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Regional Climate Change in the
Pacific Northwest
Eric Salathé
Climate Impacts Group
University of Washington
With: Cliff Mass, Patrick Zahn, Rick Steed
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
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
Salathé, Geophys Res Lett, 2006
Downscaling
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
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 135-45-15 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?
o Reason: interior heats up, pressure falls,
marine air pushes in from the ocean
• Might the summers be wetter?
o Why? More thunderstorms due to greater
surface heating.
MM5 Simulations
• Ran this configuration over several tenyear periods:
• 1990-2000-to see how well the system
is working
• 2020-2030, 2045-2055, 2090-2100
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 1990-2000 simulations
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
SeaTac Validation
January Temperature
Gridded Observations
MM5 - NCEP Reanalysis
MM5 - ECHAM5
July Temperature
Gridded Observations
MM5 - NCEP Reanalysis
MM5 - 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:
o ECHAM5 better than PCM
o NCEP 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-MM5 1990-2000 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 Cover
Temperature
Shift to Northerly Winds
Consistent trend over 21st Century
2020s
2050s
2090s
MM5 Compared to raw Climate model
2020s
2050s
2090s
Spring
Radiative Balance
Reduced
Incident Surface
Solar Radiation
Increased
Absorption of
Solar Radiation
Pressure gradient and Cloud
Trend over 21st Century
2020s
2050s
2090s
MM5 Compared to Raw Climate Model
2020s
2050s
2090s
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