Agreement and Complementarity of Sea Ice Drift Products
Artikel i vetenskaplig tidskrift, 2016

Changes in Arctic sea ice have raised questions about changes in sea ice drift patterns. Reduced sea ice coverage may open up the Arctic to further exploration of maritime activities, particularly during the summer months. Given such changes, it is important to investigate differences between available sea ice drift products. Products based on synthetic aperture radar (SAR), radar scatterometer, and radiometer are compared for both motion speed and direction within this study. Two C-band SAR and one L-band SAR product are used in the comparison. Differences in temporal and spatial resolutions of the drift estimates spanning from July 2010 until June 2011 are investigated. High temporal and spatial resolution was proven useful to fully capture the sea ice drift in the Fram Strait. For summer coverage, SAR data are a prerequisite and L-band is desirable. The two C-band SAR products have a mean speed correlation of 0.90 and exhibit high conformity, despite being generated by separate processing methods. The L-band SAR product and the scatterometer and radiometer products are to a lower degree in agreement with each other and the C-band SAR products, which may be attributed to the products’ dependency on the temporal baseline. Depending on the choice of sensor or combination of sensors, the resulting 12-month mean drift varies between 0.09 and 0.12 m/s excluding L-band SAR. The latter shows a particularly low drift of 0.05 m/s, which we attribute to an over-representation of slow ice.

synthetic aperture radar (SAR)

Radiometry

time series

remote sensing

sea ice

Författare

Malin Johansson

Chalmers, Rymd- och geovetenskap, Radarfjärranalys

Anders Berg

Chalmers, Rymd- och geovetenskap, Radarfjärranalys

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

1939-1404 (ISSN) 2151-1535 (eISSN)

Vol. 9 1 369-380 7377006

Styrkeområden

Transport

Ämneskategorier

Fjärranalysteknik

Oceanografi, hydrologi, vattenresurser

Sannolikhetsteori och statistik

DOI

10.1109/JSTARS.2015.2506786

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Senast uppdaterat

2022-04-05