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Toward an Armistice in the Cascade Snowball Fight:

Toward an Armistice in the Cascade Snowball Fight: A New Look at Trends in Cascade Mountain Snowpack Mark T. Stoelinga University of Washington. Collaborators: Mark Albright and Cliff Mass Additional invaluable help: Mike Wallace, Joe Casola, Nate Mantua.

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Toward an Armistice in the Cascade Snowball Fight:

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  1. Toward an Armistice in the Cascade Snowball Fight: A New Look at Trends in Cascade Mountain Snowpack Mark T. Stoelinga University of Washington UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  2. Collaborators: Mark Albright and Cliff Mass Additional invaluable help: Mike Wallace, Joe Casola, Nate Mantua UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  3. The Snowpack Wars (a.k.a. the Snowball Fight) • How did it develop? • Steady drumbeat in the peer-reviewed literature (with significant contributions from UW Climate Impacts Group) showing evidence for substantial loss (>50% in some locations) of April 1 snowpack in the Pacific Northwest during approximately the second half of the 20th century • Corroborating changes in spring/summer streamflow timing (UW CIG, Scripps, etc). • Strong suggestion that anthropogenic global warming is a key contributing cause. UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  4. “Snowpack levels in Washington, Oregon and California … are a fraction of what they were in the 1940s, and some snowpacks have vanished entirely.” - Time Magazine, March 2006 UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  5. The opening salvo from Mark Albright on February 10, 2007: • Hi Everyone, • Mayor Greg Nickels has written a guest column in the 7 Feb 2007 Seattle • Times. In this guest column Nickels states "The average snowpack in the Cascades • has declined 50 percent since 1950". • I believe a more accurate statement would be along the lines of: • The average snowpack in the Cascades has increased over the past 30 years in spite of the steady upward trend in global temperature, or • Long term data indicates no significant trend in Cascade Mtns snowpack over the past 90 years, or • The snowpack (1997-2007) at Mt. Rainier Paradise has increased 11% since the 1940s. • The question is, can we come up with a short concise consensus statement • on the current state of Cascade Mtns snowpack that we can present to the • Mayor's office?  Any comments? • -Mark Albright • Associate WA State Climatologist / Research Meteorologist • U of Washington UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  6. The battle was joined! 10 days of heated discussion ensued, including at least 65 email contributions from Battisti, Redmond, Hamlet, Mote, Mass, Stoelinga, Albright, Mantua, Rangno, and Wallace UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  7. Was this a “manufactroversy”? - Leah Ceccarelli, UW Communications UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  8. Was this a “manufactroversy”? - Leah Ceccarelli, UW Communications Or was it, in fact, a “legitroversy”? - Mark Stoelinga, UW Atmospheric Sciences legitroversy: A legitimate controversy that is thought by some to be a manufactroversy UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  9. A cease-fire was called, with a meeting to discuss the matter like objective scientists (the “Tuesday Summit”), leading to… UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  10. The “Hartmann Document” UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  11. The “Hartmann Document”: “While some (Cascade snow observing) stations show a 50% downward trend in April 1 snow water equivalent between 1950 and the present, we believe the overall observed trend for the Cascade Mountains of Washington and Oregon is smaller.” “…observations … from 1945 until the present show a snow water equivalent decrease of about 30%. If an earlier starting date is chosen, the trend is smaller but the number of stations available before 1945 is relatively small and their average altitude is high. If a shorter record is chosen, starting in about 1975 for example, there is a small increase in snow water equivalent. However, the statistical significance of 30-year records is smaller.” UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  12. But all was not well… The very next day, an email went out with subject line: “Consensus?” Reply subject, minutes later: “Consensus? No, clearly not.” And later that day: “I am shocked and dismayed by (redacted)’s email breaking the agreement.” (i.e., the “gag order”…yes, there was a gag order). UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  13. Two key statements in the lingering dispute: “Interdecadal variability (mostly PDO) is dominant and makes it impossible to determine any longer-term small trend due to global warming or any other source.” “The PDO can explain some but not the majority of the downward trend in April 1 SWE and summer streamflow in the Cascades.” UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  14. Follow-up studies: • Mote et al. (2008) • Casola et al. (2009) • Stoelinga et al. (2009) UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  15. My involvement: • Tinkered with streamflow data back to 1930 • - Assumed: May-Sep streamflow serves as proxy for 1 April snowpack (dubious) • Developed a full water balance-based estimate of monthly Cascade snowpack UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  16. Water balance within a watershed or group of watersheds: (change in Snowpack = Precipitation + Evapotranspiration + Runoff + change in soil Moisture ) UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  17. Why use this method? Aren’t direct snow observations and hydrologic modeling well established methods? • Advantages: • Based almost entirely on observations • Result is a watershed-wide estimate of total snowpack • Few knobs to tweak as in hydro modeling • No need to guess at phase of precipitation • No uncertainties about low-elevation snow • Based on consistent, long-term observations of streamflow and precipitation (1930-2007, covering ~3 PDO epoch periods) UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  18. T.I. Seattle Washington Oregon Portland Domain and observations used: UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  19. Annual water balance (over a water year): UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  20. Annual water balance, summed over all watersheds: r2= 0.88 – E0 = – 29.6% UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  21. Monthly water balance: Want monthly values of this Have calibrated monthly measurements Have exact monthly measurements Have annually varying estimate, assumed to distribute among months following climatology UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  22. 1950-1997: -48% ± 34% (-10.3 ± 7.3 % dec-1) (a) 1930-2007: -23% ± 28% (-2.9 ± 3.6 % dec-1) 1976-2007: +19% ± 43% (+6.0 ± 13.7 % dec-1) Resultant time series of April 1st SWE volume within all watersheds UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  23. How good is it? To test this, comparisons were made with direct observations during overlapping time periods. Example: 1 April 2006 snowcourse estimated SWE for all of Cascades (a) (b) (c) West of crest East of crest UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  24. How good is it? Water balance-estimated vs. Snowcourse-estimated snowpack r2 = 0.90 1955-2007 trends in 1 Apr snowpack: Water Balance: -28% Snowcourse: -31% UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  25. Water Balance SNOTEL How good is it? Water balance-estimated vs. Snotel-estimated snowpack UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  26. 1950-1997: -48% ± 34% (-10.3 ± 7.3 % dec-1) (a) 1930-2007: -23% ± 28% (-2.9 ± 3.6 % dec-1) 1976-2007: +19% ± 43% (+6.0 ± 13.7 % dec-1) Resultant time series of April 1st SWE volume within all watersheds UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  27. Sensitivity to Temperature and Precipitation (Casola et al. 2009) • What is the sensitivity of spring snowpack to winter-mean temperature, in terms of percent loss per degree warming? • - Casola et al. arrived at a value of -16 % per deg. C. • What is the appropriate temperature to use in order to both assess the sensitivity from observations, and to predict snowpack loss due to a predicted magnitude of climate change? • - Land air temperatures? • - Offshore air or sea-surface temperatures? UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  28. (b) r = -0.44 (c) r = -0.68 Sensitivity to Temperature and Precipitation (Casola et al. 2009) Using surface T: r2 = 0.19 Using 850mb T (onshore flow): r2 = 0.46 UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  29. (b) r = -0.44 (c) r = -0.68 Sensitivity to Temperature and Precipitation (Casola et al. 2009) Using surface T: r2 = 0.19 MLR of snowpack versus T850ons and precipitation yields a sensitivity of - 11 % per deg. C Using 850mb T (onshore flow): r2 = 0.46 UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  30. Relationship of Cascade spring snowpack to North Pacific natural climate variaiblity Nov-Mar mean SLP (hPa), 1930-2007 Hadley/CRUT gridded historical monthly SLP data set UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  31. Relationship of Cascade spring snowpack to North Pacific natural climate variaiblity Annual variance of Nov-Mar mean SLP (hPa), 1930-2007 UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  32. Relationship of Cascade spring snowpack to North Pacific natural climate variaiblity Annual variance of Nov-Mar mean SLP (hPa), 1930-2007 North Pacific Index (NPI): avg. Nov-Mar SLP in this box UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  33. NPI Time Series UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  34. Cascade Snowpack vs. NPI r2 = 0.27 UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  35. Cascade Snowpack with NPI removed 1950-1997: -29% ± 30% (-6.2 ± 6.4 % dec-1) 1930-2007: -12% ± 24% (-1.6 ± 3.1 % dec-1) 1976-2007: +9% ± 39% (+2.9 ± 12.6 % dec-1) UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  36. Cascade Snowpack 1950-1997: -48% ± 34% (-10.3 ± 7.3 % dec-1) (a) 1930-2007: -23% ± 28% (-2.9 ± 3.6 % dec-1) 1976-2007: +19% ± 43% (+6.0 ± 13.7 % dec-1) UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  37. Relationship of Cascade spring snowpack to North Pacific natural climate variaiblity Annual variance of Nov-Mar mean SLP (hPa), 1930-2007 UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  38. Correlation map of Nov-Mar Mean SLP vs. 1 April Cascade snowpack UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  39. Searching for multiple modes of North Pacific winter-mean circulation that affect Cascade spring snowpack Two approaches: 1. Maximum independent correlation at points (concocted by a local mesoscale meteorologist) 2. Partial least-squares regression (PLSR) (used widely in other fields: econometrics, facial recognition software, etc.) UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  40. Maximum independent correlation at points Correlation map of winter mean SLP vs. Cascade snowpack UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  41. Cycle through each of the three points: • Starting with point 1, remove the influence of the other two points from the entire SLP field and from the snowpack time series, via MLR • Produce a new correlation map with the residual SLP and snowpack time series • Reassign point 1 to the new maximum correlation location. • Repeat for points 2 and 3. • Repeat the entire cycle (steps 1-4) until none of the points move any more. You’re done. • You now have three SLP points that are highly correlated with snowpack but minimally correlated with each other UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  42. Final three points: UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  43. Now create a “Cascade Snowpack Circulation” index, by MLR of snowpack to SLP at the three points Additional variance of Cascade snowpack explained by including each additional point: Point 1: 35% Points 1 + 2: 59% Points 1 + 2 + 3: 71% (!) UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  44. Cascade Snowpack Circulation (CSC) Index Time Series UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  45. (c) 1930-2007: -16% ± 15% (-2.0 ± 1.9 % dec-1) 1976-2007: -5% ± 24% (-1.6 ± 7.9 % dec-1) 1950-1997: -9% ± 19% (-1.9 ± 4.0 % dec-1) Cascade Snowpack with CSC Index removed UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  46. Cascade Snowpack 1950-1997: -48% ± 34% (-10.3 ± 7.3 % dec-1) (a) 1930-2007: -23% ± 28% (-2.9 ± 3.6 % dec-1) 1976-2007: +19% ± 43% (+6.0 ± 13.7 % dec-1) UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  47. (c) 1930-2007: -16% ± 15% (-2.0 ± 1.9 % dec-1) 1976-2007: -5% ± 24% (-1.6 ± 7.9 % dec-1) 1950-1997: -9% ± 19% (-1.9 ± 4.0 % dec-1) Cascade Snowpack with CSC Index removed Is this the signature of greenhouse gas-induced climate change? UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  48. Partial Least Squares Regression • Analogous to EOF analysis • Whereas EOF analysis seeks structures in a field that explain the most variance of the field itself, PLSR seeks structures in one field (the independent variable field) that explain the maximum covariance between it and a second field (the dependent variable field). • In our case, the independent variable is winter mean SLP over the northeast Pacific Ocean; the dependent field is Cascade snowpack. • Variance in snowpack explained by patterns in SLP: • Pattern 1: 42% • Pattern 2: 26% (P1 + P2 = 68% of var expl!) • Pattern 3: 3% UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  49. Partial Least Squares Regression Pattern 1 Pattern 2 UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

  50. Cascade Snowpack with PLSR-derived CSC Index removed All 3 trends are around -2.0 % dec-1 UW Atmospheric Sciences Colloquium 22 May 2009 Seattle, WA

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