The latest from the Data Assimilation Research Testbed: New algorithms for non-gaussian distributions and sampling errors; new memory management for larger models and faster execution; new model and o
Raeder, K. D., Anderson, J. L., Gharamti, M. E., Kershaw, H., Raczka, B., et al. (2022). The latest from the Data Assimilation Research Testbed: New algorithms for non-gaussian distributions and sampling errors; new memory management for larger models and faster execution; new model and o.
| Title | The latest from the Data Assimilation Research Testbed: New algorithms for non-gaussian distributions and sampling errors; new memory management for larger models and faster execution; new model and o |
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| Genre | Conference Material |
| Author(s) | Kevin D. Raeder, Jeffrey L. Anderson, Mohamad El Gharamti, Helen Kershaw, Brett Raczka, Benjamin K. Johnson, Marlena Smith, E. Liu, J. Labriola, F. Ishraque, D. Hagan |
| Abstract | |
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| Publication Date | Dec 14, 2022 |
| Publisher's Version of Record | |
| OpenSky Citable URL | https://n2t.org/ark:/85065/d78919xx |
| OpenSky Listing | View on OpenSky |
| CISL Affiliations | TDD, DARES |