SAR, SSMI and numerical model characterisation of Arctic Ocean coastal polynyas
Coastal polynyas in the Arctic basin from the winter period (January to March) are characterised using ERS-1/2 SAR images [full resolution (PRI) and Browse image product], passive microwave data [the polynya SSM/I signature model (PSSM), the Bootstrap and the NASA Team algorithms] and a numerical po...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Text |
| Language: | English |
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| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.4923 http://earth.esa.int/pub/ESA_DOC/gothenburg/019dokke.pdf |
| Summary: | Coastal polynyas in the Arctic basin from the winter period (January to March) are characterised using ERS-1/2 SAR images [full resolution (PRI) and Browse image product], passive microwave data [the polynya SSM/I signature model (PSSM), the Bootstrap and the NASA Team algorithms] and a numerical polynya model (NPM). A SAR polynya algorithm is used to delineate open water, new ice, young ice, and to define the size and shape of polynyas. In order to extract the radiometric and contextual information in the ERS SAR PRI images, different image classification routines are developed and applied. No in-situ data has been available for verification of the polynya shapes and sizes, but the ice classification routines have to some extent been verified. The PSSM calculates polynya shape and size, and delineates open water and thin ice. It compares significantly better with the SAR compared to the NASA Team and the Bootstrap algorithms, but especially the calculation of thin ice can be improved with the help of SAR data. The wind-driven NPM computes offshore coastal polynya widths, heat exchange, ice production, and salt ejection. SAR PRI images are the most useful data set to validate the NPM and the use of SAR in combination with the NPM significantly contributes to characterise and to gain knowledge about the dynamics of polynyas. Envisat (and Radarsat 2) will have full polarisation and increased temporal and spatial coverage (compared to today's SAR sensors) that will further emphasise the applicability of the SAR. More SAR satellite data is highly necessary to assess these features in the Arctic climate study contexts. |
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