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Maurer, E.P.1, I.T. Stewart1, C. Bonfils2, P.D. Duffy3 and D. Cayan4 1 Santa Clara University, 2U.C. Merced, 3Lawrence Livermore National Lab, 4Scripps Institution of Oceanography, UCSD and WRD, USGS ( Abstract We examine the seasonal timing of flows on four major rivers in California, and how these are affected by climate variability and change. We measure seasonal timing of soil runoff and river flows by the “center timing” (CT), defined as the day when half the annual flow has passed a given measurement point. We use a physically-based surface hydrologic model driven by meteorological input from a global climate model to quantify the year-to-year variability in CT resulting from natural internal climate variability (the internal oscillations of the climate system). We find that estimated 50year trends in CT due to natural internal climate variability often exceed the trends in CT observed over the last 50 years. Thus, although observed trends in CT may be statistically significant, they are not necessarily a result of external influences on climate such as increased greenhouse gases. To estimate when CT changes might be expected to exceed levels possible from natural climate variability, we calculate the sensitivity of CT to increases in temperature ranging from 1 to 5 degrees. We find that at elevations between 2000 – 2800 m are most sensitive to temperature increases in this range, and can experience changes in CT exceeding 45 days. As temperatures rise, so do the elevations that are most sensitive to further increases in temperature. Based on these sensitivities, we estimate that changes in CT will exceed those possible from natural climate variability by the midor late 21st century, depending on rates of future greenhouse gas emissions. 1 Parallel Climate Model (PCM): Before using Control Run (constant 1870 atmosphere): How does it simulate 20th Century in California? VIC modeling results – shift 1961-1990 temperatures by fixed values, calculate CT •VIC Model is driven with GCM-simulated (biascorrected, downscaled) P, T and reproduces Q for historic period VIC Model Features: •Developed over 15 years •Energy and water budget closure at each time step •Multiple vegetation classes in each cell •Sub-grid elevation band definition (for snow) •Subgrid infiltration/runoff variability 3 binned results Streamflow Timing at Key Locations – PCM control run results CT shift for individual VIC grid cells under specified temperature shifts relative to 19611990. Stewart et al. (2005) points (against basin average elevation) in the SSJ basin are added as diamonds, and for these diamonds red indicates significance at the 90% level. Sacramento-San Joaquin Basin: Key points (inflows to major reservoirs): Feather R at Oroville American R at Folsom Dam Tuolumne at New Don Pedro Res Kings R. at Pine Flat Dam Drainage Area, km2 9350 4850 3970 4000 Mean Basin Elevation, m 1553 1335 1755 2196 Max Basin Elevation, m 2655 3009 3802 4086 Site Name Preliminary PCM Control Run Analysis Where will streamflow timing change with different T? 4 2 Obligatory VIC Graphic 1950-1999 streamflow timing trends at these 4 points (based on VIC modeling): 1950-1976 period for one grid cell Site Name 2 m Surface Air Temperature Timing Shift, days (- indicates earlier) PCM “20c3m" “run1" IPCC AR4 experiment Feather R at Oroville American R at Folsom Dam Tuolumne at New Don Pedro Res Kings R. at Pine Flat Dam +1 -9 +4 +2 No significant trends. Because these sites include rain dominated area their timing is less sensitive to historic inter-annual temperature variability than other areas. OBS is gridded monthly observations Sept-Jan: good interannual variability small biases •Impacts through +2°C focused North of Lake Tahoe •Maximum impact in 2000-2800 m range •For up to 2°C rise peak impact is in 2000-2400m range •Above that, peak impact shifts to 2400-2800m range What is the variability in 50-year streamflow timing trends in California? 629 years of control PCM simulated CT dates for Feather R. Feb-Aug: PCM underestimates interannual variability low bias in temperature simulation 5 Incremental change in CT for an incremental change in T. Each bar charts the increase in CT beyond that already experienced with the next lowest temperature shift. Whiskers and bar representing 10, 25, 75 and 90 percentile elevations within each basin. When will these Ts and CTs happen? Projected Changes in Temperature Relative to 1961-1990 (from Hayhoe et al. and Cayan et al.) Biases are different at different points, with PCM overestimating interannual variability at other locations. Overall for all California variability is close to observed. This spatially variable GCM bias means raw output is not useful for hydrology: bias correction and downscaling is needed P (scale) and T (shift) factor time series At GCM scale, CDFs of Precipitation and Temperature for each month are developed for Observations and GCM for climatological developed to 1/8° grid cell centers period. Quantiles for GCM are mapped onto CDF for Observations Factors interpolated (about 150 km2 per grid cell) Applied to entire 629-year control run Mean and variance of observed data are reproduced for climatological period Temperature trends into future in GCM output are preserved Relative changes in mean and variance in future period GCM output are preserved, mapped onto observed variance •Q10 is the value not exceeded in 10% of the trend segments. •Q10 varies from 17-19 days for these sites. Downscaling GCM Output Fig: A. Wood •Cumulative distribution functions for CT trend (days/50 years) for PCM control run. 125% 118% 116% 120% 116% 112% 117% 109% 107% 108% 105% 102% •Based on this control run a 50-year trend in CT would need to shift 17-19 days earlier to achieve statistical confidence level of 90% But haven’t past studies shown that streamflow timing is changing? Yes. Past study by Stewart et al. found a CT shift of 17.7 and 20.5 days earlier over the 1948 to 2002 period for two of their three sites that obtained 90% confidence within the Sacramento-San Joaquin basin. Those were smaller basins in snow-dominated areas, not inflows to managed water system. Can we identify hypsometric characteristics of basins that will be most vulnerable to streamflow timing shifts under warming temperatures? T under Higher Emissions (A1fi), °C T under Mid-High Emissions (A2), °C End of 21st Century Early 21st Century 3.8-5.8 0.5-1.5 Mid 21st Century End of 21st Century 1.3-2.3 T under Low Emissions (B1), °C Early 21st Century 2.6-4.5 (3.7) 0.5-1.4 Mid 21st Century End of 21st Century 0.8-2.2 1.5-2.7 (2.3) Ensemble mean of 11 GCMs Projected Changes in Timing Relative to 1961-1990 (from Maurer, 2006) Basin CT under Mid-High Emissions (A2), days Early 21st Century Mid 21st Century End of 21st Century CT under Low Emissions (B1), days Early 21st Century Mid 21st Century End of 21st Century Feather R. -14 -18 -23 -10 -11 -17 American R. -19 -23 -31 -17 -20 -26 Tuolumne R. -9 -20 -33 -10 -14 -23 Kings R. -9 -21 -36 -8 -16 -24 • CTs for these 2 lower elevation basins will statistically significant levels my early-to-mid 21st century under lower emissions, or mid-to-late 21st century under higher emissions. • CTs for higher elevation basins will be delayed, but could eventually exhibit greater changes than lower elevation basins under higher emissions. • A lower emissions future avoids much of the impact on timing for areas above 2400 m Cayan, D., E. Maurer, M. Dettinger, M. Tyree, K. Hayhoe, C. Bonfils, P. Duffy, and B. Santer, 2006, Climate scenarios for California, California Climate Change Center publication no. CEC-500-2005-203-SF Hayhoe, K., Cayan, D., Field, C., Frumhoff, P., Maurer, E., Miller, N., Moser, S., Schneider, S., Cahill, K., Cleland, E., Dale, L., Drapek, R., Hanemann, R.M., Kalkstein, L., Lenihan, J., Lunch, C., Neilson, R., Sheridan, S., and Verville, J.: 2004, ‘Emissions pathways, climate change, and impacts on California’, Proceedings of the National Academy of Sciences (PNAS) 101 (34), 12422–12427. Maurer, E.P., 2006, Uncertainty in hydrologic impacts of climate change in the Sierra Nevada, California under two emissions scenarios, Climatic Change (in press) Stewart, I. T., D. R. Cayan, and M. D. Dettinger, 2004, Changes in snowmelt runoff timing in western North America under a 'business as usual' climate change scenario, Climatic Change, 62, 217-232