1. Designing for Global Warming Orson P. Smith, PE, Ph.D. School of Engineering

2. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 2 Evidence of global warming continues to accumulate Combined global annual land-surface air and sea surface temperature anomalies

3. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 3 Strongest signals are in the North

4. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 4 Projections are Scattered Source: Intergovernmental Panel on Climate Change, 2001

5. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 5 Global Circulation Model (GCM) Predictions Vary Average, minimum, and maximum air temperatures predicted from 27 GCM’s for Fairbanks, Alaska (with permission from Vinson and Bae, 2002, “Probabilistic Analysis of Thaw Penetration in Fairbanks, Alaska,” ASCE Cold Regions Engineering Conference, Anchorage)

6. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 6 Figure from EPA website http://www.epa.gov/globalwarming/ Other Trends Complicate Predictions

7. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 7 Climate change impacts involve spatial variables Permafrost changes Thaw subsidence, onshore and offshore increased flux of sediments into steams and the coastal ocean

8. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 8 Alaska’s Permafrost Foundations are at Risk

9. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 9 Proven responses to most warming problems exist Accurate knowledge of change saves money Synthesize existing data Monitor changes statewide Improve data transfer Refine predictions Revise codes, manuals, and design software Engineers' Views from Prior Meetings

10. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 10 Strategies for Climate Change Design Criteria Development Designers may address climate change by: Subjective: factor of safety Deterministic: apply a trend Probabilistic: Monte Carlo simulations Hybrid: e.g., apply “fuzzy set” methods

11. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 11 Monte Carlo Simulations Random sampling, interpreted by assumed continuous distributions of independent variables Many repetitions results in a derived distribution of dependent variable

12. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 12 Apply a Trend Designers focus only on extremes Trends apply to entire data set Accelerated change is not resolved by conventional criteria development methods –Additional information is necessary More sophisticated historical data analysis Predictive simulations (GCM results, Monte Carlo, …)

13. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 13 Accelerated Trend Storm-related extreme conditions may have accelerated trends from more frequent and intense storms due to global warming

14. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 14 Projections from history Consider the first half of the previous time series as a hypothetical historical record Threshold of extremes

15. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 15 Conventional Extremal Analysis Return period: Cumulative Probability: Extrapolated 50- & 100-year return period values 8.69492 8.43899

16. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 16 Anticipate a Linear Trend

17. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 17 Anticipate a Linear Trend Remove the trend and identify extremes Fit extremal distribution

18. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 18 Trend-adjusted Extrapolations

19. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 19 Anticipate an Accelerating Exponential Trend

20. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 20 Exponential Trend-adjusted Extreme Values 100-year return period value 50-year return period value

21. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 21 Summary of Proposed Analysis 1.Derive trend from complete data set 2.Remove trend from data set 3.Apply conventional statistics of extremes 4.Adjust extrapolated extremes with trend

22. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 22 Cycle Superimposed on an Exponential Trend

23. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 23 Options for Addressing Climate Cycles Remove cycles with low pass filter (10 - 20 year period) Ignore cycles Decades of good data are required to define a regional climate cycle

24. Orson Smith - UAA School of Engineering 10 February 2004 Alaska Forum on the Environment 24 Questions 1.What are the fundamental trends, cycles, and distributions of engineering parameters? 2.How do we best anticipate a trend in forecasting secondary variables (floods, storm surge, erosion, thaw depth, etc.)? 3.How do we best anticipate a trend for design criteria development (extremal analysis)? 4.How do we best anticipate a cycle for design criteria development?