Eric SalathéJISAO Climate Impacts Group

University of Washington

Rick Steed UWYongxin Zhang CIG, NCARCliff Mass UW

Regional Climate Modeling and Projected Changes in Extreme Precipitation

Downscaling and Regional Climate Modeling

12-50 km or~7-32 mi

Statistical Downscaling • Maps the climate change signal from a global model onto the observed patterns• Computationally efficient• Can tune to observed climate• Preserves uncertainty in Global Climate Models• Cannot represent fine-scale patterns of climate change

Regional Climate Models (“Dynamic Downscaling”) • Extend the physical modeling of the climate system to finer spatial scales• Computationally demanding• Cannot correct bias in global model• Adds to uncertainty from Global Climate Models

Global ClimateModel

6-hourlyMonthly

100-200 km

6 km or~3.7 mi

150-km GCM

High resolution is needed for regional studies

Washington

OregonIdaho

Cas

cade

Ran

ge

Rocky Mountains

Snake Plain

Olympics

Global models typically have 100-200 km (62-124 mi.) resolution

•Cannot distinguish Eastern WA from Western WA

•No Cascades

•No land cover differences

High resolution is needed for regional studies (cont’d)

Washington

OregonIdaho

Cas

cade

Ran

ge

Rocky Mountains

Snake Plain

Olympics

Regional models typically have 12-50 km (7-32 mi) resolution

• 12 km WRF at UW/CIG

• Can represent major topographic features

• Can simulate small extreme weather systems

• Represent land surface effects at local scales

12-km WRF

Why do we want to simulate the regional climate?

Process studies Topographic effects on temperature and

precipitation Extreme weather Attribution of observed climate change Land-atmosphere interactions

Climate Impacts Applications Streamflow and flood statistics Water supply Ecosystems Human health Air Quality

Regional Climate Modeling at CIG

WRF Model ECHAM5 A1B forcing 36-km (~32 mi) grid spacing CCSM3 A2 forcing 20-km (~12 mi) grid spacing

Emissions Scenarios

IPCC Emissions Scenarios for Climate Projections

Statistical Downscaling CCSM3Fall difference between 1990s and 2040s

Low spatial detail for climate change signal

°C %

Temperature Precipitation (%change)

WRF “Dynamic Downscaling” CCSM3

Temperature Precipitation (%change)

Fall difference between 1990s and 2040s

High spatial detail for climate change signal

%

Extreme Precipitation: Global Models

Change from 1980–1999 to 2080–2099 in the intensity of precipitation

largest increase areas already experiencing heavy precipitation

Change in mm

Extreme Precipitation: Regional Models

Change from 1970-2000 to 2030-2060 in the intensity of precipitation

largest increase on windward slopes of Cascades, Columbia basinsmall increase or decrease along Cascade crest

Change in mm

Historic Trends in Extreme Precipitation (1970-2000)

Precip Intensity

ECHAM5-WRF Northeast Washington: Pend Oreille at Boundary Dam

Trends in intensity

Not the light events

But the big events

ECHAM5-WRF North Cascades: Skagit at Mt Vernon

ECHAM5-WRF North Cascades:Skagit at Diablo Dam

Trends are lostin the variability

Summary of Precipitation Intensity

Station 1970-1999Standard Deviation

Change 2020s

Change 2040s

Skagit Diablo Dam 14.79 1.51 -0.34 0.41

Skagit Mt Vernon 11.47 0.96 0.31 1.11

Ross Newhalem 10.06 0.90 -0.28 0.22

Baker Concrete 17.14 1.61 -0.18 0.97

Sauk 17.05 1.73 -0.50 0.67

Box Canyon 7.43 0.61 0.11 0.43

Boundary 7.50 0.68 0.15 0.47

Sea Tac 5.97 0.65 0.00 0.08

Summary of Precipitation Intensity

• Interannual variability is very large and dominates in the near future

• Increased precipitation intensity emerges at a few locations by mid century