Transcript NASA GISS John Mioduszewski Department of Geography Sea ice monitoring is critical to the ability to assess climate change in the Arctic, where.

NASA GISS
John Mioduszewski
Department of Geography
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 sets
www.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 http://www.fas.org/irp/imint/docs/rst/Sect14/originals/Fig14_21.jpg
with SMMR

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: 2002present
 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 NASA
http://nsidc.org/data/docs/daac/images/amsrecraft1.gif



Has a linear relationship with emissivity,
approximated in the Raleigh-Jean Law
Tb = εT
Tb 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)


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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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Passive Microwave, A New Data Set. Proc. Monitoring an Evolving Cryosphere,
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Drobot, S. D., M. R. Anderson, 2000: Spaceborne Microwave Remote Sensing of Arctic
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http://nsidc.org/data/docs/daac/smmr_instrument.gd.html].
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