Setting Up Your Dataset¶
climpred relies on a consistent naming system for
This allows things to run more easily under-the-hood.
Prediction ensembles are expected at the minimum to contain dimensions
init is the initialization dimension, that relays the time
steps at which the ensemble was initialized.
init must be of type int,
pd.DatetimeIndex, or xr.cftimeIndex. If
init is of type
int, it is assumed to
be annual data. A user warning is issues when this assumption is made.
the lead time of the forecasts from initialization. The units for the
dimension must be specified in as an attribute. Valid options are
years, seasons, months, weeks, pentads, days. Another crucial dimension is
member, which holds the various ensemble members. Any additional dimensions will
be passed through
climpred without issue: these could be things like
Verification products are expected to contain the
time dimension at the minimum.
For best use of
time dimension should cover the full length of
init from the accompanying prediction ensemble, if possible. The
must be of type
of type int is assumed to be annual data. A user warning is issued when this assumption
is made. These products can also include additional dimensions, such as
See the below table for a summary of dimensions used in
climpred, and data types
climpred supports for them.
|Short Name||Types||Long Name||Attribute(s)|
||lead timestep after initialization, [
||units (str) [years, seasons, months, weeks, pentads, days]|
||initialization: start date of experiment||None|