Literature DB >> 26473335

Ocean Data Assimilation in Support of Climate Applications: Status and Perspectives.

D Stammer1, M Balmaseda2, P Heimbach3,4, A Köhl1, A Weaver5.   

Abstract

Ocean data assimilation brings together observations with known dynamics encapsulated in a circulation model to describe the time-varying ocean circulation. Its applications are manifold, ranging from marine and ecosystem forecasting to climate prediction and studies of the carbon cycle. Here, we address only climate applications, which range from improving our understanding of ocean circulation to estimating initial or boundary conditions and model parameters for ocean and climate forecasts. Because of differences in underlying methodologies, data assimilation products must be used judiciously and selected according to the specific purpose, as not all related inferences would be equally reliable. Further advances are expected from improved models and methods for estimating and representing error information in data assimilation systems. Ultimately, data assimilation into coupled climate system components is needed to support ocean and climate services. However, maintaining the infrastructure and expertise for sustained data assimilation remains challenging.

Entities:  

Keywords:  climate predictions; data assimilation; data synthesis; modeling; observing system; ocean circulation

Mesh:

Year:  2015        PMID: 26473335     DOI: 10.1146/annurev-marine-122414-034113

Source DB:  PubMed          Journal:  Ann Rev Mar Sci        ISSN: 1941-0611


  3 in total

1.  Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction.

Authors:  Stephen G Penny; Santha Akella; Magdalena A Balmaseda; Philip Browne; James A Carton; Matthieu Chevallier; Francois Counillon; Catia Domingues; Sergey Frolov; Patrick Heimbach; Patrick Hogan; Ibrahim Hoteit; Doroteaciro Iovino; Patrick Laloyaux; Matthew J Martin; Simona Masina; Andrew M Moore; Patricia de Rosnay; Dinand Schepers; Bernadette M Sloyan; Andrea Storto; Aneesh Subramanian; SungHyun Nam; Frederic Vitart; Chunxue Yang; Yosuke Fujii; Hao Zuo; Terry O'Kane; Paul Sandery; Thomas Moore; Christopher C Chapman
Journal:  Front Mar Sci       Date:  2019-07

2.  Unsupervised Learning Reveals Geography of Global Ocean Dynamical Regions.

Authors:  Maike Sonnewald; Carl Wunsch; Patrick Heimbach
Journal:  Earth Space Sci       Date:  2019-05-21       Impact factor: 2.900

3.  Vertical redistribution of salt and layered changes in global ocean salinity.

Authors:  Chao Liu; Xinfeng Liang; Rui M Ponte; Nadya Vinogradova; Ou Wang
Journal:  Nat Commun       Date:  2019-08-01       Impact factor: 14.919

  3 in total

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