1. Detecting SWE peak time from passive microwave data Naoki Mizukami GEOG6130 Advanced Remote Sensing

2. Peak SWE time - Why important? Peak SWE time - Why important? USGS  Peak SWE time affects timing of streamflow peak in snowmelt dominated stream  Peak SWE affect the magnitude of streamflow rate

3. Estimates of peak SWE time  Daily SWE observations (e.g. SNOTEL) Point measurements Measurement sites are sparse No established methods for interpolation/extrapolation of point measurements  Remote sensing Not much explored

4. Objective  Estimate peak SWE time via passive microwave TB measurements  Compare PM derived peak SWE time with SNOTEL observed peak SWE time

5. Passive microwave snowmelt signal dry Low Scattering Emission wet High snowpack Microwave response TB Accumulation period ablation period time SWE SWE peak time

6. Dataset  Daily SSM/I brightness temperature (TB) Data source-National Snow and Ice Data Center (NSIDC) at University of Colorado. 7 channels (19GHz ~ 85GHz, Horizontal & Vertical polarization) The pixel size is 25 km x 25km (EASE-GRID) 2001-2002  Daily snow water equivalent (SWE) Data source- Snow Telemetry (SNOTEL), Natural Resources Conservation Service (NRCS). 2001-2002

7. TB(37GHz V), Day 82 – 87 (2002)

8. Analysis Procedure  Obtain 10 day average TB and SNOTEL SWE  Obtain temporal change in TB for one time step ΔTB (time i) = TB(time i) - TB(time i-1)  Find time when maximum ΔTB occurs Day1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 time i time i+1 time i+2

9.  Use SSM/I grids that encompass min. 2 SNOTEL sites SSM/I grid SNOTEL

10. Time series –SWE & TBs at one grid Continental snowpack

11. Time series –SWE & Δ37V Daily time series of SWE and Δ37V (2001-2002) Continental snowpack

12. Time series –SWE & TBs at one grid 2001-2002 season maritime snowpack

13. Time series –SWE & Δ37V Daily time series of SWE and Δ37V (2001-2002) maritime snowpack

14. Observed peak SWE time from SNOTEL PM derived peak SWE time Peak SWE time map  Similar spatial pattern  Obvious error

15. PM derived peak SWE time – SNOTEL peak SWE time Estimate errors in peak SWE time

16. Summary  Passive microwave TB (37V) was used to detect peak SWE time during winter - finding max. 37V temporal change  Spatial pattern for estimated SWE peak time is similar to SNOTE observed peak time.  Significant errors exist in maritime snowpack climate

17. SSM/I grid and SNOTEL sites Longitude latitude SSM/I pixel (orange dot) and 4 SNOTEL sites (yellow dots) within 25km from the center of the pixel UT WY

18. Snow climate Physical characteristics alpineCold deep snow, numerous layers, some wind affected, low density prairieThin, moderately cold snowpack, wind slab ephemeralA thin, extremely warm snow (0~50cm deep). Melting is common. Short life MaritimeWarm deep snow, coarse grain, occasional melt TaigaModerately deep cold snow (low density). Depth hoar common TundraA thin, cold, wind-blown snow. Melting is rare. Depth hoar overlain by wind slab snow classification system developed by Sturm et al. (1995)