In addition to spatial interpolations (from stations or grids with different resolutions) it is also possible to temporally resample grids. Hence, if a set of grids is available at certain dates (from weather models for example), a number of resampling algorithms can be configured to provide data at dates/times in between.

Grid resampling section

First, grid resampling must be enabled by setting the REGRIDDING_STRATEGY to GRID_1DINTERPOLATE in the [InputEditing] section. Note that this currently forces the path through the temporal resampling (regridding) algorithms, and any spatial resampling configured (from point timeseries) will not take action. Then, grid resampling is configured in the [GridInterpolations1D] section for each meteo parameter separately.

For example:

[InputEditing]
REGRIDDING_STRATEGY = GRID_1DINTERPOLATE
 
[GridInterpolations1D]
TA::RESAMPLE = LINEAR

Available Grid resampling algorithms

The following grid resampling algorithms are implemented:

LINEAR: linear data resampling, see GridLinearResampling
TIMESERIES: extract time series at all grid points and use Interpolations1D algorithm, see GridTimeseriesResampling

Note: By default, linear resampling will be used. It is possible to enable/disable all resampling with the ENABLE_GRID_RESAMPLING key (in the [GridInterpolations1D] section). You can make MeteoIO write all grids that were resampled/regridded this way to the file system by setting WRITE_RESAMPLED_GRIDS = TRUE (also in [GridInterpolations1D]).