Geology Reference
In-Depth Information
Kern
[2001] mentioned also that in polar regions the pre-
cipitation was observed to occur at CLW >0.35 kg/m
2
.
However, due to scattering of the microwave signal off
precipitation particles, estimations of CLW tend to be
biased toward values above 0.35 kg/m
2
. The same refer-
ence presents a table of monthly averages of IWV, CLW,
and
V
in the Arctic and Antrarctic. The data are based on
retrievals of these parameters from SSM/I. In general,
scattering by precipitation particles (in liquid or solid
form) decreases
T
b
at the higher frequencies of passive
microwave while absorption and re-emission increases it
[
Fuhrhop and Simmer
, 1996]. The net effect is an increase
of
T
b
with IWV or CLW. Likewise, an increase in the
surface wind over ocean
V
causes roughening of the
water surface and an increase of
T
b
at both horizontal
and vertical polarizations. However, the increase in
T
b
from horizontal polarization occurs at a higher rate,
which causes the polarization difference (
T
b,v
−
T
b,h
) from
open water to decrease significantly with increasing wind
speed [
Fuhrhop and Simmer
, 1998]. This causes overesti-
mation of ice concentration in the presence of rough
open water (section 10.2.2). Ice, on the other hand, has
remarkably less polarization difference than the surround-
ing open water.
Upon estimating the required meteorological parame-
ters, a correction scheme can be applied to account for
the effects of those parameters on the observations. A
commonly used scheme involves using an empirical
equation to subtract the effects of IWV, CLW, and
V
from the observed brightness temperature. The equation
is developed by compiling a database of simulated obser-
vations using a radiative transfer model with different
inputs of IWV, CLW, and
V
. This approach was adopted
in
kern
[2004] where the MicroWave MODel (MWMOD)
[
Fuhrhop and Simmer
, 1998] was used to calculate simu-
lated brightness temperature for the operational passive
microwave frequencies. From the database a linear poly-
nomial regression was developed and used to determine
corrected values of the brightness temperature. The cor-
rection for IWV and CLW is performed using a single
equation by subtracting the contributions of these two
parameters from the observed
T
b,p
for a given polarization
p
. If the footprint contains open water and ice, an initial
estimate of ice (or equivalently water) concentration
C
is
needed. The correction, denoted
T
b,p
‐corr‐WL
, is given by
(WL denotes correction for IWV and CLW):
brackets in the RHS is a fourth‐order polynomial (
i
=
j
= 4)
where the coefficients
a
ij
depend on the surface emissivity
p
. The latter varies with the wind speed if the correction
is made over open water. A lookup table of the coeffi-
cients, along with the open water emissivity variation
with wind speed
p
(
V
), are given in
Kern
[2001]. Different
sets of coefficients are obtained for the ice and water sur-
faces. The correction for the ice and OW in a heterogene-
ous footprint is weighed by their concentrations
C
k
in the
above equation. Correction for the influence of wind
speed over ocean surface is carried out using the follow-
ing equation. The parameter at the LHS is the brightness
temperature corrected for the three factors of integrated
water vapor, cloud liquid water contents, and surface
wind over ocean; denoted by the letters WLV:
4
i
T
T CbV
(7.104)
bp
,
corr WLV
bp
,
corrWL W
i
i
0
where the coefficients
b
i
are also generated from regres-
sion of data obtained using MWMOD and provided in
Kern
[2001];
C
OW
is the concentration of OW. An initial
concentration should be assumed.
The increase of
T
b
caused by IWV and CLW becomes
more significant at higher frequencies and over open
water areas (since they have more clouds and water
vapor). Therefore, it is important to correct the high‐fre-
quency observations over open water and a marginal ice
zone. Other atmospheric factors that affect
T
b
include
scattering by drizzle, raindrops, and frozen hydrometeors.
They become increasingly important at frequencies
greater than 30 GHz [
Gasiewski
, 1993]. They all cause a
decrease of brightness temperature, but, on the other
hand, emission from raindrops also increases it. The net
effect of these two opposing mechanisms depends not
only on the frequency of the recorded microwave signal
but also on its polarization. Although the effect has not
been modeled and fully described,
Shokr et al.
[2009]
found experimentally that rain over open water causes an
increase of
T
b
particularly from the horizontal polariza-
tion and higher frequency channels. Their data were
obtained from measurements of microwave emission
from laboratory‐grown sea ice in an outdoor tank using a
surface‐based radiometer. This depolarization of the
wave causes open water to be misidentified as sea ice by
most ice concentration algorithms (Figure 8.22).
7.7.2. Seawater
n
4
i
i
T
T
C
(
a
(
(
V
)
)(
IWVCLW
)(
)
bp
,
corr WL
bp
,
k
ij
p
Understanding radiometric properties and processes of
seawater is crucial not only for developing a reliable
ice‐water discrimination capability but also for estimating
sea ice concentration from remote sensing observations.
It is crucial because of two facts: (1) the radiometric
signatures of sea ice and seawater overlap under certain
k
1
ij
,
0
k
(7.103)
Here the subscript
k
refers to each one of the two
surface types (i.e., ice and open water surfaces),
n
is the
number of surfaces (=2). The term between the square
