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The influence of spatial variability of polar firn on microwave emission. 1 WSL-Institute for Snow- und Avalanche Research SLF, Davos, CH. Martin Proksch 1 , Henning Löwe 1 , Stefanie Weissbach 2 , Martin Schneebeli 1. 2 Alfred-Wegener-Institute for Polar and Marine Research, Germany.

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the influence of spatial variability of polar firn on microwave emission

The influence of spatial variability of polar firn on microwave emission

  • 1 WSL-Institute for Snow- und Avalanche Research SLF, Davos, CH

Martin Proksch1, Henning Löwe1, Stefanie Weissbach2, Martin Schneebeli1

  • 2Alfred-Wegener-Institute for Polar and Marine Research, Germany
  • Microsnow Reading, 6. – 8. August 2014
outline
Outline
  • Motivation
  • Instrument and measurements
  • Simulations and Results
    • Spatial variability
    • Layer thickness
  • Conclusions

WSL-Institut für Schnee- und Lawinenforschung SLF

1 motivation i
1. Motivation I
  • Microwave observations are essential in polar regions (think about polar night!)
  • To understand the microwave signatures of polar firn, in-situ data is necessary, but traditional snow measurements are:
    • limited in spatial resolution
    • limited by extensive measurement times
    • constrained due to harsh polar environments
    • subjective (variability between observers)
  • Desirable: fast derivation of the relevant objective parameters with sufficient resolution (e.g. Correlation length and density to model microwave emission)

WSL-Institut für Schnee- und Lawinenforschung SLF

1 motivation ii
1. Motivation II
  • Where to measure (Sampling design)?
  • Answer requires knowledge about snow variability!

Pic: Martin Schneebeli

WSL-Institut für Schnee- und Lawinenforschung SLF

2 1 instrument snowmicropen smp
2.1 Instrument: SnowMicroPen (SMP)
  • Specifications:
    • High resolution: vertical ~1mm
    • Fast: 1 m profile ~ 1 minute
    • Portable

=> Ideal for spatial variability

  • Output:
    • Density, SSA and Correlation length (Proksch et al, submitted)
    • 2D stratigraphy from transects
2 2 measurements at kohnen station density
2.2 Measurements at Kohnen Station: Density

92 SMP profiles with interval 0.5 m -> 45m transect:

WSL-Institut für Schnee- und Lawinenforschung SLF

2 2 measurements at kohnen station correlation length l ex
2.2 Measurements at Kohnen Station: Correlation length lex

92 SMP profiles with interval 0.5 m -> 45m transect:

WSL-Institut für Schnee- und Lawinenforschung SLF

2 2 measurements at kohnen station specific surface area ssa
2.2 Measurements at Kohnen Station: specific surface area SSA

92 SMP profiles with interval 0.5 m -> 45m transect:

WSL-Institut für Schnee- und Lawinenforschung SLF

3 1 memls simulations
3.1 MEMLS simulations

MEMLS: Microwave Emission Model ofLayeredSnowpacks, Wiesmann andMätzler, 1999.

-> withImproved Born Approximation, Mätzler 1998.

MEMLS input:

  • 1cm layerthickness in top mostmeter
  • lex: SMP (no «grainsize» scaling)
  • Density: SMP
  • Snow temperatureprofile
  • Tsky: 0K
  • Snow-groundreflectivity: 0
  • 20m deepprofile, linearlyincreasing

WSL-Institut für Schnee- und Lawinenforschung SLF

3 2 results brightness temperatures
3.2 Results: Brightnesstemperatures

σ Tb

Tb

WSL-Institut für Schnee- und Lawinenforschung SLF

3 2 results brightness temperatures1
3.2 Results: Brightnesstemperatures

σ Tb

Tb

WSL-Institut für Schnee- und Lawinenforschung SLF

3 2 results brightness temperatures2
3.2 Results: Brightnesstemperatures
  • One MEMLS run per SMP profile, total N = 92
  • σ(Tb, 36GHz) = 16.6 K

σ Tb

Tb

WSL-Institut für Schnee- und Lawinenforschung SLF

WSL-Institut für Schnee- und Lawinenforschung SLF

14

3 2 results brightness temperatures3
3.2 Results: Brightnesstemperatures
  • One MEMLS run per SMP profile, total N = 92
  • σ(Tb, 36GHz) = 16.6 K
  • Todecreaseσ, wehavetoincreasethenumberofmeasurements N:
  • σ(Tb) = 16 K
  • for N=92
  • σ(Tb) = 8K
  • for N = 368
  • σ(Tb) = 2K
  • for N = 2944

σ Tb

Tb

WSL-Institut für Schnee- und Lawinenforschung SLF

3 2 results summit
3.2 Results: Summit

Standard deviations:

  • T19GHz, V-pol = 13.9 K
  • T36GHz, V-pol = 24.1 K
  • T89GHz, V-pol = 23.5 K

Constant Density: Constant corr. length

  • T19GHz, V-pol = 13.5 K T19GHz, V-pol = 3.7 K T36GHz, V-pol = 26.1 K T36GHz, V-pol = 3.8 K T89GHz, V-pol = 27.8 K T89GHz, V-pol = 7.0 K
3 2 results point barnola
3.2 Results: Point Barnola

Standard deviations:

  • T19GHz, V-pol = 3.3 K
  • T36GHz, V-pol = 11.0 K
  • T89GHz, V-pol = 21.2 K

Constant Density: Constant corr. length

  • T19GHz, V-pol = 4.5 K T19GHz, V-pol = 1.2 K T36GHz, V-pol = 12.8 K T36GHz, V-pol = 1.5 K T89GHz, V-pol = 23.7 K T89GHz, V-pol = 4.3 K

WSL-Institut für Schnee- und Lawinenforschung SLF

3 3 results spatial correlations
3.3 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF

3 3 results spatial correlations1
3.3 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF

3 3 results spatial correlations2
3.3 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF

3 3 results spatial correlations3
3.3 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF

3 3 results spatial correlations4
3.3 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF

3 3 results spatial correlations5
3.3 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF

3 3 results spatial correlations6
3.3 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF

3 4 results layer thickness
3.4 Results: Layer thickness
  • 20m deep profile:
    • First meter SMP measurement
    • 2 – 20 meter: linear increasing, with random noise added.

20 cm

3 cm

WSL-Institut für Schnee- und Lawinenforschung SLF

3 4 results effect of vertical averaging
3.4 Results: Effectofverticalaveraging

Averaging to 3cm layer thickness leads to significant loss of density variations!

WSL-Institut für Schnee- und Lawinenforschung SLF

4 summary and conclusions
4. Summary and Conclusions
  • The SnowMicroPen allows the measurement of full-meter profiles in less than one minute
  • Transects reveals the 2D quantitative stratigraphy of polar firn
  • One single profile is not enough – statistically based sampling design?
  • Layer thickness critical
  • Outlook: optimize deep profiles to match Satellite data

WSL-Institut für Schnee- und Lawinenforschung SLF

slide26
s

Thankyou!

  • Thanksto:
  • Christian Mätzler
  • Ludovic Brucker

WSL-Institut für Schnee- und Lawinenforschung SLF

3 5 results measurement accuracy
3.5 Results: Measurement accuracy
  • Meas. accuracy in top most meter
  • To model Tb within 1K

WSL-Institut für Schnee- und Lawinenforschung SLF

outlook
Outlook
  • Compareto SSMI

WSL Institute for Snow and Avalanche Research SLF

to do
To do:
  • Spat var - forotherstations
  • Layer thickness
  • Measaccuracy

WSL Institute for Snow and Avalanche Research SLF

3 2 results spatial correlations
3.2 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF

3 2 results spatial correlations1
3.2 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF

3 2 results spatial correlations2
3.2 Results: Spatialcorrelations

WSL-Institut für Schnee- und Lawinenforschung SLF