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Uncertainty in Projections of Regional Hydrologic Impacts of Climate Change

PI: Edwin P. Maurer
Institution: Santa Clara University
The objective of this analysis is the quantification of the inter-model uncertainty for hydrologic impacts of climate change through 2100 on California. This builds on ongoing work examining the uncertainty, due to intermodel variability of GCM projections of precipitation and temperature, of projected hydrologic changes through 2100. This study uses monthly values of average temperature and precipitation from 10 GCMs (all of the models that participated in the most recent phase of CMIP, and that provided atmospheric data). The monthly GCM data are bias corrected using a quantile mapping technique that forces the monthly statistics of the GCM output for a climatological period to match the monthly statistics of the overlapping observations, while allowing evolution of the mean and variability of the GCM into the future. Spatial downscaling is performed by interpolating to 1/8 degree the ratio of each month’s precipitation (from the GCM) to the climatological observed value for each GCM-scale grid cell, and interpolating the shift in temperature between the GCM and observed values. Daily values of precipitation and temperature at 1/8 degree are generated using random resampling from the historical record, with rescaling of precipitation and shifting of temperature so the monthly average matches the bias-corrected and interpolated monthly GCM values. These daily sequences from each GCM are used to drive a hydrological model, which ultimately generates streamflow at strategic points throughout California. The differences in mean values of monthly streamflows under a control run and a perturbed (1%/year increasing CO2) run are compared to the inter-model variability to examine which changes are consistent across models, and which are less so. Since the California region is highly dependent on snow accumulation and melt, the changes in the timing of the annual hydrograph are also tested for robustness of timing shifts between different GCMs. A final experiment is performed where identical precipitation is used for all GCMs, to isolate the contribution of temperature and precipitation variability between models to the overall variability. The proposed analysis will duplicate this study using the results submitted by the participating modeling groups. This study will examine the inter-model variability of hydrological impacts projected through 2100 for the participating GCMs, and contrast the inter-model variability between the two scenarios A1fi and B1. In each case, the inter-model variability will be statistically compared to the projected hydrologic changes, to quantify the significance level of the change in monthly flows and the shift in annual hydrograph peak.
  • Brekke, L. D., E. P. Maurer, J. D. Anderson, M. D. Dettinger, E. S. Townsley, A. Harrison, and T. Pruitt,, 2009: Assessing reservoir operations risk under climate change. Water Resources Research, 45, W04411, doi:10.1029/2008WR006941. Abstract. Edit.
  • Maurer, E.P., 2007: Uncertainty in hydrologic impacts of climate change in the Sierra Nevada, California under two emissions scenarios. Climatic Change, 82, 309-325, doi:10.1007/s10584-006-9180-9. Abstract. Edit.
  • Maurer, E.P., I.T. Stewart, C. Bonfils, P.B. Duffy, and D. Cayan, 2007: Detection, attribution, and sensitivity of trends toward earlier streamflow in the Sierra Nevada. J. Geophysical Research, 112, doi:10.1029/2006JD008088.. Abstract. Edit.
  • Maurer, E.P., J.C. Adam, and A.W. Wood, 2009: Climate model based consensus on the hydrologic impacts of climate change to the Rio Lempa basin of Central America. Hydrology and Earth System Sciences, 13, 183-194. Abstract. Full Article. Edit.

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