1. Climate Forecasts and Western Water Supply Outlooks Thomas Pagano and David Garen WCC-NRCS-USDA tpagano@wcc.nrcs.usda.gov phone 503 414 3010

2. Water Supply Forecasts in the West The operational history of using climate forecasts Benefits to water supply forecasts Opportunities and barriers Long-term cycles and climate change

3. Location

4. Time Period Historical Average

5. Location Time Period “Most Probable” Water Volume Historical Average Error Bounds

6. Core users rely on site-specific forecast tables to operate reservoirs or plan irrigation Westwide and regional maps of “most probable” forecast for general consumption

7. Autumn Precipitation Current Snowpack El Nino Soil Moisture...Seasonal Runoff Volumes… with Error Bounds Regression Equations and Coordination Water Supply Forecast Current Practices

8. The history of linking climate and water supply forecasts

9. in 6 words or less…

10. The history of linking climate and water supply forecasts in 6 words or less… “If only we knew future precipitation”

11. Ancient History

12. Dr James Church Father of Snow Surveys Ancient History 1935: The largest source of water supply forecast (WSF) error is future precipitation Amount of WSF error for Lake Powell Inflow due to future precipitation (Schaake, 1985): Jan 1st: 80% Apr 1st: 50%

13. The Dawn of Climate Forecasts Monthly Climate Outlook 1953: First public 30-day climate forecast 1955: Use of climate forecasts in Columbia River WSF - Potential benefit is great - Actual skill is too low - Hydrologist exposed to increased chance of “bust” 1964 follow up - Forecast skill improving but still not good enough - Problem is now “downscaling”

14. 1974 June-Aug Temp Outlook Namias The 1970’s and California ~1974: CA Dept Water Resources hires Namias through “Project Hydrospect” 1976: Marron (NRCS) uses El Nino index in forecasting Lake Tahoe area streamflows Marron

15. The 1982-83 El Nino and the Colorado River “El Nino of the Century” Full reservoirs Cold wet spring followed by rapid warming Lake Powell Apr-July inflow Apr 1st forecast: 109% of average Observed runoff: 210% of average Near failure of Glen Canyon Dam Imprint on institutional memory Plywood Flashboards on Glen Canyon Dam

16. Studies of El Nino and Western US Streamflow CayanRedmond Koch El Nino/Dry El Nino/Wet 1989-1991: Recognizing continental patterns in climate signals and the links to streamflow

17. Perkins Colorado Basin Garen Columbia Basin Hartman left NRCS in 1990 to NWS Colorado Basin River Forecast Center 1988-1990: Routine use of climate indices in operational water supply forecasting starts at the Natural Resources Conservation Service Widespread operational adoption

18. The El Nino of the Century #2: 1997-98 Fear of a repeat of 1982-83 floods Users expected under-forecast bias and made extra releases at Powell In the end: “Non-event” at Powell Several million $ saved in Arizona V. President Gore hauling sandbags

19. 2001 and the Pacific Northwest 2000-01 La Nina + Cold PDO = Strongest possible climate indication of a WET Pacific Northwest Inaction by Water Supply Forecasters

20. 2001 and the Pacific Northwest 2000-01 La Nina + Cold PDO = Strongest possible climate indication of a WET Pacific Northwest Inaction by Water Supply Forecasters Driest winter on record observed What went wrong?

21. Operational Benefits

24. Issues and Barriers Hydrologists are from Mars Watershed Scale Semi-Deterministic High Skill Continental to Global Scale Probabilistic Low Skill Climatologists are from Venus

25. Issues of Scale: 2 Views of the Southwest The Climatologist

26. 100 miles Issues of Scale: 2 Views of the Southwest Upper Rio Grande Mar 1 2003 Snowpack The HydrologistThe Climatologist

27. Streamflow (k ac-ft) La NinaEl Nino SON Nino 3.4 Links with Apr-Sept Stehekin R at Stehekin, WA Streamflow CLIMATE R = 0.45

28. Streamflow (k ac-ft) Apr 1 Rainy Pass Snow Water (inches) La NinaEl Nino SON Nino 3.4 Links with Apr-Sept Stehekin R at Stehekin, WA Streamflow CLIMATE SNOW R = 0.91 R = 0.45

29. Semi-Deterministic Inherently Probabilistic Very small shifts: the equivalent of changing 2-3 cards in a deck of 52

30. Climate and WSF issues WSF has used El Nino for decades. Is that sufficient? Climate forecasts make Water Supply Forecasts possible as early as Sept. Skill in pre-season forecasts would be low but not zero. What would people expect from these forecasts? Do these forecasts require a fundamentally different format emphasizing uncertainty? How to cultivate skepticism while combating pessimism?

31. Strategies for resource managers Changing reservoir releases Prepositioning emergency resources Shifting focus of training Raising public awareness Have a no-regrets strategy… Is inaction a no-regrets strategy? When in drought, prepare for rain..

32. And then there’s long-term cycles… “If predictions hold true, California and Arizona could be high and dry, while Washington and Oregon could be drenched for the next 20 to 30 years.”

33. Sept-Nov PDO Index 1930-2001 Arizona Statewide Fall-Spring Precipitation 19301940195019601970198019902000

34. Sept-Nov PDO Index 1930-2001 Arizona Statewide Fall-Spring Precipitation 19301940195019601970198019902000

36. “Cycle” Doesn’t mean there aren’t serious implications, however!

37. “Cycle” “Quasi-cyclic aperiodic decadal variability” Doesn’t mean there aren’t serious implications, however!

38. Varieties of Year-to-Year Seasonal Streamflow Changes Less Variable More Variable years

39. Varieties of Year-to-Year Seasonal Streamflow Changes Less Variable Less Persistent More Persistent More Variable years

40. Of 137 stations around the western US Apr-Sept flow volumes: becoming increasingly variable year-to-year persistence also high Variance Persistence Most like: Years Start Year 20-year moving window (1980 = 1980-1999)

41. Of 137 stations around the western US Apr-Sept flow volumes: becoming increasingly variable year-to-year persistence also high Variance Persistence Most like: Start Year 20-year moving window (1980 = 1980-1999)

42. The magic question: Variance or Continue trend Revert?

43. Conclusions Seasonal climate forecasts are available and credible Useful decisions possible if managers mindful of large forecast uncertainty Nature always changing Who knows what will happen next?