Cardington core observation file
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- Python
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Description
### Developing functionality to ingest Cardington core file: metoffice-obr-fluxtower_cardington_boundary-layer-met_YYYYMMDD_30min
*Initial Parameters**
[] air_temperature_prt_2m: standard_name = "air_temperature"
[] relative_humidity_1p2m: standard_name = "relative_humidity"
[] wind_speed_scalar_2m: standard_name = "wind_speed"
[] wind_direction_2m: standard_name = "wind_from_direction"
[] specific_humidity_2m: long_name = "Mean specific humidity at 2m"
[] pressure_barometric: standard_name = "air_pressure"
Recipe based around:
[recipes](https://github.com/MetOffice/CSET/tree/main/src/CSET/recipes)/[surface_fields]
/generic_surface_single_point_time_series.yaml
(1) Load data as if it was another model - read.read_cubes
(2) in recipe var.constraint on 'air temperature'
(3) Use coordinate opertator CSET.operators.regrid.regrid_to_single_point on model data
(3b) Set boundary margin argument to zero
Observation
steps:
- operator: read.read_cube
file_paths: $INPUT_PATHS
constraint:
operator: constraints.combine_constraints
varname_constraint:
operator: constraints.generate_var_constraint
varname: 'air temperature'
cell_methods_constraint:
operator: constraints.generate_cell_methods_constraint
cell_methods: ['mean']
coord: 'time'
interval: '1 hour'
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