Assessing Glacier Volume & Mass ∆

Active vs Passive

Active methods
i.e. radar, laser

Instrument beams radiation down to surface from satellite

Passive RS

Instrument picks up reflected solar radiation

Type of
Mass Lost?

Mass lost - snow or firn or ice ? (thus what's relavent density?)

= Important consideration esp wrt potential sealevel ∆

Glacier properties

Thickness: i.e. height, surface elevation

Length/area/extent

Intensity Spectra

Amount of each wavelength of radiation received at Earth surface from the sun

Reflectance Spectra

Ratio of given wavelength of radiation
received (incident) vs reflected

Allows albedo calculation

Albedo

= % incident light at given wavelength reflected

Electromagnetic radiation

Radiation from sun comprises components of a range of wavelengths (a spectrum)

Different land types have different reflectance spectra

Light from sun = shortwave radiation

Glacier Height ∆ Field Msmt

Field msmt = v labour intensive

Methods (on individual glaciers)

  • Snow density msmt
  • Snow/ice stake readings

Only 37 glaciers have a 40 yr time series measured

Easier alternative = remote sensing elevation ∆

Volume
∆ Msmt

Volume ∆ attributed to surface elevation ∆

Convert elevation ∆ to mass by multiplying by density

∴ Must assign density to lost material (snow/firn/ice?)

Glacier Length ∆ Field Msmt

Glacier terminus position

= monitored routinely on ~ 500 glaciers (of 100,000s)

Long record (data begins late 1800s)

Methods:

  • Aerial photography
  • Satellite imaging
  • Maps
  • Photos / paintings
  • Dated moraines

Band
Analysis

What?

LANDSAT - satellite imagery

Frequency bands extracted from imagery

Each band receives unique wavelength range of electro mag rad

∴ Chosen radiation wavelength/intensities
= returned with photo analysis

Using Bands to Extract Snow/Ice/Firn

Locating ice = problematic at times

Algorithms in Landsat can give false appearance of natural colour

Scientific / robust method
= use reflectance bands i.e. NSDI

Normalised Snow Difference Index

NDSI = Normalised difference of 2 bands

one in visible range

one in near-infrared or shortwave

Used to map snow / ice

1. Subtract band 5 image from band 2 pixel by pixel i.e. (Band2-Band5)

2. Normalise for limited light/effect of dust
i.e. divide by sum of 2 bands

NDSI = (band2-band5) / (band2+band5)

Benefits

Ads distinction between snow + cloud/veg

Snow is:

  • highly reflective in visible
  • highly absorptive in IR / shortwave

Whereas cloud remains highly reflective in both parts of spectrum

Mass ∆

Glacier dimension ∆ --> Mass loss

Glaciers can ∆ mass via both surface area & thickness ∆

Mass Loss Quantification

Mass = volume x density, thus need to know:

  • Volume ∆
  • Density of material lost

Ice density ~ 900 kg/m3

Snow/firn ~ 600 g/m3

GRACE

Gravity Recover & Climate Experiment

Measures variations in Earth's gravity field over time

Resolution: coarse (~300km)

Other mass ∆s also affect record

Limited to major ice sheets