Columns
This section presents a definition and examples for each column of a xscen DataCatalog.
The entries for the columns are based on CMIP6 metadata and the ES-DOC controlled vocabulary (https://github.com/ES-DOC/pyessv-archive).
Some columns might be left empty (with a NaN
), but id
, domain
, processing_level
and xrfreq
are mandatory.
These four columns are what xscen uses by default to guess which entries can be merged together : all entries with the same unique combination of
the four columns will be combined in a single Dataset when any of the first three functions listed here are used.
id
: Unique Dataset ID generated byxscen
based on a subset of columns. By default, it is based onxscen.catalog.ID_COLUMNS
.E.g. “ERA_ecmwf_ERA5_ERA5-Land_NAM”, “CMIP6_ScenarioMIP_CMCC_CMCC-ESM2_ssp245_r1i1p1f1_global”
type
: Type of data.E.g. “forecast”, “station-obs”, “gridded-obs”, “reconstruction”, “simulation”
processing_level
: Level of post-processing reached.E.g. “raw”, “extracted”, “regridded”, “biasadjusted”
bias_adjust_institution
: Institution that computed the bias adjustment.E.g. “Ouranos”, “PCIC”
bias_adjust_project
: Name of the project that computed the bias adjustment.E.g. “ESPO-R5”, “BCCAQv2”
mip_era
: CMIP generation associated with the data.E.g. “CMIP6”, “CMIP5”
activity
: Model Intercomparison Project (MIP) associated with the data. This is the same as activity_id in CMIP6 data. CMIP is the activity for the historical experiment and the DECK experiments.E.g. “CMIP”, “CORDEX”, “HighResMIP”
driving_model
: Name of the driver. Following the driving_model convention from ES-DOC, this is in the format “institution-model”.E.g. “CCCma-CanESM2”
institution
: Institution associated with the source.E.g. “CCCma”, “Ouranos”, “ECMWF”
source
: For simulation type, this is the model. For GCMs, this is the name of the model (source_id in CMIP6 and rcm_name in ES-DOC for CORDEX). For reconstruction type, this is the name of the dataset.E.g. “CanESM5”, “CRCM5”, “ERA5”, “ERA5-Land, ERA5-Preliminary”
experiment
: Name of the experiment of the model.E.g. “historical”, “ssp245”, “rcp85”
member
: Name of the realisation. For RCMs, this is the member associated with the driver.E.g. “r1i1p1f1”
xrfreq
: Pandas/xarray frequency.E.g. “YS”, “QS-DEC”
frequency
: Frequency in letters (CMIP6 format).E.g. “yr”,”qtr”
variable
: Variables in the dataset. It can be a Tuple.E.g. “tasmax”, (“tasmax”, “tasmin”, “pr”)
domain
: Name of the region covered by the dataset. It can also contain information on the grid.E.g. “global”, “NAM”, “ARC-44”, “ARC-22”
date_start
: First date of the dataset. This usually is a Datetime object with a ms resolution.E.g. “2022-06-03 00:00:00”
date_end
: Last date of the dataset. This usually is a Datetime object with a ms resolution.E.g. “2022-06-03 00:00:00”
version
: Version of the dataset.E.g. “1.0”
format
: Format of the dataset.E.g. “zarr”, “nc”
path
: Path to the dataset.E.g. “/some/path/to/the/data.zarr”