Detecting SWE peak time from Detecting SWE peak time from passive microwave datapassive microwave data

Naoki Mizukami

GEOG6130 Advanced Remote Sensing

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

Estimates of peak SWE timeEstimates 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

ObjectiveObjective

Estimate peak SWE time via passive microwave TB measurements

Compare PM derived peak SWE time with SNOTEL observed peak SWE time

Passive microwave snowmelt Passive microwave snowmelt signalsignal

dry

Low

Scattering Emission

wet

High

snowpack

Microwave response

TB

Accumulation period ablation period

time

SWE

SWE peak time

DatasetDataset 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

TB(37GHz V), Day 82 – 87 (2002)

Analysis ProcedureAnalysis Procedure Obtain 10 day average TB and SNOTEL

SWE

Obtain temporal change in TB for one time stepΔTB (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

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

SSM/I gridSNOTEL

Time series –SWE & TBs at one Time series –SWE & TBs at one gridgrid

0

5

10

SW

E [c

m]

SWE

Jul01 Oct01 Jan02 Apr02 Jul02180

200

220

240

260

280

Tb

[K] 19V

19H

37V

37H

85V

85H

0

5

10

180

200

220

240

260

280

19V

19H

37V

37H

85V

85H

Jul01 Oct01 Jan02 Apr02 Jul02-20

-10

0

10

20

30

Continental Continental snowpacksnowpack

0

5

10

180

200

220

240

260

280

19V

19H

37V

37H

85V

85H

Jul01 Oct01 Jan02 Apr02 Jul02-20

-10

0

10

20

30

Time series –SWE & Time series –SWE & ΔΔ37V37V

Daily time series of SWE and Δ37V (2001-2002)

0

5

10

SW

E [c

m]

Jul01 Oct01 Jan02 Apr02 Jul02-20

-10

0

10

20

30

3

7V

Continental Continental snowpacksnowpack

05

101520

253035

404550

180

200

220

240

260

280

19V

19H

37V

37H

85V

85H

Jul01 Oct01 Jan02 Apr02 Jul02-20

-10

0

10

20

30

Time series –SWE & TBs at one Time series –SWE & TBs at one gridgrid

2001-2002 season

0

5

10

SW

E [c

m]

SWE

Jul01 Oct01 Jan02 Apr02 Jul02180

200

220

240

260

280

Tb

[K] 19V

19H

37V

37H

85V

85H

maritime maritime snowpacksnowpack

05

101520

253035

404550

180

200

220

240

260

280

19V

19H

37V

37H

85V

85H

Jul01 Oct01 Jan02 Apr02 Jul02-20

-10

0

10

20

30

Time series –SWE & Time series –SWE & ΔΔ37V37V

Daily time series of SWE and Δ37V (2001-2002)

0

5

10

SW

E [c

m]

Jul01 Oct01 Jan02 Apr02 Jul02-20

-10

0

10

20

30

3

7V

05

101520

253035

404550

180

200

220

240

260

280

19V

19H

37V

37H

85V

85H

Jul01 Oct01 Jan02 Apr02 Jul02-20

-10

0

10

20

30

05

101520

253035

404550

180

200

220

240

260

280

19V

19H

37V

37H

85V

85H

Jul01 Oct01 Jan02 Apr02 Jul02-20

-10

0

10

20

30

maritime maritime snowpacksnowpack

Observed peak SWE time from Observed peak SWE time from SNOTELSNOTEL

PM derived peak SWE timePM derived peak SWE time

Peak SWE time mapPeak SWE time map

Similar spatial pattern

Obvious error

PM derived peak SWE time – SNOTEL peak SWE PM derived peak SWE time – SNOTEL peak SWE timetime

Estimate errors in peak SWE timeEstimate errors in peak SWE time

SummarySummary

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

SSM/I grid and SNOTEL sitesSSM/I grid and SNOTEL sites

-113 -112.5 -112 -111.5 -111 -110.5 -11040

40.5

41

41.5SNOTEL sitesSSM/I pixel center

Longitude

lati

tud

e

SSM/I pixel (orange dot) and 4 SNOTEL sites (yellow dots) within 25km from the center of the pixel

UTWY

Snow climate Snow climate

Physical characteristics

alpine Cold deep snow, numerous layers, some wind affected, low density

prairie Thin, moderately cold snowpack, wind slab

ephemeral A thin, extremely warm snow (0~50cm deep). Melting is common. Short life

Maritime Warm deep snow, coarse grain, occasional melt

Taiga Moderately deep cold snow (low density). Depth hoar common

Tundra A thin, cold, wind-blown snow. Melting is rare. Depth hoar overlain by wind slab

snow classification system developed by Sturm et al. (1995)