1. Outline RTQC goals to achieve Description of current proposal Tests
Tool
Output

2. RTQC Goal
Define a set of criteria that glider datasets should meet to be considered as usable
According to glider observing capabilities
Implement a tool that validates datasets against the defined set of criteria.
Do not modify data, just flag it.
Other tools can make use of it to apply corrections if required

3. RTQC Tests
Tests to be applied on glider data have to be defined (what criteria should the data meet?).
Initial guess made up now is a translation and adaptation of some of the tests for ARGO profilers (Thanks to Justin)
Still some specific tests are missing, like the freezing point test.

4. RTQC Tests
But tests will have to be adapted to glider observing capabilities:
Resolution, both temporal and spatial are typically higher than ARGO profilers.
Sensors specificities pose problems less visible on other platforms.
Platform movement allows to observe different processes.

5. RTQC tool A Matlab tool has been developed to this end.
Given a dataset and a QC configuration
Applies defined QC Tests over the data.
Outputs the result on a NetCDF file, containing the original information plus the ancillary information about data quality.

6. RTQC tool The tool is configurable by means of a JSON file.
The configuration contains a list of parameters to be tested.
Each parameter contains an ordered list of tests to be applied on the data.

7. RTQC tool Each test contains: Type of test to be applied.
Parameters (thresholds, windows, etc.).
Constraints on data that should pass the test.
Flag to apply if test fails (suspicious, bad, etc.).

8. RTQC tool By now, 4 test types are implemented: Valid range Gradient
Spike
Stationary

9. RTQC tool
Generalizations to previous QC tests definitions are introduced here, adding a reference variable:
Range test is sample independent.
Gradient, spike and stationary tests depend on sampling rate, which can by varying.
A reference variable is added at this point.
Reference variable can be time, depth, etc.

10. RTQC tool
Constraints on the test allow to restrict applicability of a test to only certain conditions:
Regions
Depth ranges
Time (for seasonality, still to be implemented)

11. RTQC tool
Examples (separatedly)

12. RTQC tool Density inversion test: Build folding profiles:
From surface to deepest, at each point compute the maximum density value.
From deepest point to surface, at each point compute the minimum density value.
Given the two folding profiles, wherever the difference exceeds a defined threshold, it is flagged as a density inversion.

13. RTQC Tool output
The output of the RTQC process is dumped on a NetCDF file.
It has to be adequately documented and compliant with conventions.

14. RTQC Tool output
Scientific variable needs to have documented in it that there is QC information available.
Attribute “QC_indicator” can exist and have one value for the whole variable
Attribute “ancillary_variables” can exist and have a space-separated list of variable names

15. RTQC Tool output QC variable needs to be documented as well:
Attribute standard_name is built with the standard name of the variable it refers to plus a modifier: “status_flag”.
Attributes “flag_values” and “flag_meanings” document the table of possible values for this variable.

16. Conclusions A RTQC tool has been developed.
Basic tests are implemented.
Easy configuration.
Need advise of scientists with regional expertise and glider technicians to fine tune the tests to be applied.