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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.04488 |
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| _version_ | 1866916313553698816 |
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| author | Chrust, Marcin Weaver, Anthony T. Browne, Philip Zuo, Hao Balmaseda, Magdalena Alonso |
| author_facet | Chrust, Marcin Weaver, Anthony T. Browne, Philip Zuo, Hao Balmaseda, Magdalena Alonso |
| contents | An Ensemble of Data Assimilations (EDA) can provide valuable information on the analysis and short-range forecast uncertainties. The present ECMWF operational ocean analysis and reanalysis system, called ORAS5, produces an ensemble but does not exploit it for the specification of the background-error covariance matrix $\mathbf{B}$, a key component of the data assimilation system. In this article, we describe EDA developments for the ocean, which take advantage of the short-range forecast ensemble for specifying, in two distinct ways, parameters of a covariance model representation of $\mathbf{B}$. First, we generate a climatological ensemble over an extended period to produce seasonally varying climatological estimates of background-error variances and horizontal correlation length-scales. Second, on each assimilation cycle, we diagnose flow-dependent variances from the ensemble and blend them with the climatological estimates to form hybrid variances. We also use the ensemble to diagnose flow-dependent vertical correlation length-scales. We demonstrate for the Argo-rich period that this new, hybrid formulation of $\mathbf{B}$ results in a significant reduction of background errors compared to the parameterized formulation of $\mathbf{B}$ used in ORAS5. The new ocean EDA system will be employed in ORAS6, ECMWF's next generation ocean reanalysis system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_04488 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Impact of an Ensemble of Ocean Data Assimilations in ECMWF's next generation ocean reanalysis system Chrust, Marcin Weaver, Anthony T. Browne, Philip Zuo, Hao Balmaseda, Magdalena Alonso Atmospheric and Oceanic Physics An Ensemble of Data Assimilations (EDA) can provide valuable information on the analysis and short-range forecast uncertainties. The present ECMWF operational ocean analysis and reanalysis system, called ORAS5, produces an ensemble but does not exploit it for the specification of the background-error covariance matrix $\mathbf{B}$, a key component of the data assimilation system. In this article, we describe EDA developments for the ocean, which take advantage of the short-range forecast ensemble for specifying, in two distinct ways, parameters of a covariance model representation of $\mathbf{B}$. First, we generate a climatological ensemble over an extended period to produce seasonally varying climatological estimates of background-error variances and horizontal correlation length-scales. Second, on each assimilation cycle, we diagnose flow-dependent variances from the ensemble and blend them with the climatological estimates to form hybrid variances. We also use the ensemble to diagnose flow-dependent vertical correlation length-scales. We demonstrate for the Argo-rich period that this new, hybrid formulation of $\mathbf{B}$ results in a significant reduction of background errors compared to the parameterized formulation of $\mathbf{B}$ used in ORAS5. The new ocean EDA system will be employed in ORAS6, ECMWF's next generation ocean reanalysis system. |
| title | Impact of an Ensemble of Ocean Data Assimilations in ECMWF's next generation ocean reanalysis system |
| topic | Atmospheric and Oceanic Physics |
| url | https://arxiv.org/abs/2407.04488 |