Modeled
10
8
6
4
2
Observed
0
0
40
80
120
160
200
240
Observation Sequence
Figure 9. Temporal variability of 240 consecutive 3-hour observations of
total cloud amount in November 1982 on North Pole 25 and our modeled
total cloud amount based on eq 4.
Naturally, using this algorithm to estimate total cloud amount has some limita-
tions, since the observed cloud amount can result from any type of cloud from stra-
tus to cirrus. Since each cloud type influences the radiation and temperature
regime in the lower atmosphere differently, a prediction scheme based on only a
single parameter, surface-layer temperature, must ultimately be an oversimplifi-
cation. Nonstationarity in the physical processes in the lower atmosphere--caused,
for example, by advecting and adjusting air masses or by the slow evolution of
the atmospheric boundary layer during very stable stratification--can also distort
the results. All of these problems (as well as some imperfect approximations in eq
4) should improve, however, with further work on this algorithm. In light of the
results shown in Figures 8 and 9, we think eq 4 presents interesting prospects as
an indirect method for estimating cloud amount in the polar regions, especially
during the polar night. With the development of the International Arctic Buoy Pro-
gram (IABP), in particular, and the consequent availability of simultaneously mea-
sured surface-layer temperatures from various parts of the Arctic Basin, our method
could provide estimates of cloud amounts with coverage comparable to satellites.
PARAMETERIZING THE LONGWAVE RADIATION
BALANCE IN SEA ICE MODELS
Longwave radiation is one of the key processes determining the rate at which
sea ice forms in the polar regions in winter (Maykut 1986, Makshtas 1991a). This
fact has led to numerous parameterizations for the longwave radiation balance of
snow-covered sea ice. These have, in turn, been used to study the climatic signifi-
cance of processes affecting ocean-atmosphere interaction in high latitudes, espe-
cially with coupled ocean-ice models in which the characteristics of the atmosphere
are external parameters (e.g., Parkinson and Washington 1979, Hibler 1979).
13
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