Retrieval of sea ice parameters using fusion of high resolution model and remote sensing data
This thesis discusses the retrieval of sea ice parameters using the combination of remote sensing data and a sea ice model for the region of the Baffin Bay, Hudson Bay, Labrador Sea and the Gulf of St. Lawrence. The Los Alamos sea ice model, CICE, which is used as a module for coupled global ice-oce...
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| Format: | Thesis |
| Language: | English |
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Memorial University of Newfoundland
2018
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| Online Access: | https://research.library.mun.ca/13355/ https://research.library.mun.ca/13355/1/thesis.pdf |
| Summary: | This thesis discusses the retrieval of sea ice parameters using the combination of remote sensing data and a sea ice model for the region of the Baffin Bay, Hudson Bay, Labrador Sea and the Gulf of St. Lawrence. The Los Alamos sea ice model, CICE, which is used as a module for coupled global ice-ocean models, was used for this work. The model was implemented with a 7-category thickness distribution, open boundaries and a variable coefficient for ice-ocean heat flux. A slab ocean mixed-layer model based on density criteria was used for the standalone regional implementation of the model. The model estimates of ice concentration were validated using seasonal means, and anomalies. A combined optimal interpolation and nudging scheme was implemented to assimilate Sea Surface Temperature (SST) and ice concentration from Advanced very-high-resolution radiometer (AVHRR) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) respectively. The inclusion of the variable drag coefficient required updates of ice volume and dependent tracers corresponding to the updates in the ice concentration estimates. The sea ice variables of thickness, freeboard, level ice draft and keel depth were compared with the estimates derived from Soil Moisture and Ocean Salinity (SMOS), CryoSat2, and a ULS instrument respectively. The assimilated model provided better estimates of ice concentration, thickness, freeboard and level ice draft. The model estimated ice thickness compared well with the thin ice thickness estimated from the SMOS data, except during March, when there is significant ice extent. The reason for this discrepancy could be attributed to the absence of mixed layer heat flux forcing in the model and also the effect of snow and the onset of melt that alters the observation. Field measurements were also used for the comparison of model estimates. The measurements from the Upward Looking Sonar (ULS) instrument located at Makkovick Bank were used to estimate the level ice draft and keel depth. The observations from ULS along ... |
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