1. 21 st Century Climate Change Effects on Streamflow in the Puget Sound, WA. Lan Cuo, Eric P. Salathé Jr. and Dennis P. Lettenmaier Nov. 7, 2007 Hydro Group Seminar Seattle, WA

2. Background “Warming of the climate system is unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice, and rising global average sea level “ – IPCC AR4 Mountain snowpack is the key to understanding Pacific Northwest (PNW) water resources. In upland Puget Sound river basins, snow is the dominant form of water storage, storing water from the winter (when most precipitation falls) and releasing it in spring and early summer. Climatic variations and changes that influence spring snowpack, therefore, can have a significant impact on water resource availability in the Puget Sound. Objectives How does climate change affect streamflow in the Puget Sound Basin?

3. Methodology Study Area - Puget Sound Basin Bounded by the Cascade and Olympic Mountains Area: 30,000 sqr.km Maritime climate, annual precipitation 600 mm - 3000 mm, October – April Land cover: 82% vegetation 7% urban 11% other

4. The Emission Scenarios of the IPCC Special Report on Emission Scenarios (SRES) A1. The A1 storyline and scenario family describes a future world of very rapid economic growth, global population that peaks in mid-century and declines thereafter, and the rapid introduction of new and more efficient technologies. Major underlying themes are convergence among regions, capacity building and increased cultural and social interactions, with a substantial reduction in regional differences in per capita income. Based on technological emphasis, A1 has 3 groups: A1F1: fossil intensive A1T: non-fossil energy sources A1B: balance across all sources (where balanced is defined as not relying too heavily on one particular energy source, on the assumption that similar improvement rates apply to all energy supply and end use technologies). Methodology – terminology explanation

6. Methodology Generate 1/16 th degree climate forcing data using composite GCM results for 2010-2090. Test the reliability of GCM composite forcing by using composite GCM historical climate forcing in 1950 -1999. Use DHSVM to simulate streamflow for 2010- 2090 for A1B scenario. Compare the A1B scenario (2010-2090) streamflow with the simulated historical (1950- 1999) streamflow.

7. ModelsInstitutions BCCRUniv. of Bergen, Norway CCSM3NCAR, USA CGCM 3.1_t47CCCma, Canada CGCM3.1_t63CCCma, Canada CNRM_CM3CNRM, France CSIRO_MK3CSIRO, Australia ECHAM5MPI, Germany ECHO_GMax Plank Institute for Mathematics, Germany GFDL_CM2_1Geophysical Fluid Dynamic Laboratory, USA GISS_AOMNASA/GISS, (Goddard Institute for Space Studies) USA HADCMMet Office, UK HADGEM1Hadley Center Global Environment Model, v 1., UK INMCM3_0Institute Numerical Mathematics, Russia IPSL_CM4IPSL (Institute Pierre Simon Laplace, Paris, France MIROC_3.2CCSR/NIES/FRCGC, Japan PCM1NCAR, USA 16 Models used to Simulate IPCC Emission Scenario A1B

8. Data: Eastern Puget Sound Annual Tmin 2010 -2090 is the composite (average) of all 16 models.

9. Data: Western and Lowland Puget Sound Annual Tmin

10. Data: Eastern Puget Sound Annual Tmax

11. Data: Western and Lowland Puget Sound Annual Tmax

12. Data: Eastern Puget Sound Annual Precipitation

13. Data: Western and Lowland Puget Sound Annual Precipitation

14. Climate change in the Puget Sound Sub-basins, 2010-2090 average minus 1915-2002 average BasinsMean annual Tmin (°C) Mean annual Tmax (°C) Mean annual Precip. (mm) ∆Tmax ∆ Tmin ∆ Prcp Skagit-0.5102400 2.22.5196 Stillaguamish212.52400 2.12.5258 Snohomish1112400 2.12.4239 Cedar2.612.62100 22.4114 Green2.1122000 2.22.591 Puyallup1.511.61600 2.12.2248 Nisqually2.5131600 22.3222 Deschutes4.315.41200 1.82.193 Skokomish2.4133000 1.71.9443 Hammahamma0.210.82500 1.82333 Duckabush010.72400 1.92274 Dosewallips-1.69.42100 1.82323 Quilcene-0.810.71600 1.92.1375 Lowland_east3.814.21500 22.2190 Lowlnad_west3.413.81500 1.92244 Basin average1.5122020 22.2243

15. Results: Model Calibration

20. Results: the Reliability of GCM Composite Forcing Three data sets: 1.Observed streamflow 2.Simulation with observed forcing 3.Simulation with GCM composite 4.Period is 1950-1999

21. Results: Reliability of GCM Composite Forcing 1950 - 1999 GagesPeriodMean Daily Streamflow (cms) Mean Monthly Streamflow (cms) Obs.Sim. (comp) Sim. (hist) Obs.Sim. (comp) Sim (hist) 12115000 1950- 1999 7.287.327.237.307.327.24 12115500 1950- 1999 2.862.582.522.872.532.52 12117000 1956- 1999 2.772.572.542.782.582.54 However, simulations with GCM composite forcing have very poor Nash-Sutcliff Number and RMSE.

22. Results : Reliability of GCM Composite Forcing

23. Results: Streamflow change in SRES A1B

24. Preliminary Conclusions 1.Statistically downscaled GCM composite forcing data are suitable for studying mean hydrological properties such as daily, monthly and seasonal mean, but not for detailed time series study. 2.In a future, warmer temperatures will result in more winter precipitation falling as rain rather than snow throughout much of the Puget Sound. This change will result in: less winter snow accumulation, higher fall, winter, early spring streamflows, earlier spring snowmelt, earlier peak spring streamflow, and lower summer streamflows Acknowledgement: This work is supported by the University of Washington CIG and PRISM.