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Progress in Downscaling Climate Change Scenarios in Idaho Brandon C. Moore
Outline • Datasets • Methodologies • Downscaling at the University of Idaho • Results • Summary
GCM Observed Datasets 8 km 8 km 4 km ~220 km Problems: (1) GCM too coarse for local assessment (2) GCM biases in climatology (spatially and temporally) (3) Regional climate variability (topography, water)
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 • 1K uncertainty in downscaling is comparable to the spread of the models around 2050. • Not as significant at 2100 1°K
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
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.