Analysis of ocean in situ observations and Web-based visualization: From individual measurements to an integrated view
Barth, A.; Watelet, S.; Troupin, C.; Alvera-Azcárate, A.; Beckers, J.M. (2017). Analysis of ocean in situ observations and Web-based visualization: From individual measurements to an integrated view, in: Diviacco, P. et al. Oceanographic and marine cross-domain data management for sustainable development. pp. 345-371. http://dx.doi.org/10.4018/978-1-5225-0700-0.ch015
In: Diviacco, P.; Leadbetter, A.; Glaves, H. (Ed.) (2017). Oceanographic and marine cross-domain data management for sustainable development. Advances in Environmental Engineering and Green Technologies. IGI Global: Hershey. ISBN 978-1-5225-0700-0. xxv, 424 pp., more
In: Advances in Environmental Engineering and Green Technologies. IGI Global: Hershey. ISSN 2326-9162; e-ISSN 2326-9170, more
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Authors | | Top |
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- Alvera-Azcárate, A., more
- Beckers, J.M., more
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Abstract |
The sparsity of observations poses a challenge common to various ocean disciplines. Even for physical parameters where the spatial and temporal coverage is higher, current observational networks undersample a broad spectrum of scales. This situation is generally more severe for chemical and biological parameters because such sensors are less widely deployed. The present chapter describes the analysis tool DIVA (Data-Interpolating Variational Analysis) which is designed to generate gridded fields from in situ observations. DIVA has been applied to various physical (temperature and salinity), chemical (concentration of nitrate, nitrite and phosphate) and biological parameters (abundance of a species). The chapter also shows the technologies used to visualize the gridded fields. Visualization of analyses from in situ observations provide a unique set of challenges since the accuracy of the analysed field is not spatially uniform as it strongly depends on the location of the observations. In addition, an adequate treatment of the depth and time dimensions is essential. |
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