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Proceedings of the Symposium on Global and Environmental Monitoring

Table 1:
Earth Observations Laboratory, Institute for Space and Terrestrial
Science (EOL/ISTS)
York University Microwave Group (York University)
Ice Centre, Environment Canada (ICEC)
Atmospheric Environment Service, Environment Canada (AES)
Canada Centre for Remote Sensing (CCRS)
Department of Fisheries and Oceans (DFO)
Norland Science, Ottawa, Ontario
Jet Propulsion Laboratory, Pasadena, California (JPL)
Figure 1 :
Field Validation Site for the Lancaster Sound SIMS
project. Intensive and extensive sample areas are for
the 1990 field season.
A considerable amount of energy has been expended in developing
methodologies by which remote sensing imagery can be utilized to
improve our understanding of the physical processes occurring
within the atmosphere-cyrosphere-hydosphere regime. Major
projects such as AIDJEX (Arctic Ice Dynamics Joint Experiment),
BESEX (Bering Sea Experiment), LIMEX (Labrador Ice Margin
Experiment), MIZEX (Marginal Ice Zone Experiment), and
NORSEX (Norwegian Remote Sensing Experiments) have added
considerably to our understanding of physical processes inherent in
the hydrosphere-cryosphere-atmosphere system. These projects have
also been particularly useful in developing remote sensing
methodologies which can be utilized to parameterize the important
variables for subsequent modelling and monitoring research. The
SIMS project will build on these past achievements to enhance our
understanding of the physical processes and to develop
methodologies by which remote sensing data can be used to measure
climate state variables.
Within SIMS we plan to utilize information from remote
measurements of reflected and emitted components of the
electromagnetic spectrum. Visual wavelength data will provide site
specific measurements of visual wavelength reflected components.
Coupled with in situ measurements, these data can be linked to
surface radiation parameters required for determination of regional
radiation budget calculations. Thermal wavelength data will provide
site specific measurements of the thermodynamic properties of
various ice surfaces. Coupled with in situ measurements, these data
can be linked to the longwave components of the net radiation
budget calculations. Finally, SAR imagery will provide surface
structure information. Coupled with in situ surface radiative and
thermodynamic properties this structural information will allow us
to develop proxy indicators by which we can infer specific radiative
properties of the various ice surfaces present in our study area, and
various cloud cover conditions.
Breaks in the sea ice insulating area (polynyas, leads, cracks) create
areas of enhanced turbulent heat flux. These areas account for only
a small portion of the surface area of the Arctic yet may contribute
significantly to the total turbulent heat fluxes in the floating ice
regime (Maykut 1982). Therefore, sea ice is the most significant
surface parameter influencing atmosphere-surface interactions and
polar ocean heat fluxes (Crane, 1981). Seasonal or interannual
changes in ice extent may have substantial energy budget
implications (Carleton, 1981).
Due to differing heat exchanges between atmosphere-ice or
atmosphere-open water regimes, it may be expected that variations
in the distribution of ice/water surfaces will affect diabatic heating
and regional synoptic activity within the atmosphere. Thus, when
the atmosphere-cryosphere-hydrosphere system is considered as a
whole, the most significant influence on atmosphere-surface
interactions is the relative distribution of ice/water surfaces (Crane,
Remote sensing at thermal infrared wavelengths (-8.0-11.0 pm) can
provide information on the surface temperature of sea ice (Steffen
and Lewis, 1988) and can be used to monitor snow surface
temperature throughout the snow melt period (Barnes, 1981; Foster
et al„ 1987) - a period important in energy balance studies (Foster
el al., 1987). Thermal imagery is also commonly used for small-
scale studies of ice extent, ice movement, and can be used for a
relative assessment of ice thickness (up to about 1 metre) (Barnes et
al., 1974; Dey, 1980; Poulin, 1975; Weeks, 1981). Thermal
infrared data have not been used extensively in the calculation of
radiative and sensible heat fluxes (Carsey and Zwally, 1986).
SAR can be used to parameterize information on ice thickness as a
function of ice type (i.e.; thin first-year, thick first-year, multi-year,
and rough multi-year). The all-weather day-night sensing
capabilities of this active microwave sensor makes it ideal for Arctic
applications. Upcoming orbital SARs (ERS-1, JERS-1, and
RADARSAT) will provide spatial samples of ice conditions at a
temporal resolution of daily to weekly for various parts of the
Canadian Arctic.
3.2 Albedo
The typical integrated albedo of a snow surface is on the order of
0.85, for water 0.05 to 0.10, and 0.6 (water-free) to 0.2 (water-
covered) for ice surfaces (Barry, 1983). Albedo also changes as a
function of ice type. The large water/ice albedo contrast exerts a
strong control on regional radiation and energy balances. Inherent
in a change of such surface covers is a positive feedback (Crane,
1981; Dickinson et al., 1987; Hansen et al. (1984); Hartmann
(1984); Kellogg (1983); Schneider and Dickinson, 1976; Robock,
1983). Large changes in surface albedo occur during the melt period
of the ice snow pack which also has significant implications
regarding the ice regime energy balance. The study of such melt
events and associated snowmelt-related albedo changes could provide
an index of interannual climate variability; subsequent understanding
of these variations could then be applied to climate models,
resulting in a more representative knowledge of Arctic spring
transition conditions (Anderson, 1987b).
Although not an exhaustive list, the physical processes which are
most suited to remote measurement include: thermodynamic
properties of sea ice; albedo; atmospheric drag; sea ice-cloud
interaction; and snow cover. The science issues and methodologies
appropriate for remote measurement of these variables are discussed
It should be possible to develop proxy indicators of albedo using
either surface structure information (from SAR) and/or thermal
wavelength imagery complementing the melt-event work already
done with the application of passive microwave data (e.g.,
Anderson, 1987a; Crane and Anderson, 1988; and Crane, 1989), and
visible data (e.g., Robinson et al., 1986, 1987). Preliminary
analysis of the applications of SAR imagery to development of
these proxy indicators was conducted during LIMEX'89 (De Abreu,
et al., 1989). This study found that a relationship exists between
surface albedo and ice type. Five types of ice were considered during
the LIMEX project: First-Year Ice; Black/Grey Nilas; Grease Ice;
Open Water and Frozen Brash. During the SIMS project a wider
range of ice types and snow covers will be studied.
3.1 Thermodynamic Properties of Sea Ice
The presence of sea ice restricts exchanges of heat (see Badgley,
1966; Gudmandsen, 1985; Maykut, 1978, 1982; Zwally et al.,
1983), mass, momentum, and chemical constituents between the
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