Fusion of Satellite SAR with Passive Microwave Data for Sea Ice Remote Sensing

Author(s):  
S. G. Beaven ◽  
S. P. Gogineni
2019 ◽  
Vol 11 (17) ◽  
pp. 2009 ◽  
Author(s):  
Qingkai Wang ◽  
Peng Lu ◽  
Yongheng Zu ◽  
Zhijun Li ◽  
Matti Leppäranta ◽  
...  

Arctic sea ice concentration (SIC) has been studied extensively using passive microwave (PM) remote sensing. This technology could be used to improve navigation along vessel cruise paths; however, investigations on this topic have been limited. In this study, shipborne photographic observation (P-OBS) of sea ice was conducted using oblique-oriented cameras during the Chinese National Arctic Research Expedition in the summer of 2016. SIC and the areal fractions of open water, melt ponds, and sea ice (Aw, Ap, and Ai, respectively) were determined along the cruise path. The distribution of SIC along the cruise path was U-shaped, and open water accounted for a large proportion of the path. The SIC derived from the commonly used PM algorithms was compared with the moving average (MA) P-OBS SIC, including Bootstrap and NASA Team (NT) algorithms based on Special Sensor Microwave Imager/Sounder (SSMIS) data; and ARTIST sea ice, Bootstrap, Sea Ice Climate Change Initiative, and NASA Team 2 (NT2) algorithms based on Advanced Microwave Scanning Radiometer 2 (AMSR2) data. P-OBS performed better than PM remote sensing at detecting low SIC (< 10%). Our results indicate that PM SIC overestimates MA P-OBS SIC at low SIC, but underestimates it when SIC exceeds a turnover point (TP). The presence of melt ponds affected the accuracy of the PM SIC; the PM SIC shifted from an overestimate to an underestimate with increasing Ap, compared with MA P-OBS SIC below the TP, while the underestimation increased above the TP. The PM algorithms were then ranked; SSMIS-NT and AMSR2-NT2 are the best and worst choices for Arctic navigation, respectively.


2016 ◽  
Vol 121 (9) ◽  
pp. 7056-7072 ◽  
Author(s):  
Yasuhiro Tanaka ◽  
Kazutaka Tateyama ◽  
Takao Kameda ◽  
Jennifer K. Hutchings

Oceanography ◽  
1993 ◽  
Vol 6 (1) ◽  
pp. 4-12 ◽  
Author(s):  
Barry ◽  
Masianik ◽  
Steffen ◽  
Weaver ◽  
Troisi ◽  
...  

1995 ◽  
Vol 19 (2) ◽  
pp. 216-242 ◽  
Author(s):  
Joseph M. Piwowar ◽  
Ellsworth F. LeDrew

Climatologists have speculated that a spatially coherent pattern of high-latitude temperature trends could be an early indicator of climatic change. The sensitivity of sea ice to the temperature of the overlying air suggests the possibility that trends in Arctic ice conditions may be useful proxy indicators of general climatic changes. Aspects of the north-polar ice pack which have been identified as key parameters to be monitored include ice extent, concentration, type, thickness and motion dynamics. In spite of the considerable interannual, regional and seasonal variations exhibited by these data, there may be some evidence of an emerging trend towards decreasing ice extent and concentration. Collecting data in such a remote and harsh environment to support these analyses is only possible through satellite remote sensing. Remote sensing in the microwave portion of the electromagnetic spectrum is particularly relevant for polar applications because microwaves are capable of penetrating the atmosphere under virtually all conditions and are not dependent on the sun as a source of illumination. In particular, analyses of passive microwave imagery can provide us with daily information on sea-ice extent, type, concentration, dynamics and melt onset. A historical record of Arctic imagery from orbiting passive microwave sensors starting from 1973 provides us with an excellent data source for climate change studies. The development of analysis tools to support large area monitoring is integral to advancing global change research. The critical need is to create techniques which highlight the space-time relationships in the data rather than simply displaying voluminous quantities of data. In particular, hypertemporal image analysis techniques are required to help find anticipated trends and to discover unexpected or anomalous temporal relationships. Direct hypertemporal classification, principal components analysis and spatial time-series analysis are identified as three primary techniques for enhancing change in temporal image sequences. There is still a need for the development of new tools for spatial- temporal modelling.


2006 ◽  
Vol 44 ◽  
pp. 433-438 ◽  
Author(s):  
Walter N. Meier ◽  
Julienne Stroeve ◽  
Shari Gearheard

AbstractPassive microwave imagery indicates a decreasing trend in Arctic Summer Sea-ice extent Since 1979. The Summers of 2002–05 have exhibited particularly reduced extent and have reinforced the downward trend. Even the winter periods have now Shown decreasing trends. At the local level, Arctic residents are also noticing changes in Sea ice. In particular, indigenous elders and hunters report changes Such as earlier break-up, later freeze-up and thinner ice. The changing conditions have profound implications for Arctic-wide climate, but there is also regional variability in the extent trends. These can have important ramifications for wildlife and indigenous communities in the affected regions. Here we bring together observations from remote Sensing with observations and knowledge of Inuit who live in the Baffin Bay region. Weaving the complementary perspectives of Science and Inuit knowledge, we investigate the processes driving changes in Baffin Bay Sea-ice extent and discuss the present and potential future effects of changing Sea ice on local activities.


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