Polarview@FIMR: WWW-based delivery of baltic sea ice products to end-users

Karvonen, Juha; Haapala, Jari; Lehtiranta, Jonni; Seinä, Ari

doi:10.1109/igarss.2007.4423031

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…For the Baltic Sea, SAR images are used to produce a spatially more accurate level ice thickness chart (pixel size 500 m × 500 m) than the ice chart of the Finnish Ice Service (FIS) (resolution 10 km; Karvonen and others, 2003, 2007). The ice area boundaries in the FIS ice chart are relocated to correspond to the area boundaries of the segmented, i.e.…”

Section: Earlier Studies Of Satellite-based Sea-ice Thickness Mappingmentioning

confidence: 99%

Multisensor data and thermodynamic sea-ice model based sea-ice thickness chart with application to the Kara Sea, Arctic Russia

Similä¹,

Mäkynen²,

Cheng³

et al. 2013

Ann. Glaciol.

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ABSTRACT. We introduce a method to construct an ice thickness chart using two satellite datasets and a one-dimensional high-resolution thermodynamic snow and sea-ice model (HIGHTSI). Thin-ice thickness up to 40 cm is retrieved using MODIS ice surface temperature data. For thicker ice, thickness is retrieved from a combination of SAR image and background level ice thickness chart H i provided by HIGHTSI. Because H i is inherently static, we utilize passive microwave data based sea-ice concentration charts to introduce mesoscale ice dynamics into H i . In order to create the thickness chart, the value of modified H i is scaled by a factor which depends on the magnitude of backscattering coefficient 0 . The proposed method is effective in cold winter conditions. We calculated a series of ice thickness charts covering the Kara Sea, Arctic Russia, during winter 2008/09. The ice thickness charts were validated against Russian ice charts. Our method gave realistic results in the thickness range 30-120 cm and was uncertain for the detection of thinner-ice areas. Due to the limitations in our reference dataset, more validation work is needed to establish the accuracy in more detail. Our thickness charts can be used for operational purposes and in climate studies.

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Section: Earlier Studies Of Satellite-based Sea-ice Thickness Mappingmentioning

confidence: 99%

Multisensor data and thermodynamic sea-ice model based sea-ice thickness chart with application to the Kara Sea, Arctic Russia

Similä¹,

Mäkynen²,

Cheng³

et al. 2013

Ann. Glaciol.

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“…Given the strong influence of surface roughness on backscatter from FYI, this relationship has been exploited to develop thickness retrieval algorithms from single-frequency, single-polarization SAR data [7], [8]. While encouraging, these thickness retrieval algorithms cannot be directly applied to ice regimes containing multiyear ice (MYI) due to the increased influence of volume scattering from air bubbles in MYI, and the different surface roughness properties of FYI and MYI.…”

Section: Introductionmentioning

confidence: 99%

Comparison of in situ and airborne measurements of multiyear sea ice thickness with dual-frequency, polarimetric SAR observations

Casey

Beckers

Busche

et al. 2013

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS

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First results are presented from a comparison of in situ and airborne measurements of sea ice thickness to C-and Xband polarimetric synthetic aperture radar images acquired over the Lincoln Sea in March-May 2012. Operation IceBridge data indicate a moderate correlation between ice surface roughness and thickness in this multi-year ice regime, motivating efforts to derive ice thickness from SAR data. C-band backscatter shows moderate correlations to in situ and airborne ice thicknesses (r ≈ 0.6). At X-band correlations with airborne ice thickness data are much lower. For all polarizations the relationship with ice thickness levels off at thicknesses greater than 5 m, where ice is heavily deformed. Current research efforts are focused on exploiting polarimetric parameters to discriminate thick deformed ice to support future efforts to develop a thickness retrieval algorithm for undeformed ice up to 5 m thick.

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Polarview@FIMR: WWW-based delivery of baltic sea ice products to end-users

Cited by 2 publications

References 14 publications

Multisensor data and thermodynamic sea-ice model based sea-ice thickness chart with application to the Kara Sea, Arctic Russia

Multisensor data and thermodynamic sea-ice model based sea-ice thickness chart with application to the Kara Sea, Arctic Russia

Comparison of in situ and airborne measurements of multiyear sea ice thickness with dual-frequency, polarimetric SAR observations

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