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) 
CANADA 
Figure 1 : 
Field Validation Site for the Lancaster Sound SIMS 
project. Intensive and extensive sample areas are for 
the 1990 field season. 
3. REMOTE SENSING OF PHYSICAL PROCESSES FOR GLOBAL 
CHANGE 
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, 
1981). 
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 
below. 
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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