caa a22 4500 605546584 CHVBK 20210128100941.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s10236-015-0850-x doi (NATIONALLICENCE)springer-10.1007/s10236-015-0850-x Coastal ocean data assimilation using a multi-scale three-dimensional variational scheme [Elektronische Daten] [Zhijin Li, James McWilliams, Kayo Ide, John Farrara] A multi-scale three-dimensional variational scheme (MS-3DVAR) is implemented to improve the effectiveness of the assimilation of both very sparse and high-resolution observations into models with resolutions down to 1 km. The improvements are realized through the use of background error covariances of multi-decorrelation length scales and by reducing the inherent observational representativeness errors. MS-3DVAR is applied to coastal ocean data assimilation to handle the wide range of spatial scales that exist in both the dynamics and observations. In the implementation presented here, the cost function consists of two components for large and small scales, and MS-3DVAR is implemented sequentially from large to small scales. A set of observing system simulation experiments (OSSEs) are performed to illustrate the advantages of MS-3DVAR over conventional 3DVAR in assimilating two of the most common types of observations—sparse vertical profiles and high-resolution surface measurements—simultaneously. One month of results from an operational implementation show that both the analysis error and bias are reduced more effectively when using MS-3DVAR. Springer-Verlag Berlin Heidelberg, 2015 Multi-scale data assimilation nationallicence Variational data assimilation nationallicence Fine-resolution model nationallicence Ocean prediction nationallicence Observing system nationallicence Coastal ocean nationallicence Li Zhijin Jet Propulsion Laboratory, California Institute of Technology, M/S 300-323, 4800 Oak Grove Drive, Pasadena, CA, USA aut McWilliams James Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, USA aut Ide Kayo Department of Atmospheric and Oceanic Science, Center for Scientific Computation and Mathematical Modeling, Earth System Science Interdisciplinary Center, Institute for Physical Science and Technology, University of Maryland, College Park, MD, USA aut Farrara John Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, USA aut Ocean Dynamics Springer Berlin Heidelberg 65/7(2015-07-01), 1001-1015 1616-7341 65:7<1001 2015 65 10236 https://doi.org/10.1007/s10236-015-0850-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10236-015-0850-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Li Zhijin Jet Propulsion Laboratory, California Institute of Technology, M/S 300-323, 4800 Oak Grove Drive, Pasadena, CA, USA aut NATIONALLICENCE 700 1- McWilliams James Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, USA aut NATIONALLICENCE 700 1- Ide Kayo Department of Atmospheric and Oceanic Science, Center for Scientific Computation and Mathematical Modeling, Earth System Science Interdisciplinary Center, Institute for Physical Science and Technology, University of Maryland, College Park, MD, USA aut NATIONALLICENCE 700 1- Farrara John Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, USA aut NATIONALLICENCE 773 0- Ocean Dynamics Springer Berlin Heidelberg 65/7(2015-07-01), 1001-1015 1616-7341 65:7<1001 2015 65 10236