earth’s Past, Present, and Future Atmospheric and Oceanic Sciences University of Wisconsin - Madison The Wisconsin Initiative on Climate Change ImpactsDaniel J. VimontUniversity of Wisconsin - MadisonThanks to:Steve Vavrus, David Lorenz, Michael Notaro (CCR)Chris Kucharik (SAGE)Jack Williams (UW Geography)Wisconsin State Climatology OfficeWisconsin Initiative on Climate Change Impacts (WICCI)Wisconsin Focus on Energy Program
  3. Outline Introduction A history of the Wisconsin Initiative on Climate Change Impacts (or WICCI) WICCI Organizational Structure WICCI as a boundary organization Downscaling Methodology and Results Downscaling for Climate Impacts Assessment Conclusions
  4. Outline Introduction A history of the Wisconsin Initiative on Climate Change Impacts (or WICCI) WICCI Organizational Structure WICCI as a boundary organization Downscaling Methodology and Results Downscaling for Climate Impacts Assessment Conclusions
  5. Wisconsin Initiative on Climate Change Impacts WICCI: Partnership between the UW Nelson Institute for Environmental Studies, the Wisconsin DNR, and other state groups Goal: Assess and anticipate climate change impacts on specific Wisconsin natural resources, ecosystems and regions; evaluate potential effects on industry, agriculture, tourism, and other human activities; and develop and recommend adaptation strategies… http://www.wicci.wisc.edu
  6. Wisconsin Initiative on Climate Change Impacts History: June, 2007: Initial meeting between DNR and UW. Outlined idea. Summer, 2007: Organizational structure outlined Fall 2007 – Present: Science Council formed and operational Fall 2007: First working group(s) formed. Climate Working Group Spring / Summer, 2008: First major funding: FOE downscaling (~$183K) Jan 12, 2009: First WG meeting (>100 participants) Feb 2, 2009: Advisory Council formed http://www.wicci.wisc.edu
  7. Wisconsin Initiative on Climate Change Impacts History: Spring, 2009: “Bracing for Impact” series of lectures for public and WPT August, 2009: Submitted proposal for Great Lakes RISA Sept. 2, 2009: Brief the Secretary of the DNR, suggested coordination with the Governor’s staff. Sept. 14, 2009: Second Advisory Council Meeting (downscaling results released) Sept. 15, 2009: Public (media) release of downscaling results Sept. 21, 2009: Second working group meeting (~150 participants) Fall, 2010: First Assessment Report http://www.wicci.wisc.edu
  8. Outline Introduction A history of the Wisconsin Initiative on Climate Change Impacts (or WICCI) WICCI Organizational Structure WICCI as a boundary organization Downscaling Methodology and Results Downscaling for Climate Impacts Assessment Conclusions
  9. WICCI Organizational Structure Needs in Climate Impact Assessment Broad expertise across disciplines Stakeholder engagement Science and policy representation and expertise Legitimacy within and across scientific and policy communities Public engagement and support
  10. WICCI Organizational Structure Boundary Objects: “Objects” that sit between social worlds, like science and nonscience…. they can be used by individuals within each for specific purposes without losing their own identity (from Guston, 2001)
  11. WICCI Organizational Structure Boundary Organizations: Provide the opportunity and sometimes the incentives for the creation and use of boundary objects They involve the participation of actors from both sides of the boundary, as well as professionals who serve a mediating role Exist at the frontier of the two relatively different social worlds of politics and science, but they have distinct lines of accountability to each (from Guston, 2001)
  12. Impact Systems Physical Climate WICCI Policy WICCI Organizational Structure WICCI as a Boundary Organization
  13. WICCI Organizational Structure Science Council: ~20 members representing a variety of expertise in Wisconsin. Primary function is to organize and coordinate Working Groups that have the scientific expertise to assess climate change impacts pertinent to specific issues or areas of concern.
  14. WICCI Organizational Structure Advisory Committee: Representatives of business interests, non-governmental organizations, municipalities, agencies, state and local government, and other stakeholders. Advises WICCI, and provides engagement / link to stakeholders.
  15. WICCI Organizational Structure Operations and Outreach: Provides logistical support to the Science Council and performs outreach functions related to the mission of WICCI (e.g. media release, public lectures, etc.)
  16. WICCI Organizational Structure Working Groups: created by the Science Council to conduct science-based assessments of climate change impacts pertaining to specific topics or areas of concern and to make recommendations on adaptation strategies
  17. WICCI Working Groups Human Health Milwaukee Water Resources Coldwater Fish Soil Conservation Stormwater Agriculture Wisconsin Climate Wildlife Adaptation Green Bay Plants & Natural Communities Coastal Communities Central Sands Hydrology Forestry
  18. WICCI Future Directions Assessment Reports: First Assessment Report to be completed Fall, 2010. This will include an assessment of physical climate change in Wisconsin and specific vulnerabilities. Funding: Some sort of steady funding is needed. We have applied for a Great Lakes RISA, and will be submitting a proposal for a USGS Midwest Regional Center. Public / Political Connections: We have launched a (brief) media campaign, and will continue public lecture series. We also are actively travelling around the state to give talks, including to political groups (e.g. the Public
  19. Outline Introduction A history of the Wisconsin Initiative on Climate Change Impacts (or WICCI) WICCI Organizational Structure WICCI as a boundary organization Downscaling Methodology and Results Downscaling for Climate Impacts Assessment Conclusions
  20. Needs for Downscaled Data Characterize Uncertainty Uncertainty from: large-scale model physics, emissions scenario, transition from large to small scale, additional uncertainty (from subjective assessment) High resolution (spatial and temporal) 8-10km resolution, daily time scale Need to represent extremes Extreme precipitation is necessary for hydrology; extreme temperature for human health / forestry / others FLEXIBILITY!!! Numerous potential applications, so flexibility is needed!
  21. Global Climate Change Moving from Global to Regional Downscaling: Interpret global projections on a scale relevant to climate impacts. WICCI Climate Working Group / Focus on Energy
  22. Problems with simple interpolation:
  23. Global to Local Climate Change Moving from Global to Regional Downscaling Method: Downscale Probability Distribution, instead of actual variable. Advantages: PDF is large-scale, so method is “more true” to technique Extreme events are better characterized PDFs are more flexible – allows a variety of applications Work by David Lorenz - WICCI Climate Working Group / Focus on Energy
  24. Downscaling Precipitation and Temperature
  25. Downscaling Precipitation and Temperature The large-scale predictors do not contain all the information we need to know to predict the precipitation (P) and temperature (T) at a particular point. This uncertainty in predicting P and T has important implications for generating downscaled P and T with realistic variance and extremes. We must predict more the just the most likely value for P and T given the large scale fields, but also the distribution of the errors from this value. The downscaled P and T are the sum of 1) the most likely value and 2) a random number generated from the distribution of the errors. Both components are required to give realistic variance and extremes.
  26. Downscaling Precipitation and Temperature Train the downscaling on station data (COOP stations) and NCEP reanalysis precipitation (it’s like a GCM) Debias daily CDF of large-scale predictors from each global climate model to NCEP CDF Use downscaling relationships from observations on global climate models. Estimate parameters of sub-gridscale distribution at each station location. Interpolate distribution parameters (not actual data) to fine-scale grid - Final product: daily varying probability distribution on a high-resolution grid, for each climate model, and for each emissions scenario.
  27. Temperature: Temperature is downscaled using a standard normal distribution:
  28. Temperature: Temperature is downscaled using a standard normal distribution (valid because residuals are normal): Large Scale Small Scale (raw)
  29. Precipitation: Two steps: 1) Bernoulli distribution for rain / no rain. 2) Generalized gamma distribution for rain amount. The histogram of precipitation amount when the large-scale predictor is in a) the 25th to 27.5th percentile and b) the 97.5th to 100th percentile
  30. Precipitation: Gamma: Generalized Gamma:
  31. How does it perform?
  32. Ways to use the data: Classic Risk Assessment Use actual probability distributions to identify Risk as the product of probability and consequence Spatio-temporal Data Generate spatial data using a “weather generator” type noise pattern. 3. Historical Rescaling Rescale an existing time series from a present-day PDF to a future PDF.
  33. Present Climate Predicted Climate Impact threshold Probability Climate Space Actual Probability Distributions Risk Assessment: Identify threshold / response surface Define present day risk with present day probability distribution Compare future risk with future probability distribution Explore how adaptation strategies can impact risk Adaption Probability Climate Space
  34. Intense Precipitation Events
  35. Global Climate Change Thanks to D. Lorenz Downscaling: Focus global projections to a scale relevant to climate impacts. WICCI Climate Working Group / Focus on Energy
  36. Temporal Correlation between Stations Expect downscaled station data to be correlated with each other because a portion of the stations’ variability is controlled by the large-scale. However, if the spatial scale of the "random component" of the P (or T) variability is larger the separation between stations, then one expects the downscaled P (or T) to under-estimate the correlation between stations.
  37. Temporal Correlation between Stations To remedy this situation, the random numbers used to generate the precipitation at the different stations are not independent but instead are correlated with each other. Let R be a nstatXntime matrix of independent random numbers used to generate the P occurrence. The new R to generate the P occurrence is: W•R, where W is a nstat X nstat matrix of weights.
  38. Spatial and / or temporal data
  39. Annual Temperature Change
  40. Winter Temperature Change
  41. >90° Days, and <0° Nights
  42. Winter Precipitation Change
  43. Present Climate Probability MaxT (e.g.) Rescale a historical time series Why to use this approach: You’ve already done some analysis with historical weather data Impact is “event-like” Covariates are important (e.g. warm, wet, and windy on a given day) Policy decisions can be compared to historical decisions Probability MaxT (e.g.)
  44. Outline Introduction A history of the Wisconsin Initiative on Climate Change Impacts (or WICCI) WICCI Organizational Structure WICCI as a boundary organization Downscaling Methodology and Results Downscaling for Climate Impacts Assessment Conclusions
  45. Climate Change Impacts in Wisconsin The Wisconsin Initiative on Climate Change Impacts (WICCI) WICCI is set up as a boundary organization that includes climate sciences, impact sciences, and policy makers. The organizational structure engages stakeholders and climate / impact scientists alike, while preserving the identities of each group. Working groups allow focused and efficient efforts at understanding specific impacted systems The Operations and Outreach arm actively engages the public, and works to build support for the group in new and existing stakeholder communities.
  46. Climate Change Impacts in Wisconsin The Wisconsin Initiative on Climate Change Impacts (WICCI) Future directions: Base funding is needed as interest in the group snowballs. Assessment reports to be completed annually. Continued public outreach and engagement needed to build support at the state and local levels.
  47. Climate Change Impacts in Wisconsin Downscaling Climate over Wisconsin Downscaled projections of precipitation and maximum and minimum temperature for Wisconsin have been completed. The downscaling methodology predicts the (daily) probability distribution for a specific station based on large scale inputs. The advantages of the downscaling technique include (a) it works well (b) interpolation of distribution parameters avoids bias in extremes or discrete events (c) uncertainty is characterized across various dimensions (d) the resulting data are very flexible
  48. Resources: Wisconsin Initiative on Climate Change Impacts http://www.wicci.wisc.edu Governor’s Task Force on Global Warming http://dnr.wi.gov/environmentprotect/gtfgw/ UW Atmospheric and Oceanic Sciences http://www.aos.wisc.edu Nelson Institute for Environmental Studies http://www.nelson.wisc.edu Center for Climatic Research http://ccr.aos.wisc.edu Center for Sustainability and the Global Environment http://www.sage.wisc.edu Intergovernmental Panel on Climate Change http://www.ipcc.ch
More Related