Progress in Downscaling Climate Change Scenarios in Idaho

Brandon C. Moore

Outline

• Datasets

• Methodologies

• Downscaling at the University of Idaho

• Results

• Summary

Datasets• GCM • Observed

8 km

~220 km

8 km

Problems: (1) GCM too coarse for local assessment (2) GCM biases in climatology (spatially and temporally)

(3) Regional climate variability (topography, water)

4 km

Datasets

• Which datasets should we use?– Climatology– Historic trends– Extremes– Multi-model

• Ensemble• Weighted-average

Methodology

• Delta Method– Apply simple scaling factor; easy to use– Assumes fixed step change; higher stat. moments

unchanged

• Bias Correction Spatial Downscaling– Wood et al, 2004; Maurer, 2007

• Constructed Analog– Hidalgo et al, 2008

Bias Correction Spatial Downscaling (BCSD)

• Aggregate gridded OBS to GCM resolution** (= 1K)• Remove trend• Generate CDF of observed and GCM data**

– Q-Q mapping approach– Z-score approach (mean and variability)

• Add trend back in• Resample/interpolate** to finer resolution• Apply spatial factor to account for subgrid

topography

Relative to Climate Scenarios

1°K

• 1K uncertainty in downscaling is comparable to the spread of the models around 2050.

• Not as significant at 2100

Construct Analog

• Aggregate observed to GCM resolution• Apply a bias correction on the GCM• Determine 30 “best” synoptic patterns based on

pattern RMSE– Must be chosen within 45 day window of target date

• Determine regression coefficients at coarse resolution

• Apply regression coefficients to fine-scale patterns

Downscaling at UI

• Construct Analog– Downscaled daily– Tmax, Tmin, Prcp, 10m winds, RHmax, RHmin– Late 20th century (1971-2000)– Late 21st century (2081-2100); A1B– Spatial resolution: 8km– 13 Global Circulation Models– Additional scenarios/time slices to come

Downscaling at UI

• Modified BCSD– Downscaled monthly; moving toward daily– 20th and 21st century– Tmax, Tmin, Prcp– Spatial resolution: 4km– 3 models, 2 scenarios– Additional models and scenarios to be

completed

Change in Cool Season (Oct-May) PrecipitationPercent Change Late 21st Century SRES-A1B vs. Late 20th Century 20C3M

MME

Change in Snowfall (SWE%)Percent Change Late 21st Century SRES-A1B vs. Late 20th Century 20C3M

MME

Projections of annual temperature trends for the state of Idaho

Summary

• Multiple downscaled climate scenarios for ensemble runs– 2 methods– Multiple models– Multiple resolutions

• Future work– Validation– Methods publication– Prepare for AR5

• Meeting in Portland next week

References

• Hidalgo, H., Dettinger, M., and Cayan, D., 2008. Downscaling with constructed analogues—Daily precipitation and temperature fields over the United States: California Energy Commision PIER Final Project Report CEC-500-2007-123, 48 p.

• Maurer, E. P., 2007. Uncertainty in hydrologic impacts of climate change in the Sierra Nevada, California under two emissions scenarios, Climatic Change, Vol. 82, No. 3-4, 309-325.

• Wood, A. W., L. R. Leung, V. Sridhar, and D. P. Lettenmaier, 2004. Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climatic Change, 62, 189-216.