Data Assimilation of realistic SWOT satellite observations
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| Sprache: | Englisch |
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2020
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| _version_ | 1866901704538062848 |
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| author | Francisco Rodrigues do Amaral |
| author_facet | Francisco Rodrigues do Amaral |
| contents | <p>For the past 25 years, satellite altimetry has produced Sea Surface Height (SSH) maps which have allowed oceanographers to study large-scale ocean dynamics (> 200km). However, the small scales of ocean circulation play a key role in a variety of natural phenomena. In order to research on finer scale ocean dynamics, the future SWOT mission will provide the capability of making measurements of SSH with unprecedented resolution. This will bring challenges to the current data processing techniques and therefore, more advanced techniques are being developed. One such technique is the Back-and-Forth Nudging (BFN) data assimilation<br> method which provides SSH maps consistent with both real-world measurements and the physics of a numerical ocean model. The objective of this project is to test and evaluate different strategies for implementing the BFN method with realistic SWOT observations accounting for both noise and errors. The results show that, for a low signal-to-noise ratio region, de-noising the SWOT observations<br> is essential for a good performance of BFN. Under de-noised observations, the best strategy was found to be by nudging only the relative vorticity (RV) term. This strategy reconstructed SSH fields with an effective resolution of 60 km and RMSE score of 0.81. For a region with high signal-to-noise ratio, the BFN method appeared robust to noisy observations. Once again, it was found that after denoising observations, the best strategy was nudging the RV term only. This strategy reconstructed SSH fields with an effective resolution of 89.9 km and RMSE score of 0.86.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_7928522 |
| institution | Zenodo |
| language | eng |
| publishDate | 2020 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Data Assimilation of realistic SWOT satellite observations Francisco Rodrigues do Amaral Data Assimilation Ocean Surface Satellite Altimetry Quasi-Geostrophic Model <p>For the past 25 years, satellite altimetry has produced Sea Surface Height (SSH) maps which have allowed oceanographers to study large-scale ocean dynamics (> 200km). However, the small scales of ocean circulation play a key role in a variety of natural phenomena. In order to research on finer scale ocean dynamics, the future SWOT mission will provide the capability of making measurements of SSH with unprecedented resolution. This will bring challenges to the current data processing techniques and therefore, more advanced techniques are being developed. One such technique is the Back-and-Forth Nudging (BFN) data assimilation<br> method which provides SSH maps consistent with both real-world measurements and the physics of a numerical ocean model. The objective of this project is to test and evaluate different strategies for implementing the BFN method with realistic SWOT observations accounting for both noise and errors. The results show that, for a low signal-to-noise ratio region, de-noising the SWOT observations<br> is essential for a good performance of BFN. Under de-noised observations, the best strategy was found to be by nudging only the relative vorticity (RV) term. This strategy reconstructed SSH fields with an effective resolution of 60 km and RMSE score of 0.81. For a region with high signal-to-noise ratio, the BFN method appeared robust to noisy observations. Once again, it was found that after denoising observations, the best strategy was nudging the RV term only. This strategy reconstructed SSH fields with an effective resolution of 89.9 km and RMSE score of 0.86.</p> |
| title | Data Assimilation of realistic SWOT satellite observations |
| topic | Data Assimilation Ocean Surface Satellite Altimetry Quasi-Geostrophic Model |
| url | https://doi.org/10.5281/zenodo.7928522 |