Stochastic Forcing for Ocean Uncertainty Prediction
Our research vision is to develop and transform ocean modeling and data assimilation to quantify regional ocean dynamics on multiple scales. Our group creates and utilizes new models and methods for multiscale modeling, uncertainty quantification, data assimilation and the guidance of autonomous...
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| Format: | Article |
| Language: | English |
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Defense Technical Information Center
2024
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| Online Access: | https://hdl.handle.net/1721.1/153821 |
| _version_ | 1811068496920969216 |
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| author | Lermusiaux, Pierre F. |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Lermusiaux, Pierre F. |
| author_sort | Lermusiaux, Pierre F. |
| collection | MIT |
| description | Our research vision is to develop and transform ocean modeling and data assimilation to quantify
regional ocean dynamics on multiple scales. Our group creates and utilizes new models and methods
for multiscale modeling, uncertainty quantification, data assimilation and the guidance of autonomous
vehicles. We then apply these advances to better understand physical, acoustical and biological
interactions. We seek both fundamental and applied contributions to build knowledge and benefit naval
operations. |
| first_indexed | 2024-09-23T07:56:51Z |
| format | Article |
| id | mit-1721.1/153821 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T07:56:51Z |
| publishDate | 2024 |
| publisher | Defense Technical Information Center |
| record_format | dspace |
| spelling | mit-1721.1/1538212024-09-16T21:05:01Z Stochastic Forcing for Ocean Uncertainty Prediction Lermusiaux, Pierre F. Massachusetts Institute of Technology. Department of Mechanical Engineering Our research vision is to develop and transform ocean modeling and data assimilation to quantify regional ocean dynamics on multiple scales. Our group creates and utilizes new models and methods for multiscale modeling, uncertainty quantification, data assimilation and the guidance of autonomous vehicles. We then apply these advances to better understand physical, acoustical and biological interactions. We seek both fundamental and applied contributions to build knowledge and benefit naval operations. 2024-03-20T15:48:00Z 2024-03-20T15:48:00Z 2012-09-30 2024-03-20T15:28:03Z Article http://purl.org/eprint/type/Report https://hdl.handle.net/1721.1/153821 Lermusiaux, Pierre F. 2012. "Stochastic Forcing for Ocean Uncertainty Prediction." en 10.21236/ada574631 Creative Commons Attribution-Noncommercial-ShareAlike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Defense Technical Information Center Defense Technical Information Center |
| spellingShingle | Lermusiaux, Pierre F. Stochastic Forcing for Ocean Uncertainty Prediction |
| title | Stochastic Forcing for Ocean Uncertainty Prediction |
| title_full | Stochastic Forcing for Ocean Uncertainty Prediction |
| title_fullStr | Stochastic Forcing for Ocean Uncertainty Prediction |
| title_full_unstemmed | Stochastic Forcing for Ocean Uncertainty Prediction |
| title_short | Stochastic Forcing for Ocean Uncertainty Prediction |
| title_sort | stochastic forcing for ocean uncertainty prediction |
| url | https://hdl.handle.net/1721.1/153821 |
| work_keys_str_mv | AT lermusiauxpierref stochasticforcingforoceanuncertaintyprediction |