Geoscience Reference
In-Depth Information
Table
4
shows that multiyear ice retrieval is most sensitive to the tie points at
19 GHz V channel and least sensitive to those at 19 GHz H channel. In the NASA
Team algorithm, 19 GHz H is only used in PR. As mentioned above, multiyear ice
concentration retrieval is mainly determined by the gradient ratio (GR) in the GR/
PR space. The low sensitivity of horizontal channel (shown in Table
4
) con
rms the
weak in
rst
year ice are more sensitive than those of open water as expected. To sum up, tie
points of multiyear ice and
fl
uence of polarization ratio. Besides, tie points of multiyear ice and
first year ice at 19 GHz V are the most sensitive thus
need to be determined as precisely as possible if the dynamic NASA Team algo-
rithm is used.
To conclude, dynamic tie points improve the retrieval of multiyear ice con-
centration with the NASA Team algorithm by taking the temporal variation of
brightness temperature into account. However, because of the high sensitivity of tie
points and the impact of spatial variation of brightness temperature, much further
work could be done to further improve the retrieval of multiyear ice with the NASA
Team algorithm. For example, we could de
ne three regions for deriving tie points
of open water,
first year and multiyear ice instead of two (shown in Fig.
1
). Fur-
thermore, better weather
filters could improve the retrieval as well.
Acknowledgements Financial support of the China Scholarship Council is gratefully acknowl-
edged. We also thank the reviewers for their valuable comments and suggestions.
References
Comiso JC (2012) Large decadal decline of the arctic multiyear ice cover. J Clim 25
Comiso JC, Cavalieri DJ, Parkinson CL, Gloersen P (1997) Passive microwave algorithms for sea
ice concentration: a comparison of two techniques. Remote Sens Environ 60:357
-
384
Drobot SD, Anderson MR (2001) An improved method for determining snowmelt onset dates over
Arctic sea ice using scanning multichannel microwave radiometer and special sensor
microwave/imager data. J Geophy Res Atmos (1984
24049
Heygster G, Huntemann M, Ivanova N, Saldo R, Pedersen LT (2014) Response of passive
microwave sea ice concentration algorithms to thin ice. In: 2014 IEEE international on
geoscience and remote sensing symposium (IGARSS), pp. 3618
2012) 106:24033
-
-
3621
-
Kwok R (2009) Out
fl
ow of Arctic Ocean sea ice into the Greenland and Barents Seas: 1979
2007.
-
2457
Lomax AS, Lubin D, Whritner RH (1995) The potential for interpreting total and multiyear ice
concentrations in SSM/I 85.5 GHz imagery. Remote Sens Environ 54:13
J Clim 22:2438
-
26
Nghiem S, Rigor I, Perovich D, Clemente
‐
Col
ó
n P, Weatherly J, Neumann G (2007) Rapid
reduction of Arctic perennial sea ice. Geophy Res Lett 34
Perovich DK, Richter-Menge JA (2009) Loss of sea ice in the arctic. Annu Rev Mar Sci
1:417
-
441
Serreze MC, Francis JA (2006) The Arctic ampli
cation debate. Clim Change 76:241
-
264
Steffen K, Schweiger A (1991) NASA team algorithm for sea ice concentration retrieval from
defense meteorological satellite program special sensor microwave imager: comparison with
Landsat satellite imagery. J Geophys Res Oceans (1978
-
21987
Stroeve J, Serreze M, Fetterer F, Arbetter T, Meier W, Maslanik J, Knowles K (2005) Tracking the
Arctic
2012) 96:21971
-
-
'
s shrinking ice cover: another extreme September minimum in 2004. Geophys Res Lett 32
Search WWH ::
Custom Search