1. Regional Climate Change in the Pacific Northwest Eric Salathé Climate Impacts Group University of Washington With: Cliff Mass, Patrick Zahn, Rick Steed

2. Simulations for the IPCC 4th Assessement Averages over the Pacific Northwest 20th Century Evaluation Trends for the 21st Century Climate Change in the Pacific Northwest

3. 20th Century Validation 20th Century Temperature Trend Temperature Bias Precipitation Seasonal Cycle

4. Range of Projected Climate Change for the Pacific Northwest from Latest IPCC Climate Simulations

7. 21st Century Change

8. Shift in Pacific Storm Track J Yin, Geophys Res Lett, 2005 Salath é, Geophys Res Lett, 2006

9. Downscaling

10. Empirical Downscaling Assumes climate model captures temperature and precipitation trends Quick: Can do many scenarios Shares uncertainties with global models Regional Climate Model Based on MM5 regional weather model Represents regional weather processes May produce local trends not depicted by global models Additional modeling layer adds bias and uncertainty Downscaling Methods Used in CIG Impacts studies

11. Statistical Downscaling Large-scale temperature as predictor for temperature Large-scale precipitation and sea-level pressure as predictors for precipitation

12. Climate Change: IPCC SRES A2 Winter Average over Small River Basin

13. Mesoscale Climate Model  Based on MM5 Weather Model  Nested grids 135-45-15 km  Nudging on outermost grid by forcing global model  Advanced land-surface model (NOAH) with interactive deep soil temperature

14. Example of Potential Surprises Might western Washington be colder during the summer under global warming? oReason: interior heats up, pressure falls, marine air pushes in from the ocean Might the summers be wetter? oWhy? More thunderstorms due to greater surface heating.

15. MM5 Simulations Ran this configuration over several ten- year periods: 1990-2000-to see how well the system is working 2020-2030, 2045-2055, 2090-2100

16. Global Forcing: Surface Temperature

17. First things first To make this project a reality we needed to conquer some significant technical hurtles. Example: diagnosing and predicting future deep soil temperatures Example: requirements for acquiring GCM output every 6 h and storing massive amounts of output. Evaluating the 1990-2000 simulations

18. Evaluating Model Fidelity We have carefully evaluated how well the GCM and the MM5 duplicated the 1990-2000 period. Multiple Runs: NCAR-NCEP Reanalysis NCAR-DOE Parallel Climate Model (PCM) Max Planck ECHAM5 Primary Validation against station observations -- Not against gridded product

19. SeaTac Validation

20. January Temperature Gridded ObservationsMM5 - NCEP ReanalysisMM5 - ECHAM5

21. July Temperature Gridded ObservationsMM5 - NCEP ReanalysisMM5 - ECHAM5

22. Winter Cold Bias Cold episodes occurred 1-2 times per winter with temperature getting unrealistically cold (below 10F) in Puget Sound: Also a general cold bias to minima, especially in Summer Performance varies with global forcing model: oECHAM5 better than PCM oNCEP Reanalysis performs quite well

23. Why Cold Outbreaks? Widespread surges of arctic air originate in Global Model, likely owing to poorly-resolved terrain (Cascades and Rockies). Extreme cold air inherited by MM5. Results from previous experiments with lower-resolution (T42) GCM indicate that higher resolution reduces frequency and severity of unrealistic cold events.

24. Issues in downscaling Example of cold bias in PCM control simulation Due to poor resolution, model generates intermittent spuriously cold events over the Western US Surf Temp (K)

25. Summer Cold Bias Bias only in night time (minimum) temperature Appears in climate model run and reanalysis run Probably due to excess radiative loss at night Cloud and radiation parameterizations

26. Evaluation of Future Runs  Because there are some biases in the GCM runs, results for future decades (2020s, 2040s, and 2090s) will be evaluated against the ECHAM5-MM5 1990-2000 baseline  Differences between the MM5 anomaly and the raw global model anomaly will show information introduced by MM5

27. Winter Warming

28. Surface Radiation Balance Increased Absorption of Surface Solar Radiation

29. Loss of Snow cover and Warming Snow CoverTemperature

30. Shift to Northerly Winds

31. Consistent trend over 21st Century 2020s2050s2090s

32. MM5 Compared to raw Climate model 2020s2050s2090s

33. Spring

34. Radiative Balance Reduced Incident Surface Solar Radiation Increased Absorption of Solar Radiation

35. Pressure gradient and Cloud

36. Trend over 21st Century 2020s2050s2090s

37. 2020s2050s2090s MM5 Compared to Raw Climate Model

38. Applications: Air Quality

39. Applications: Hydrology

40. Summary  Projected Pacific Northwest Climate Change  warming: 1/4 to 1 ºF/decade  Probably more warming in Summer than Winter  Precipitation changes uncertain – Possibly wetter winters and drier summers  Challenges  Deficiencies in Global model propagate to regional model  Biases from regional model  Mesoscale model simulates different climate signal from global model  Loss of snow amplifies warming in Winter and Spring  Increased cloud cover in Spring -- reduces effect of snow loss