Compilation and analysis of existing ocean and ice data. (AMOC: Task 1)
The objective is to develop and design an acoustic system for long-term monitoring of the ocean temperature and ice thickness in the Arctic Ocean, including the Fram Strait, for climate variability studies and global warming detection. The approach is to detect and quantify global warming in the Arc...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Report |
| Language: | English |
| Published: |
1999
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| Subjects: | |
| Online Access: | https://zenodo.org/record/7703997 https://doi.org/10.5281/zenodo.7703997 |
| Summary: | The objective is to develop and design an acoustic system for long-term monitoring of the ocean temperature and ice thickness in the Arctic Ocean, including the Fram Strait, for climate variability studies and global warming detection. The approach is to detect and quantify global warming in the Arctic Ocean, using gyre scale acoustic long range propagation for basin wide ocean temperature and ice thickness changes. Acoustic propagation, which has been successfully tested for climate monitoring in other oceans, will be an important component in addition to remote sensing of sea ice from satellites, in situ observations and modelling. An acoustic monitoring system can potentially be used to verify such warming in the Arctic Ocean. The unique combination of the underwater acoustic remote sensing with satellite remote sensing of the ice cover including modelling and data assimilation, in the predicted sensitive climate region of the Arctic Ocean, is perhaps the key solution to monitor global climate changes and early detection of global warming. Task 1 will provide the other tasks with input data for model runs. This input will be through distributing sample data sets along a first set of profiles, and by compiling a common reposistory of ice and ocean data that can be used by modellers. During Task 1, the input formats of the selected acoustical models were inspected, preparing for developing a graphical user interface that generates model input files automatically. This will make the work with running models more efficient, as preparing all input files manually will be time consuming. NERSC Technical Report no. 162. Funded by the European Union, Contract no. ENV4-CT97-0463 |
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