Remote Sensing Principles Relevant to Sea Ice - Sea Ice: Physics and Remote Sensing - page 333

Am5h-o-Arc07-261-261 Qu5h-o-Arc07-261-261

2007-9-18

AMSR HIRZ QuickScot

2007-9-18

QuikSCAT σ o hh AMSR-E Tb 36 h

300 K -5 dB

-10 dB

250 K

-15 dB

200 K

QuikScot L1B
hh
18/9/2007

AMSR-E
36.5 GHz-H
18/9/2007

-20 dB

150 K

-25 dB

100 K -30 dB

Surface Temperature

2007-09-18

75N

256K

258K

80N

260K

85N

262K

264K

266K

268K

85N

270K

272K

80N

274K

75N

276K

278K
280K

70N

Surface temperature

Figure 7.46 Daily average mosaics of AMSR‐E T b ,36 h and QuikSCAT over the Arctic basin for 18 September
2007 (top panel) and the coincident surface temperature map obtained using the weather model GEM used by
the Canadian Meteorological Center (bottom). Anomalies in the remote sensing signatures of the MY ice image
are marked by the solid arrows and they correspond to higher air temperature in the temperature map. The dotted
arrow indicates an area of very cold temperature (below −20 °C). [ Shokr and Agnew , 2013]. (For color detail,
please see color plate section).

Since wet snow is a lossy medium to microwave fre-
quencies, the dielectric constant increases (both its real
and imaginary parts) as wetness increases. For radar
observations, the increase of the real part (permittivity)

causes the surface scattering to increase while the increase
in the imaginary part (loss) causes the volume scattering
to decrease due to increasing absorption (details on the
permittivity and loss are given in section 3.6). The