Microwave remote sensing of sea ice in the AIDJEX Main Experiment

Campbell, W. J.; Wayenberg, J.; Ramseyer, J. B.; Ramseier, R. O.; Vant, M.R.; Weaver, R.; Redmond, A.; Arsenaul, L.; Gloersen, P.; Zwally, H. Jay; Wilheit, T. T.; Chang, Tzu‐Ching; Hall, Dorothy K.; Gray, L. H.; Meeks, D C; Bryan, Mark L.; Barath, F. T.; Elachi, C.; Leberl, Franz; Farr, Tom G.

doi:10.1007/bf00913880

Cited by 51 publications

(14 citation statements)

References 13 publications

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“…This all time, all weather, highresolution capability (up to 3 X 3 m: or, more commonly, 25 X 25 m :) makes radar a remote-sensing tool well suited to providing data on sea ice. A review of the qualitative analysis of Aidjex radar data was given by Campbell et al [1978], confirming and extending experiences of numerous earlier radar sea ice studies (Anderson [1966], U.S. Coast Guard [1972], Johnson and Farmer [1971a], Parashar [1974Parashar [ , 1976, Dunbar [1975], Morra and de Loor [1976], and Bryan [1976], among others).…”

Section: Introductionsupporting

confidence: 70%

Mapping of sea ice and measurement of its drift using aircraft synthetic aperture radar images

et al. 1979

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Side-looking radar images of Arctic sea ice were obtained as part of the Arctic Ice Dynamics Joint Experiment. Repetitive coverages of a test site in the Arctic were used to measure sea ice drift, employing single images and blocks of overlappin. g radar image strips; the images were used in conjunction with data from the aircraft inertial navigatio. n and altimeter. Also, independently measured, accurate positions of a number of ground control points were available. Initial tests of the method were carried out with repeated coverages of a land area on the Alaska coast (Prudhoe). Absolute accuracies achieved were essentially limited by the accuracy of the inertial navigation data. Errors of drift measurements were found to be about +2.5 km. Relative accuracy is higher; its limits are set by the radar image geometry and the definition of identical features in sequential images. The drift of adjacent ice features with respect to one another could be determined with errors of less than +0.2 km.

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Section: Introductionsupporting

confidence: 70%

Mapping of sea ice and measurement of its drift using aircraft synthetic aperture radar images

et al. 1979

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“…In general, the low‐frequency channels will respond more to changes in the sea ice, whereas the 85 GHz channels barely penetrate the typical snow cover. A homogeneous snow cover tends to decrease polarization and raises the emissivity [ Campbell et al , 1978] and constitutes the most important part of the typical winter first year ice signature variability. Although it has not been reported, this mechanism can be conceived to modify the sensitivity to thin ice, as at higher observing frequencies, a thinner snow layer may mask the signal from the underlying thin ice.…”

Section: Ssm/i Ice Concentration Algorithmsmentioning

confidence: 99%

Intercomparison of passive microwave sea ice concentration retrievals over the high‐concentration Arctic sea ice

et al. 2007

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[1] Measurements of sea ice concentration from the Special Sensor Microwave Imager (SSM/I) using seven different algorithms are compared to ship observations, sea ice divergence estimates from the Radarsat Geophysical Processor System, and ice and water surface type classification of 59 wide-swath synthetic aperture radar (SAR) scenes. The analysis is confined to the high-concentration Arctic sea ice, where the ice cover is near 100%. During winter the results indicate that the variability of the SSM/I concentration estimates is larger than the true variability of ice concentration. Results from a trusted subset of the SAR scenes across the central Arctic allow the separation of the ice concentration uncertainty due to emissivity variations and sensor noise from other error sources during the winter of [2003][2004]. Depending on the algorithm, error standard deviations from 2.5 to 5.0% are found with sensor noise between 1.3 and 1.8%. This is in accord with variability estimated from analysis of SSM/I time series. Algorithms, which primarily use 85 GHz information, consistently give the best agreement with both SAR ice concentrations and ship observations. Although the 85 GHz information is more sensitive to atmospheric influences, it was found that the atmospheric contribution is secondary to the influence of the surface emissivity variability. Analysis of the entire SSM/I time series shows that there are significant differences in trend between sea ice extent and area, using different algorithms. This indicates that long-term trends in surface and atmospheric properties, unrelated to sea ice concentration, influence the computed trends.

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“…The salinity of the ice has been studied by Cox and Weeks [1974] and by Campbell et al [1978] in the Arctic and by Gow et al [1982] in the Antarctic. In the Arctic, a significant difference in the salinity profiles of first-year and multiyear ice (or ice that has survived at least one summer) is commonly observed, with the latter being substantially less saline in the freeboard layer than the former.…”

Section: Physical and Radiative Properties Of Sea Icementioning

confidence: 99%

Sea ice effective microwave emissivities from satellite passive microwave and infrared observations

Comiso¹

1983

J. Geophys. Res.

122

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Microwave sea ice emissivities are investigated on a global scale by using near‐simultaneous images from the temperature‐humidity infrared radiometer (THIR) and the dual‐polarization scanning multichannel microwave radiometer (SMMR), both onboard the Nimbus 7 satellite. The emissivities in several study areas in the Arctic region are observed to be approximately constant during a 9‐month period within the fall, winter, and spring months for both first‐year and multiyear ice, with a standard deviation of about 3%. During the onset of summer, when the snow cover starts to melt, emissivity increases of about 30% are observed at 37 GHz for multiyear ice, with the effect decreasing to less than 5% at the 6.6‐GHz channels. Multichannel cluster analysis over very large study areas during winter shows considerable variability in emissivities of well‐defined clusters of consolidated ice at 37 GHz and about one third as much at 18 GHz. Some nonlinearities in the functional relationship of the emissivities in the consolidated ice regions between first‐year and multiyear ice are also evident, especially when data from one frequency is plotted against that of another. However, the cluster analysis technique separates the various emissivity data points into distinct clusters corresponding to radiometrically different ice types. If the variability within each cluster is quantified and taken into account by using multispectral analysis, in addition to improving the capability of classifying ice by age, information about ice thickness and surface characteristics might also be obtainable.

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Microwave remote sensing of sea ice in the AIDJEX Main Experiment

Cited by 51 publications

References 13 publications

Mapping of sea ice and measurement of its drift using aircraft synthetic aperture radar images

Mapping of sea ice and measurement of its drift using aircraft synthetic aperture radar images

Intercomparison of passive microwave sea ice concentration retrievals over the high‐concentration Arctic sea ice

Sea ice effective microwave emissivities from satellite passive microwave and infrared observations

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