Snowcover along elevation gradients in the Upper Merced and Tuolumne River basin of the Sierra Nevada of California from MODIS and blended ground data

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1 Snowcover along elevation gradients in the Upper Merced and Tuolumne River basin of the Sierra Nevada of California from MODIS and blended ground data Robert Rice a, Roger Bales a, Thomas H. Painter b, Jeff Dozier c a Sierra Nevada Research Institute, UC Merced b National Snow and Ice Data Center, CU Boulder c Bren School, UC Santa Barbara MODIS false color composite of Tuolumne, Merced and adjacent basins.

2 Upper Tuolumne basin, May MODIS snowcover product. Snowcover patterns: 2004 & Snow water equivalent (SWE) analysis. Critical elevation bands: measurement & change.

3 Tuolumne- 4,184 km 2 Merced- 2,846 km 2 elevation, m

4 MODSCAG MODIS Snow Covered Area and Grain size April 10, 2004 Based on MEMSCAG (Multiple Endmember Snow-Covered Area and Grain Size) Painter et al., 2003, RSE

5 Filtering and smoothing of MODIS daily snow cover and grain size Objective: produce time series that is spatially and temporally complete and consistent Contributors to noisy daily values Data dropouts and sensor noise Cloud cover Sensor viewing angle (nadir to 65 ) Smearing pixels up to 2.5 in cross-track direction Off-angle views of snow under trees see less snow than nadir views Other Subpixel cloud cover Topographic variability within pixel Etc

6 Example of cloudy day

7 Effect of viewing angle (Tuolumne & Merced)

8 Noisy variability caused by look angle, small clouds, vegetation, topography detail Vegetation causes differences in view angle 8

9 Need to interpolate and smooth to fill the space-time cube Raw snow cover Interpolated snow cover

10 Approach Wiener 2D filter to eliminate noise (set noisy values to NaN). Cloud/snow discrimination based on grain size and location (set cloudy values to NaN). Interpolate in time dimension using smoothing splines,, weighted by cos 2 of view angle. Then interpolate in spatial dimension with quickhull algorithm.

11 Tuolumne 2004 January-July July

12 Tuolumne 2004 October-2005 July

13 Tuolumne Upper Tuolumne (2,420 km 2 above 1500-m), snow depth & snow water equivalent (SWE) are measured daily at 7 snow pillows & monthly at 17 snow courses. Distributed SWE estimates developed from a range-wide interpolation. Merced In the Upper Merced (1,755 km 2 above 1500-m), snow depth & snow water equivalent (SWE) are only measured daily at only 3 snow pillows & monthly at 2 additional snow courses.

14 Melt season SCA: Tuolumne 2004 elev band, m 3750 Tuolumne 2004: 2004: less snow (83% of normal) ground became snow free relatively early SCA, fraction Each higher elevation band requires ~1 mo longer to become snow free 0.0 3/1/04 4/1/04 5/1/04 6/1/04 7/1/04 8/1/04 9/1/04 10/1/04 Merced 2005 Merced 2005: more snow (163%) ground became snow free ~1 mo later than in 2004

15 Tuolumne interpolated, blended SWE Little elevation difference in interpolated SWE at beginning of snowmelt. SWE (m) elevation band, m Jan Feb Mar Apr May Jun Jul Average SWE across an elevation band, accounting for fractional SCA, shows distinct gradient with elevation. SWE x SCA (m) Jan Feb Mar Apr May Jun Jul 2004

16 Merced interpolated, blended SWE Little elevational difference in interpolated SWE at beginning of snowmelt Average SWE across an elevation band, accounting for fractional SCA, shows distinct gradient with elevation

17 Snowmelt by elevation band based on interpolated, masked SWE: June/July 2005 Progressive contributions from higher elevation bands w/ time. No to little contributions form lowest or highest elevations. Volumne snowmelt, 10 7 m contributions to snowmelt by elev band, m Tuolumne 0 6/15/05 6/20/05 6/25/05 6/30/05 7/5/05 7/10/05 7/15/05 Merced

18 Alternate estimate of SWE & snowmelt from SCA time series & snowmelt analysis Determine potential snowmelt per elevation band based on energy balance or degree day calculation. Potential snowmelt quantity applied to all areas with snowcover, using fractional SCA per pixel. That is, if an area has snowcover it is assumed to contribute melt at a rate equal to the potential snowmelt times SCA. Amount of snowmelt calculated up to day when SCA is depleted equals beginning SWE.

19 Tuolumne Degree day factor estimated from snow pillow sites SWE, cm Kibbie Ridge Paradise MDW Horse MDW Tuolumne MDW Slide CNY Dana Meadow No systematic variation of degree day factor with elevation. Strong seasonal change in degree day factor. Degree day factor snow pillow data 0 Jan Feb Mar Apr May Jun Jul Gin Horse Kibbie Paradise Slide Tuolumne Tioga /1/04 4/1/04 5/1/04 6/1/04 7/1/04

20 Merced Degree day factor estimated from snow pillow sites No systematic variation of degree day factor with elevation. Strong seasonal change in degree day factor.

21 60 Contributions to snowmelt by elevation band, snowmelt based on degree day calculation Volumne snowmelt, 10 7 m Tuolumne /1/04 4/1/04 5/1/04 6/1/04 7/1/04 8/1/04 9/1/04 10/1/04 Merced

22 Tuolumne-2004 Comparing snowmelt based on interpolated SWE vs. degree day calculation Rapid depletion based on interpolation of snow pillow data. Large contributions from below 2100 m by interpolation method. Interpolation over-estimates below 3000 m & underestimates above 3000 m. Volumne snowmelt, 10 7 m 3 Volumne snowmelt, 10 7 m 3 60 Based on SCA depletion and degree day calculation /1/04 4/1/04 5/1/04 6/1/04 7/1/ Based on interpolated SWE /1/04 4/1/04 5/1/04 6/1/04 7/1/04

23 Merced Comparing snowmelt based on interpolated SWE vs. Degree day calculation Lower elevations depleted prior to this June period Interpolated method also shows more rapid depletion at mid elevations Less total melt for interpolated method because snow pillow sites melted out early

24 One source of error is vegetation Note gap between accumulation season SCA & canopy fraction below ~2400 m elevation

25 Fraction of snowmelt contributed by various elevation bands 0.6 March - Septemeber Snowmelt Catchment area Fraction Elevation band, m Tuolumne Merced

26 Snowmelt Catchment area March 2004 Tuolumne fraction March snowmelt Elevation band, m Merced Main contributions 2004: m 2005: m Colder at higher elevations

27 0.6 April 2004 Fraction Snowmelt Catchment area Tuolumne April snowmelt Elevation band, m Main contributions: 2004: m 2005: m Merced

28 0.6 Fraction Snowmelt Catchment area May 2004 Tuolumne May snowmelt Elevation band, m Main contributions: 2004: m 2005: m Merced

29 Snowmelt Catchment area June 2004 Tuolumne Fraction June snowmelt Elevation, m Merced Main contributions: 2004: m 2005: m

30 0.6 July 2004 Fraction Snowmelt Catchment area Tuolumne July snowmelt Elevation, m Main contributions: m Merced

31 0.6 August 2004 Fraction Snowmelt Catchment area Tuolumne August snowmelt Elevation, m Main contributions: 2004: m 2005: m Merced

32 Conclusions: snow in Upper Tuolumne & Merced (2004 & 2005) 36%-of Tuolumne (34%-Merced) snowmelt from above 3000 m. Note: highest snow pillow is 2918 m. Main source of Aug-Sep snowmelt. Also important in July (2004 & 2005) & June (2004). 13%- of Tuolumne (5%-Merced) snowmelt from below 2100 m. Note: lowest snow pillow is 2100 m. Important mainly in March (2004 & 2005) & April (2005). 50%- of Tuolumne (60%-Merced) snowmelt from m. SCA depletion occurred over 2 mo at m, 4 mo at m. SCA depletion required 1 mo longer at each higher elevation. All snow pillows melt out much faster, mo. SCA depletion maps provide a better quantitative basis for estimating basin-scale scale SWE than do snow pillows. Vegetation may cause under-estimation estimation of 20-50% at elevations below 2400 m & 5% overall

33 Acknowledgement Funded by NASA Grant NNG04GC52A REASoN CAN Multi-resolution snow products for the hydrologic sciences. Xiande Meng (UCM), Peter Slaughter (UCSB).

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