Reference : Analysis of Ocean in Situ Observations and Web - Based Visualization: From Individua...
Parts of books : Contribution to collective works
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
http://hdl.handle.net/2268/201033
Analysis of Ocean in Situ Observations and Web - Based Visualization: From Individual Measurements to an Integrated View
English
Barth, Alexander mailto [Université de Liège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
Watelet, Sylvain mailto [Université de Liège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
Troupin, Charles []
Alvera Azcarate, Aida mailto [Université de Liège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
Beckers, Jean-Marie mailto [Université de Liège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
Sep-2016
Oceanographic and Marine Cross-Domain Data Management for Sustainable Development
Diviacco, Paolo
Leadbetter, Adam
Glaves, Helen
IGI Global
300
Yes
9781522507000
Hershey
USA
[en] Variational Inverse Method ; Data-Interpolating Variational Analysis ; Statistical Modelling ; In Situ Measurements ; Climatology ; Data Products ; Web-Based Visualization ; Web Map Service
[en] 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.
GHER, MARE, AGO
Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS ; Commission européenne : Direction générale des Affaires maritimes et de la Pêche ; Union Européenne = European Union - UE = EU ; CECI
EMODNET Chemistry, SeaDataNet II
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/201033
10.4018/978-1-5225-0700-0
http://www.igi-global.com/book/oceanographic-marine-cross-domain-data/148510
FP7 ; 283607 - SEADATANET II - SeaDataNet II: Pan-European infrastructure for ocean and marine data management

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
Barth2016-DIVA-OceanBrowser.pdfAuthor preprint4.9 MBView/Open

Bookmark and Share SFX Query

All documents in ORBi are protected by a user license.