John MioduszewskiDepartment of Geography

NASA GISS

Sea ice monitoring is critical to the ability to assess climate change in the Arctic, where it is changing most rapidly. Arctic Sea ice is declining at a rate of almost 6%/decade (NSIDC) which greatly impacts surface heat flux, large-scale energy transport, and ecological and human interests. Additionally, sea ice dynamics contribute to a disproportional amount of uncertainty in IPCC climate projections. Passive microwave sensing of sea ice is the primary method by which sea ice data is acquired. This is due to the long record of observations as well as this method’s ability to penetrate cloud cover and darkness to provide daily data. Passive microwave sensors detect radiation emitted from the surface depending on the emissivity properties of the surface. This radiation is converted to a brightness temperature, Tb, which is used to differentiate among open water and ice, or even different types of ice. Multiple channels and polarization allow for detection of a variety of ice characteristics while simultaneously minimizing sources of error. Integration with visible imagery and active sensing is advised to best take advantage of the strengths of each technique.

Concentration and extent Location of small-scale features (e.g. ice

leads) These have a major impact on latent and sensible

heat fluxes Ice type (first year vs. multiyear), thickness,

and surface roughness Snow on ice

Reduces surface roughness, acts as a thermal blanket, facilitates the transfer of brine, and can even submerge or flood the surface of thin ice

Movement Divergence is conducive to polynya formation,

convergence forms pressure ridges, net transport is needed for heat flux calculations regionally

Electrically Scanning Microwave Radiometer (ESMR): 1972-1977 Made a single

frequency measurement (19GHZ) that discriminated between ice and open water

Orbited on Nimbus-5 Not typically used in

data setswww.icsu-scope.org

Scanning Multichannel Microwave Radiometer (SMMR):1978-1987 on Nimbus 7 5 different bands

allowed for mapping of ice concentration and distinction between first year and multiyear ice

For practical purposes, concentration and ice extent records began with SMMR

http://www.fas.org/irp/imint/docs/rst/Sect14/originals/Fig14_21.jpg

Special Sensor Microwave Imager (SSM/I): 1987-present 25km spatial resolution

(12.5km in the high frequency band)

onboard Defense Meteorological Satellite Program (DMSP) satellites

Currently onboard F15 and F17

http://gpcp-pspdc.gmu.edu/images/SSMI.pic.gif

Advanced Microwave Scanning Radiometer (AMSR) on Aqua: 2002-present 12 channels at 6

frequencies Resolution improves

with frequency (from 56 to 5.4 km)

Beam width from 2.2° to 0.18°

Oversight by NASAhttp://nsidc.org/data/docs/daac/images/amsrecraft1.gif

Has a linear relationship with emissivity, approximated in the Raleigh-Jean Law

Tb = εTTb is impacted by ice and surface

characteristics e.g., decreased by brine drainage and melt

ponds/drainage Increased by snow loading and other

properties of first-year ice

Lλ= (2kcT)/λ4

Useful way to describe the relationship between emission and wavelength when λ >> λmax (i.e. microwave)

Since very little radiation is emitted in the microwave by terrestrial bodies, Planck’s Law is difficult to apply This is a good approximation for λ >

0.15 cm Also why resolution is so poor: must

sample a large area to register an emissivity

Resolution improves at higher frequencies (smaller λ’s) because more radiation is emitted by ice at these λ’s; don’t need to sample such a large area

http://www.mikroninfrared.com/images/fig4radintensity.gif

Microwave emissivity is a function of dielectric constant This is mostly dependent on temperature and

moisture characteristics Most materials have a dielectric constant

between 1 and 4 (ice is 3.2), but water’s is 80▪ This makes passive microwave sensing extremely

good for detection of melt onset, but creates problems afterwards as water and ice exist together

▪ Snowpack also complicates this, scattering the ice’s emitted radiance

Emissivity of everything in the direction of the ice is measured, which adds error

Emissivity also depends on the frequency measured

https://bora.uib.no/bitstream/1956/1135/1/MRS_Chapter8-proof.pdf

As with many imaging sensors, radiation from the atmosphere, reflected from the surface, transmitted through the surface, etc. is all measured in addition to what is desired

Microwave emissivity is a function of dielectric constant Most materials have a dielectric constant

between 1 and 4 (ice is 3.2), but water’s is 80▪ This makes passive sensing extremely good for the

melt season, including detection of melt onset▪ Snowpack complicates this though, scattering the

ice’s emitted radiance Emissivity of everything in the direction

of the ice is measured, which adds error Emissivity also depends on the

frequency measured

Lower frequencies (19-22 GHZ) are best for determining melt onset

Spatial resolution is better at higher frequencies

Cloud and atmospheric effects reduced below about 50 GHz

Each band has its strengths and weaknesses

http://topex.ucsd.edu/rs/Lec11.pdf

http://topex.ucsd.edu/rs/Lec11.pdf

The seasonal variation in microwave signature also depends on whether first year or multiyear ice is being detected

Snow on ice and melt ponds are the biggest Inaccurate during the melt season due to

meltwater-related emission and scattering (up to 50% error) (Drobot and Anderson 2000)

Different layers of snow and ice cause different dielectric signals

Different frequencies are better at detecting different properties

Very poor spatial resolution Difficult to integrate with higher resolution data Difficult to locate smaller scale phenomena such

as ice movement and lead structure

A relatively long, continuous record of sea ice

Daily data regardless of cloud cover or time of day

(From NSIDC)

http://nsidc.org/images/arcticseaicenews/20091005_Figure3.png

Passive microwave sensing has allowed the remarkable decline in Arctic sea ice to be documented

Passive microwave sensing has allowed us to monitor sea ice for over 3 decades and document the Arctic decline Remote sensing is the only way this could

be done in the vast, harsh polar environments

Best way to combat the shortcomings are to use multiple sensors to synthesize their strengths

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Sandven, S. and O.M. Johannesen, 2006: “Sea Ice Monitoring in Remote Sensing” in Manual of Remote Sensing: Remote Sensing of the Marine Environment. American Society for Photogrammetry & Remote Sensing, pp 241-243.

Sandwell, D. and H. Fricker, 2009: Satellite Remote Sensing, Chapter 11. [Available online at http://topex.ucsd.edu/rs/Lec11.pdf].

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