examples

🚧 Under Construction 🚧
This section is being worked on and will be completed soon.

Example of how to use the Titantuner

In this section we illustrate how to use Titantuner. The parameters provided are intended as examples to inspire, but they may differ from those that best suit your specific needs. The choice of tests depends on the objectives of the quality control, as well as the type of network and the geographical context. All the examples below are done using the test obs_ta_demo.txt.

Combine tests

Titantuner offers the possibility of combining tests:

Example of combination for temperature

Using "further test only unflagged values" helps eliminate large errors before refining the test. This ensures that erroneous values do not affect the statistics, and it can also lead to faster computation times. A typical workflow for the quality control of temperature might be: first flagging large errors using a buddy check test, then flagging smaller errors with an SCT (Statistical Consistency Test), and finally identifying stations with too few neighboring stations, where spatial statistical quality control may be limited.

Example of other combinations

One might wish to refine conditions for a station to be excluded/kept. For instance it is possible to run two tests after each other and combine the results using "pass if pass this test or previous, reject others", "pass if pass this test and previous, reject others" , "reject if flagged by this test or previous, keep others", "reject if flagged both by this test and previous, keep others". Here is an example of using "pass if pass this test or previous, reject others":

Understand better the effect of parameters

When using "Apply test (no combination / first test)" with different tests or different parameters, it is possible to visually compare the results. Here is an example, where we see the effect of changing T2pos and T2neg (named pos and neg arguments in Titanlib) for the SCT test. When using stations that are not shielded it is likely that they will indicate warmer temperature when exposed in the sun. Thus one can wish a different criteria according to if the temperature deviate positively or negatively from the statistical values.