Diive

MeteoScreening Air Temperature

MeteoScreening uses a general settings file `pipes_meteo.yaml` that contains info how
specific `measurements` should be screened. Such `measurements` group similar variables
together, e.g. different air temperatures are measurement `TA`.
Additions to module `pkgs.qaqc.meteoscreening`:

- Added class `ScreenVar`
- Performs quality screening of air temperature `TA`.
- As first check, I implemented outlier detection via the newly added package `ThymeBoost`,
along with checks for absolute limits.
- Screening applies the checks defined in the file `pipes_meteo.yaml` for the respective
`measurement`, e.g. `TA` for air temperature.
- The screening outputs a separate dataframe that contains `QCF` flags for each check.
- The checks do not change the original time series. Instead, only the flags are generated.
- Screening routines for more variables will be added over the next updates.
- Added class `MeteoScreeningFromDatabaseSingleVar`
- Performs quality screening *and* resampling to 30MIN of variables downloaded from the database.
- It uses the `detailed` data when downloading data from the database using `dbc-influxdb`.
- The `detailed` data contains the measurement of the variable, along with multiple tags that
describe the data. The tags are needed for storage in the database.
- After quality screening of the original high-resolution data, flagged values are removed and
then data are resampled.
- It also handles the issue that data downloaded for a specific variable can have different time
resolution over the years, although I still need to test this.
- After screening and resampling, data are in a format that can be directly uploaded to the
database using `dbc-influxdb`.
- Added class `MeteoScreeningFromDatabaseMultipleVars`
- Wrapper where multiple variables can be screened in one run.
- This should also work in combination of different `measurements`. For example, screening
radiation and temperature data in one run.

Outlier Detection

Additions to `pkgs.outlierdetection`:

- Added module `thymeboost`
- Added module `absolute_limits`

[//]: (- optimum range)

[//]: (- `diive.core.times` `DetectFrequency` )

[//]: (- `diive.core.times`: `resampling` module )

[//]: (- New package in env: `ThymeBoost` [GitHub]&40;https://github.com/tblume1992/ThymeBoost/tree/main/ThymeBoost) )

Carbon cost

**GENERAL**

- This version introduces the code for calculating carbon cost and critical heat days.

**NEW PACKAGES**

- Added new package for flux-specific calculations: `diive.pkgs.flux`

**NEW MODULES**

- Added new module for calculating carbon cost: `diive.pkgs.flux.carboncost`
- Added new module for calculating critical heat days: `diive.pkgs.flux.criticalheatdays`

**CHANGES & ADDITIONS**

- None

**BUGFIXES**

- None

Starting diive library

**GENERAL**

The `diive` library contains packages and modules that aim to facilitate working
with time series data, in particular ecosystem data.

Previous versions of `diive` included a GUI. The GUI component will from now on
be developed separately as `diive-gui`, which makes use of the `diive` library.

Previous versions of `diive` (up to v0.22.0) can be found in the separate repo
[diive-legacy](https://gitlab.ethz.ch/diive/diive-legacy).

This initial version of the `diive` library contains several first versions of
packages that will be extended with the next versions.

Notable introduction in this version is the package `echires` for working with
high-resolution eddy covariance data. This package contains the module `fluxdetectionlimit`,
which allows the calculation of the flux detection limit following Langford et al. (2015).

**NEW PACKAGES**

- Added `common`: Common functionality, e.g. reading data files
- Added `pkgs > analyses`: General analyses
- Added `pkgs > corrections`: Calculate corrections for existing variables
- Added `pkgs > createflag`: Create flag variables, e.g. for quality checks
- Added `pkgs > createvar`: Calculate new variables, e.g. potential radiation
- Added `pkgs > echires`: Calculations for eddy covariance high-resolution data, e.g. 20Hz data
- Added `pkgs > gapfilling`: Gap-filling routines
- Added `pkgs > outlierdetection`: Outlier detection
- Added `pkgs > qaqc`: Quality screening for timeseries variables

**NEW MODULES**

- Added `optimumrange` in `pkgs > analyses`
- Added `gapfinder` in `pkgs > analyses`
- Added `offsetcorrection` in `pkgs > corrections`
- Added `setto_threshold` in `pkgs > corrections`
- Added `outsiderange` in `pkgs > createflag`
- Added `potentialradiation` in `pkgs > createvar`
- Added `fluxdetectionlimit` in `pkgs > echires`
- Added `interpolate` in `pkgs > gapfilling`
- Added `hampel` in `pkgs > outlierdetection`
- Added `meteoscreening` in `pkgs > qaqc`

**CHANGES & ADDITIONS**

- None

**BUGFIXES**

- None

**REFERENCES**

- Hollinger, D. Y., & Richardson, A. D. (2005). Uncertainty in eddy covariance measurements
and its application to physiological models. Tree Physiology, 25(7),
873–885. https://doi.org/10.1093/treephys/25.7.873
- Langford, B., Acton, W., Ammann, C., Valach, A., & Nemitz, E. (2015). Eddy-covariance data with low signal-to-noise
ratio: Time-lag determination, uncertainties and limit of detection. Atmospheric Measurement Techniques, 8(10),
4197–4213. https://doi.org/10.5194/amt-8-4197-2015
- Papale, D., Reichstein, M., Aubinet, M., Canfora, E., Bernhofer, C., Kutsch, W., Longdoz, B., Rambal, S., Valentini,
R., Vesala, T., & Yakir, D. (2006). Towards a standardized processing of Net Ecosystem Exchange measured with eddy
covariance technique: Algorithms and uncertainty estimation. Biogeosciences, 3(4),
571–583. https://doi.org/10.5194/bg-3-571-2006
- Pastorello, G. et al. (2020). The FLUXNET2015 dataset and the ONEFlux processing pipeline
for eddy covariance data. 27. https://doi.org/10.1038/s41597-020-0534-3
- Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N.,
Gilmanov, T., Granier, A., Grunwald, T., Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila,
A., Loustau, D., Matteucci, G., … Valentini, R. (2005). On the separation of net ecosystem exchange into assimilation
and ecosystem respiration: Review and improved algorithm. Global Change Biology, 11(9),
1424–1439. https://doi.org/10.1111/j.1365-2486.2005.001002.x