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Regional Climate Change in the Pacific Northwest

This study examines climate change in the Pacific Northwest, analyzing simulations for the IPCC 4th Assessment and evaluating trends for the 21st century. It explores temperature bias, precipitation patterns, and potential surprises, using both empirical and statistical downscaling methods. The study also evaluates the fidelity of the models and provides projections for future climate change impacts on air quality and hydrology in the region.

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Regional Climate Change in the Pacific Northwest

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

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

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

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

  5. 21st Century Change

  6. Shift in Pacific Storm Track J Yin, Geophys Res Lett, 2005 Salathé, Geophys Res Lett, 2006

  7. Downscaling

  8. Downscaling Methods Used in CIG Impacts studies 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

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

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

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

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

  13. 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

  14. Global Forcing: Surface Temperature

  15. 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

  16. 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

  17. SeaTac Validation

  18. January Temperature Gridded Observations MM5 - NCEP Reanalysis MM5 - ECHAM5

  19. July Temperature Gridded Observations MM5 - NCEP Reanalysis MM5 - ECHAM5

  20. 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: • ECHAM5 better than PCM • NCEP Reanalysis performs quite well

  21. 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.

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

  23. 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

  24. 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

  25. Winter Warming

  26. Surface Radiation Balance Increased Absorption ofSurface Solar Radiation

  27. Loss of Snow cover and Warming Snow Cover Temperature

  28. Shift to Northerly Winds

  29. Consistent trend over 21st Century 2020s 2050s 2090s

  30. MM5 Compared to raw Climate model 2020s 2050s 2090s

  31. Spring

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

  33. Pressure gradient and Cloud

  34. Trend over 21st Century 2020s 2050s 2090s

  35. MM5 Compared to Raw Climate Model 2020s 2050s 2090s

  36. Applications: Air Quality

  37. Applications: Hydrology

  38. 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

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