a web interface for griding arbitrarily distributed in situ data based on data-interpolating variational analysis (diva)
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ID: 190226
2010
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Abstract
Spatial interpolation of observations on a regular grid is a common task in many
oceanographic disciplines (and geosciences in general). It is often used to create climatological maps for physical,
biological or chemical parameters representing e.g. monthly or seasonally averaged fields. Since instantaneous observations
can not be directly related to a field representing an average, simple spatial interpolation of observations is in general
not acceptable. DIVA (Data-Interpolating Variational Analysis) is an analysis tool which takes the error in the
observations and the typical spatial scale of the underlying field into account. Barriers due to the coastline
and the topography in general and also currents estimates (if available) are used to propagate the information
of a given observation spatially.
DIVA is a command-line driven application written in Fortran and Shell Scripts. To make DIVA easier to use, a web interface has been developed (http://gher-diva.phys.ulg.ac.be). Installation and compilation of DIVA is therefore not required. The user can directly upload the data in ASCII format and enter several parameters for the analysis. The analyzed field, location of the observations, and the error mask are presented as different layers using the Web Map Service protocol. They are visualized in the browser using the Javascript library OpenLayers allowing the user to interact with layers (for example zooming and panning). Finally, the results can be downloaded as a NetCDF file, Matlab/Octave file and Keyhole Markup Language (KML) file for visualization in applications such as Google Earth.
DIVA is a command-line driven application written in Fortran and Shell Scripts. To make DIVA easier to use, a web interface has been developed (http://gher-diva.phys.ulg.ac.be). Installation and compilation of DIVA is therefore not required. The user can directly upload the data in ASCII format and enter several parameters for the analysis. The analyzed field, location of the observations, and the error mask are presented as different layers using the Web Map Service protocol. They are visualized in the browser using the Javascript library OpenLayers allowing the user to interact with layers (for example zooming and panning). Finally, the results can be downloaded as a NetCDF file, Matlab/Octave file and Keyhole Markup Language (KML) file for visualization in applications such as Google Earth.
| Reference Key |
barth2010advancesa
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|---|---|
| Authors | ;A. Barth;A. Alvera-Azcárate;C. Troupin;M. Ouberdous;J.-M. Beckers |
| Journal | journal of the medical library association |
| Year | 2010 |
| DOI |
10.5194/adgeo-28-29-2010
|
| URL | |
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