The Heat is On: Snow and Water Resources in a Changing Climate

1. The Heat is On: Snow and Water Resources in a Changing Climate Tom Pagano, Tom.Pagano@por.usda.gov 503 414 3010

2. Outline Climate Change and Trend Research at NRCS Past studies using NRCS data When do trends start? What drives historical trends? “Garbage in, Garbage out”: Systematic biases Understanding implications for water managers Projections in perspective Mapping vulnerability Higher order impacts Communication and uncertainty issues

3. Past studies of Western US snowpack trends

4. Past studies of Western US snowpack trends Aguado et al 1992: Donner Summit Feb 1 SWE/Oct-Jan Precip at Nevada City trending down over 1920-83 (about ~20% decline). Karl, et al 1993: 1973-1990 NH Snow cover affected by temperature. No Lower 48 US trend in Snowfall/Precip 1950-1990. Dettinger & Cayan 1994: 1948-1987 significant westwide declines in April 1 snowcourse SWE/Nov-Mar precip for the nearest climate division, esp Cascades, California, Montana McCabe & Wolock 1999: 1948-1987 Apr 1 SWE clustered into 4 regions. ~0.8 correlation with Nov-Mar precip, -0.24 to -0.58 correlation with Nov-Mar temperature. Only Pacific Northwest had significant downward trends. Serreze et al 1999: Westwide 1981-1995 no strong trend in SWE/precipitation ratio, but well correlated with temperature. Selkowitz et al 2002: Northern Montana, 35% April 1 SWE decrease 1950-2001. 10% May 1 SWE increase 1922-2001. Trend and PDO similar with multi-year smoothing (therefore not climate change but glaciers still disappearing). Mote 2003a: Northwest Washington- Period of Record and 1950-(2003?) April 1 SWE downward linear trend, many in excess of 40%. Low elevations strongest decline. Trends before 1950 positive although only handful of high elevation stations exist. Regression of SWE against Precip and Temp confirmed trend signal. Vegetation change observed to exaggerate downward trend. Mote 2003b: WA/OR/ID/MT April 1 SWE 1950-2000 trend negative. January-May all show similar trends. Low elevations strongest decline. Cascade trend mostly attributed to temperature (via interannual regression) Howat 2005: 1950-2002 April 1 SWE in California. Increased precip and temp mean swe increases in southern Sierras but decreases at low elevations. Decreased precip and increased temp mean SWE loss in northern California. Hamlet, et al 2005: 1915-2003 and 1947-2003 westwide, model compared to obs, trend deconstructed for temperature and precip. Temperature trends not well explained by PDO. Mote et al 2005: April 1 SWE trends match model westwide trends. Trends back to 1930 not as strong as trends back to 1950 but still negative. Trend strongest at lowest elevation. Regonda et al 2005: Summarized past studies. March-May SWE significantly declining westwide. Biggest declines at low elevation. Knowles et al 2006: 1949-2004 Snow fall vs winter precipitation trends strongest in March, January due to warming. Going back to 1920 shows PDO partly but not totally to blame. Mote 2006: Similar to other Mote works. Pacific climate explains 10-60% of trends. Mote et al 2007 Half of 1944-2006 April 1 Washington’s 24% decline explainable by regional Temperature/Precip. Change strongest at low elevations. Compared trends for all years from 1935-1975 to 2003. April 1 SWE/Nov-Mar Precip ratio decreased 28% 1944-2006. PDO is not significantly responsible.

5. “Yes”… Snow Water Equivalent is largely determined by precipitation. Temperature can have a relatively strong affect in some areas (Pacific Northwest, Sierras) Trends from 1950-2000 show significant losses, more rain less snow. Trends are less at high elevations, greater at low elevations.

6. “Yes”… Snow Water Equivalent is largely determined by precipitation. Temperature can have a relatively strong affect in some areas (Pacific Northwest, Sierras) Trends from 1950-2000 show significant losses, more rain less snow. Trends are less at high elevations, greater at low elevations. “But”… Taylor, Daly & NRCS personnel 2004 (conference poster): Little correlation between temperature and snowfall at Government Camp in January 1953-2003. A 1976 step change better explains Government Camp snowfall than linear trend. Snowfall/Precip at Crater Lake shows no trend since mid 1950s. Julander and Bricco (NRCS personnel) 2006 (conference paper): Vegetation, Station moves, Cloud Seeding, Pollution, Sensor technology confound climate signals. 8 sites (6% of 134) in Utah could be suitable for climate analysis. 60% of Utah sites are shifted by more than 5% due to non-climate signals. Albright 2007 (email and webpage): “Myth of the vanishing Cascade Mtn snowpack” Ollalie Meadows forest clear cut in 1970s, so this step change may give false impression of trend. Average snow in 1997-2006 > 1940-1949 for 3 stations in Washington Oregon 27 site average 1996-2005/1936-2005 down ~13% (consistent with Mote et al 2006)

7. Down ~40% of normal Washington-wide snowpack since 1950, Relative to 1971-2000 normal Snowpack in usual maximum month

8. Essentially flat Washington-wide snowpack period of record, Relative to 1971-2000 normal Snowpack in usual maximum month

9. Number sites Before 1945 network is not representative Average Elevation

10. Bumping Lake Snow Water Equivalent (merged) April 1 SWE (inches) Snow trends 1915-2007 1945 1950 >+100% +50% 0% -50% <-100% 1960 Period change as % 1971-00 normal 1970 End Date Shorter Window length Longer 1980 1990 2000 1915-2007 = -7% 1977 1920 1930 1940 1950 1960 1970 Start Year

11. Bumping Lake Snow Water Equivalent (merged) April 1 SWE (inches) Snow trends 1915-2007 1945 1950 1926-1956 = +115% >+100% +50% 0% -50% <-100% 1960 Period change as % 1971-00 normal 1970 End Date Shorter Window length Longer 1980 1990 2000 1977 1920 1930 1940 1950 1960 1970 Start Year

12. Bumping Lake Snow Water Equivalent (merged) April 1 SWE (inches) Snow trends 1915-2007 1945 1950 >+100% +50% 0% -50% <-100% 1960 Period change as % 1971-00 normal 1970 End Date Shorter Window length Longer 1980 1990 1949-1992 = -98% 2000 1977 1920 1930 1940 1950 1960 1970 Start Year

13. Trends do not indicate cause. How much of the trend is caused by Temperature? Precipitation? Correlate SWE versus climate division data: Bumping Lake SWE vs WA Clim Div #6 ONDJFM Precip Bumping Lake SWE vs WA Clim Div #6 March Temp r2=0.32 r2=0.42 1934 1934

14. Develop regression of P & T vs Swe and look at trends Period change as % 1971-00 normal End Year >+100% +50% 0% -50% <-100% 1930 Observed 1940 1950 1960 1970 1980 1990 2000

15. Develop regression of P & T vs Swe and look at trends Period change as % 1971-00 normal End Year >+100% +50% 0% -50% <-100% 1930 1930 Observed Precipitation only 1940 1940 1950 1950 1960 1960 1970 1970 1980 1980 1990 1990 2000 2000 1930 Temperature only 1940 1950 1960 1970 1980 1990 2000 1900 1920 1940 1960 1980 1900 1920 1940 1960 1980 Start Year Start Year

16. Develop regression of P & T vs Swe and look at trends Period change as % 1971-00 normal End Year >+100% +50% 0% -50% <-100% 1930 1930 Observed Precipitation only 1940 1940 1950 1950 1960 1960 1970 1970 1980 1980 1990 1990 2000 2000 1930 1930 Temperature only Temp and Precip 1940 1940 1950 1950 1960 1960 1970 1970 1980 1980 1990 1990 2000 2000 1900 1920 1940 1960 1980 1900 1920 1940 1960 1980 Start Year Start Year

17. End Year 1930 Observed 1940 1950 1960 Bumping Lake April 1 Snow Water Equivalent Trends Observed and Reconstructed from Temperature and Precipitation 1970 1980 1990 2000 1930 Climate driven (P & T) 1940 1950 1960 >+100% +50% 0% -50% 1970 <-100% 1980 Period change as % 1971-00 normal 1990 2000 1930 Non-Climate (residual trend) 1940 1950 No major trends from non-climate factors 1960 1935 station move? 1970 1980 1990 2000 1900 1980 1920 1940 1960 Start Year

18. Bumping Lake April 1 Snow Water Equivalent 70% normal loss since 1950 “Temperature reconstructed” 40% normal loss since 1950 “Precipitation reconstructed”

19. Obs T and P 1960-2002 April 1 SWE Trends Much of this kind of analysis has already been done by others. The signal seems regionally coherent and can be tied back to climate trends in many instances. Precip Temp Mote 2006

20. But wait…There’s all kind of problems with the data. How can we have any confidence in the analyses? Can metadata help with systematic biases? What metadata do we need? What is the state of the metadata? Is it too late to start collecting it? What will people do with it?

21. Clear cutting Precip SWE Oregon Public Radio Water Sustainability show on 4.15.08 Phillip Ward, Director Oregon Water Resources Department: “There were places in the coast range that, just a couple weeks ago, had over … 500% of normal snowpack”

22. Station history status Spotty… Some places excellent. Other places poor, non-digitized, non uniform.

23. Big Flat, UT Site sketch

24. http://www.ut.nrcs.usda.gov/snow/data/long-term_snow_data_comp.htmlhttp://www.ut.nrcs.usda.gov/snow/data/long-term_snow_data_comp.html Overview of systematic biases in Utah snow data Analysis of individual site histories What’s wrong with the temperature data

25. Snowcourses are not measured exactly on the 1st of the month. Leadtime has changed over time… Another systematic bias?

26. Can adjust for measurement date, but in the big picture, this effect is small May 1: Trend towards earlier measurements gives appearance of upwards long-term trend. If observed data trend is negative, real data trend is even more negative.

27. Can adjust for measurement date, but in the big picture, this effect is small May 1: Trend towards earlier measurements gives appearance of upwards long-term trend. If observed data trend is negative, real data trend is even more negative. Feb 1: Opposite is true April 1: Typically a wash

28. Understanding implications for water managers Projections in perspective Mapping vulnerability Higher order impacts Communication and uncertainty issues

29. Dinosaurs Stone age Iron age Humans leave Africa Source: http://en.wikipedia.org/wiki/Geologic_temperature_record Studies used: 540 - 65 Myr BP : Royer, Dana L. and Robert A. Berner, Isabel P. Montañez, Neil J. Tabor, David J. Beerling (2004) CO2 as a primary driver of Phanerozoic climate GSA Today July 2004, volume 14, number 3, pages 4-10. 65 - 5.5 Myr BP : Zachos, James, Mark Pagani, Lisa Sloan, Ellen Thomas, and Katharina Billups (2001). "Trends, Rhythms, and Aberrations in Global Climate 65 Ma to Present". Science292 (5517): 686–693. 5.5 Myr - 420 kyr BP : Lisiecki, L. E., and M. E. Raymo (2005), A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records, Paleoceanography, 20, PA1003, doi:10.1029/2004PA001071. 420 kyr - 12 kyr BP : Petit J.R., Jouzel J., Raynaud D., Barkov N.I., Barnola J.M., Basile I., Bender M., Chappellaz J., Davis J., Delaygue G., Delmotte M., Kotlyakov V.M., Legrand M., Lipenkov V., Lorius C., Pépin L., Ritz C., Saltzman E., Stievenard M. (1999) Climate and Atmospheric History of the Past 420,000 years from the Vostok Ice Core, Antarctica, Nature, 399, pp.429-436.12 kyr - 2000 yr BP : various (12 studies) 2000 yr - 150 yr Before 2000 :various (10 studies) 150 - 0 yr Before 2000 : Brohan, P., J.J. Kennedy, I. Haris, S.F.B. Tett and P.D. Jones (2006). "Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850". J. Geophysical Research111: D12106

30. Lake Missoula Floods Medieval Warm Period Source: http://en.wikipedia.org/wiki/Geologic_temperature_record Studies used: 540 - 65 Myr BP : Royer, Dana L. and Robert A. Berner, Isabel P. Montañez, Neil J. Tabor, David J. Beerling (2004) CO2 as a primary driver of Phanerozoic climate GSA Today July 2004, volume 14, number 3, pages 4-10. 65 - 5.5 Myr BP : Zachos, James, Mark Pagani, Lisa Sloan, Ellen Thomas, and Katharina Billups (2001). "Trends, Rhythms, and Aberrations in Global Climate 65 Ma to Present". Science292 (5517): 686–693. 5.5 Myr - 420 kyr BP : Lisiecki, L. E., and M. E. Raymo (2005), A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records, Paleoceanography, 20, PA1003, doi:10.1029/2004PA001071. 420 kyr - 12 kyr BP : Petit J.R., Jouzel J., Raynaud D., Barkov N.I., Barnola J.M., Basile I., Bender M., Chappellaz J., Davis J., Delaygue G., Delmotte M., Kotlyakov V.M., Legrand M., Lipenkov V., Lorius C., Pépin L., Ritz C., Saltzman E., Stievenard M. (1999) Climate and Atmospheric History of the Past 420,000 years from the Vostok Ice Core, Antarctica, Nature, 399, pp.429-436.12 kyr - 2000 yr BP : various (12 studies) 2000 yr - 150 yr Before 2000 :various (10 studies) 150 - 0 yr Before 2000 : Brohan, P., J.J. Kennedy, I. Haris, S.F.B. Tett and P.D. Jones (2006). "Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850". J. Geophysical Research111: D12106

31. Lake Missoula Floods Max/Min IPCC AR2 Projections for 2100 Medieval Warm Period Source: http://en.wikipedia.org/wiki/Geologic_temperature_record Studies used: 540 - 65 Myr BP : Royer, Dana L. and Robert A. Berner, Isabel P. Montañez, Neil J. Tabor, David J. Beerling (2004) CO2 as a primary driver of Phanerozoic climate GSA Today July 2004, volume 14, number 3, pages 4-10. 65 - 5.5 Myr BP : Zachos, James, Mark Pagani, Lisa Sloan, Ellen Thomas, and Katharina Billups (2001). "Trends, Rhythms, and Aberrations in Global Climate 65 Ma to Present". Science292 (5517): 686–693. 5.5 Myr - 420 kyr BP : Lisiecki, L. E., and M. E. Raymo (2005), A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records, Paleoceanography, 20, PA1003, doi:10.1029/2004PA001071. 420 kyr - 12 kyr BP : Petit J.R., Jouzel J., Raynaud D., Barkov N.I., Barnola J.M., Basile I., Bender M., Chappellaz J., Davis J., Delaygue G., Delmotte M., Kotlyakov V.M., Legrand M., Lipenkov V., Lorius C., Pépin L., Ritz C., Saltzman E., Stievenard M. (1999) Climate and Atmospheric History of the Past 420,000 years from the Vostok Ice Core, Antarctica, Nature, 399, pp.429-436.12 kyr - 2000 yr BP : various (12 studies) 2000 yr - 150 yr Before 2000 :various (10 studies) 150 - 0 yr Before 2000 : Brohan, P., J.J. Kennedy, I. Haris, S.F.B. Tett and P.D. Jones (2006). "Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850". J. Geophysical Research111: D12106

32. Max/Min IPCC AR2 Projections for 2100 Source: http://en.wikipedia.org/wiki/Geologic_temperature_record Studies used: 540 - 65 Myr BP : Royer, Dana L. and Robert A. Berner, Isabel P. Montañez, Neil J. Tabor, David J. Beerling (2004) CO2 as a primary driver of Phanerozoic climate GSA Today July 2004, volume 14, number 3, pages 4-10. 65 - 5.5 Myr BP : Zachos, James, Mark Pagani, Lisa Sloan, Ellen Thomas, and Katharina Billups (2001). "Trends, Rhythms, and Aberrations in Global Climate 65 Ma to Present". Science292 (5517): 686–693. 5.5 Myr - 420 kyr BP : Lisiecki, L. E., and M. E. Raymo (2005), A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records, Paleoceanography, 20, PA1003, doi:10.1029/2004PA001071. 420 kyr - 12 kyr BP : Petit J.R., Jouzel J., Raynaud D., Barkov N.I., Barnola J.M., Basile I., Bender M., Chappellaz J., Davis J., Delaygue G., Delmotte M., Kotlyakov V.M., Legrand M., Lipenkov V., Lorius C., Pépin L., Ritz C., Saltzman E., Stievenard M. (1999) Climate and Atmospheric History of the Past 420,000 years from the Vostok Ice Core, Antarctica, Nature, 399, pp.429-436.12 kyr - 2000 yr BP : various (12 studies) 2000 yr - 150 yr Before 2000 :various (10 studies) 150 - 0 yr Before 2000 : Brohan, P., J.J. Kennedy, I. Haris, S.F.B. Tett and P.D. Jones (2006). "Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850". J. Geophysical Research111: D12106

33. Vertical range based on climate sensitivity (2x CO2eq = +4.5, 3 or 2 deg C) From: http://en.wikipedia.org/wiki/Image:IPCC_AR4_WGIII_GHG_concentration_stabilization_levels.png Based on: Summary for Policy Makers IPCC 4th Assessment Report Working Group III Figure SPM8

34. Vertical range based on climate sensitivity (2x CO2eq = +4.5, 3 or 2 deg C) peak ~2060 increase ~50% by 2050 Emissions peak ~2010 Emissions drop ~45% by 2050 relative to 2000 emissions 2000-2006: Emissions increased 20% From: http://en.wikipedia.org/wiki/Image:IPCC_AR4_WGIII_GHG_concentration_stabilization_levels.png Based on: Summary for Policy Makers IPCC 4th Assessment Report Working Group III Figure SPM8

35. Mean change: +2°F (2020s), +3°F (2040s) • Warming expected in all seasons +2.9ºF (1.4-4.6ºF) +1.9ºF (0.7-3.2ºF) Changes relative to 1970-1999 Projected 21st Century Pacific Northwest Warming From UWash Climate Impacts Group. More detail on the CIG scenarios is available at: http://www.cses.washington.edu/cig/fpt/ccscenarios.shtml

36. Projected 21st Century Pacific Northwest Warming • Mean change: +2°F (2020s), +3°F (2040s) • Warming expected in all seasons +2.9ºF (1.4-4.6ºF) +1.9ºF (0.7-3.2ºF) Changes relative to 1970-1999 From UWash Climate Impacts Group. More detail on the CIG scenarios is available at: http://www.cses.washington.edu/cig/fpt/ccscenarios.shtml

37. Projected 21st Century Pacific Northwest Warming • Mean change: +2°F (2020s), +3°F (2040s) • Warming expected in all seasons Multnomah county average temperature departure (deg F) from 70-99 +2.9ºF (1.4-4.6ºF) +1.9ºF (0.7-3.2ºF) Changes relative to 1970-1999 From UWash Climate Impacts Group. More detail on the CIG scenarios is available at: http://www.cses.washington.edu/cig/fpt/ccscenarios.shtml

38. Projected 21st Century Pacific Northwest Warming • Mean change: +2°F (2020s), +3°F (2040s) • Warming expected in all seasons Multnomah county average temperature departure (deg F) from 70-99 +2.9ºF (1.4-4.6ºF) +1.9ºF (0.7-3.2ºF) Portland becomes like San Francisco (+2.2C/4F) Changes relative to 1970-1999 From UWash Climate Impacts Group. More detail on the CIG scenarios is available at: http://www.cses.washington.edu/cig/fpt/ccscenarios.shtml

39. Clear Lake Snotel Tavg Water year 2004 Rain Snow Average Temperature Deg C

40. Clear Lake Snotel Tavg Water year 2004 Rain Vulnerable Snow Average Temperature Deg C

41. Clear Lake Snotel Tavg Water year 2004 Rain Vulnerable Snow Average Temperature Deg C Clear Lake Accumulated Water Year Precipitation Rainfall (54%) Vulnerable Snowfall (30%) Precipitation (inches) Snowfall (16%)

42. Annual fraction of snow+rain that would fall as rain instead of snow A +3ºC change (+5.4ºF… as soon as 2060-2100?) in average temperature means less snow (red areasmean more vulnerable) Most vulnerable Maurer et al, 2002

43. Oregon-Washington Cascades (Snotel stations within 3 degrees of Mt Hood Test Site) Timberline Lodge (6000 ft) Elevation (ft) Government Camp (3900 ft) Falling on days with Tavg>0C (rain) Rhododendron (1600 ft) Percent of water year precipitation Calculated from station data 1990-2007

44. Oregon-Washington Cascades (Snotel stations within 3 degrees of Mt Hood Test Site) Falling on days with Tavg>-3C (rain + vulnerable) Elevation (ft) Falling on days with Tavg>0C (rain) With +3 C warming “90% rain” zone raises from 2525 ft to 3980 ft (+1455 ft) Standard atmosphere lapse rate: 3 C/1500 ft Percent of water year precipitation Calculated from station data 1990-2007

45. Percent of annual precipitation that falls on days with average temperature > 32.0 F (-0 C) (Based on spatial interpolation of SNOTEL data 1990-2007) Rainy Counties Snowy How this was made: For historical SNOTEL station data, sum of precipitation on days that average temperature >0C, >-1C, >-2C etc, divided by total annual precipitation on days that temperature was available. Regress resulting ratio versus elevation. Transform high spatial resolution elevation dataset by regression relationship. Dams 45 of 44

46. Percent of annual precipitation that falls on days with average temperature > 30.2 F (-1 C) (Based on spatial interpolation of SNOTEL data 1990-2007) Rainy Counties Snowy The new landscape in 2030? Dams 46 of 44

47. Percent of annual precipitation that falls on days with average temperature > 28.4 F (-2 C) (Based on spatial interpolation of SNOTEL data 1990-2007) Rainy Counties Snowy The new landscape in 2065? Dams 47 of 44

48. Percent of annual precipitation that falls on days with average temperature > 26.6 F (-3 C) (Based on spatial interpolation of SNOTEL data 1990-2007) Rainy Counties Snowy The new landscape in 2100? Dams 48 of 44

49. Percent of annual precipitation that falls on days with average temperature > 32.0 F (-0 C) (Based on spatial interpolation of SNOTEL data 1990-2007) Rainy Counties Snowy Today (1990-2007) Dams 49 of 44

50. Percent of annual precipitation that fell on days with average temperature > 32 F (0 C) Mt Hood Test Site (5400’) All rain Blazed Alder +2 C +3.6 F +1 C +1.8 F Blazed Alder (3650’) Mt Hood Test Site All snow Future lines: expected change, assuming warming by certain dates 50 of 44 The details: “Future” value at 2030 is 1990-2007 observed % of annual precipitation falling on days with Tavg > -1C, 2050 value is for Tavg > -2C. 1997 is 1990-2007 observed for Tavg > 0C. Lines between are linear interpolations.