The first checks can be routinely performed and do not require a specific knowledge of the studied region.
Internal consistency check
These tests aims to detect incorrect analysis parameters.
- Check the vertical and temporal coherence of:
- the correlation length L
- the signal-to-noise ratio λ
- the analyzed and background fields, through simple statistics (mean value, mean gradient, etc)
Large variations may be the manifestation of a wrong evaluation of the analysis parameters during the application of DIVA.
- Compare the mean distance between observation and compare it with L
- Compute RMS between two successive layers (depth and time)
Simple visual checks (by non-experts)
These tests also allows one to detect incorrect analysis parameters, but also isolated outliers. (A mechanism to report the outliers to the data provider might be an idea to develop)
- Visualize analyzed and error field
- Check the misfit between data and analysis
Consistency with a priori knowledge
These tests require a knowledge concerning the studied variables.
- Check the range of the field value and gradient compared to the range of data (if enough), or with values by experts. The range can be a function of:
- time of the year (month, season)
- location (basin, ocean, etc)
- Compare the regional product with global climatology World Ocean Atlas, if the studied variables are present in the WOA.
- Check the correlation between WOA and Emodnet parameters
Validation by regional experts
- Visual validation of various horizontal and vertical sections
- Comparison of data products with information from scientific literature
- Comparison with regional climatologies (if existing)
Validation work-flow (proposed)
- The originator uploads the product to a test site.
- He checks the product and possibly update the products.
- Two regional experts (project members or not) are invited to comment on the products.
- The data product maybe need to adapted to address the comments.
- If two regional experts are satisfied, the data products will be transfered on the official OceanBrowser web-site.
- Troupin, C. (2011). Detection of wrong analysis with Diva.