Regional Climate Change in the Pacific Northwest Eric Salathé Climate Impacts Group University of Washington With: Cliff Mass, Patrick Zahn, Rick Steed
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
20th Century Validation 20th Century Temperature Trend Temperature Bias Precipitation Seasonal Cycle
Range of Projected Climate Change for the Pacific Northwest from Latest IPCC Climate Simulations
21st Century Change
Shift in Pacific Storm Track J Yin, Geophys Res Lett, 2005 Salath é, Geophys Res Lett, 2006
Downscaling
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
Statistical Downscaling Large-scale temperature as predictor for temperature Large-scale precipitation and sea-level pressure as predictors for precipitation
Climate Change: IPCC SRES A2 Winter Average over Small River Basin
Mesoscale Climate Model Based on MM5 Weather Model Nested grids km Nudging on outermost grid by forcing global model Advanced land-surface model (NOAH) with interactive deep soil temperature
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.
MM5 Simulations Ran this configuration over several ten- year periods: to see how well the system is working , ,
Global Forcing: Surface Temperature
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 simulations
Evaluating Model Fidelity We have carefully evaluated how well the GCM and the MM5 duplicated the period. Multiple Runs: NCAR-NCEP Reanalysis NCAR-DOE Parallel Climate Model (PCM) Max Planck ECHAM5 Primary Validation against station observations -- Not against gridded product
SeaTac Validation
January Temperature Gridded ObservationsMM5 - NCEP ReanalysisMM5 - ECHAM5
July Temperature Gridded ObservationsMM5 - NCEP ReanalysisMM5 - ECHAM5
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
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.
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)
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
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-MM baseline Differences between the MM5 anomaly and the raw global model anomaly will show information introduced by MM5
Winter Warming
Surface Radiation Balance Increased Absorption of Surface Solar Radiation
Loss of Snow cover and Warming Snow CoverTemperature
Shift to Northerly Winds
Consistent trend over 21st Century 2020s2050s2090s
MM5 Compared to raw Climate model 2020s2050s2090s
Spring
Radiative Balance Reduced Incident Surface Solar Radiation Increased Absorption of Solar Radiation
Pressure gradient and Cloud
Trend over 21st Century 2020s2050s2090s
2020s2050s2090s MM5 Compared to Raw Climate Model
Applications: Air Quality
Applications: Hydrology
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