def ncar_humidity_data(grid: 'GridDimensions' = GridDimensions((10, 20)),
year: int = None) -> np.array:
"""
A data provider returning (by default) 1-degree gridded relative
humidity data at surface level. The data will be adjusted to a new
grid if one is provided.
Data is returned as a nested list structure. The outermost list has
12 indices, and represents months of the year. For instance, index 0
represents January, and index 9 is October. The second index is latitude,
and the third is longitude.
The data will default to a 1-by-1-degree grid, but can be converted to
other grid dimensions through the two function parameters. Only grids
containing integer multiples of the original grid are supported.
:param grid:
The dimensions of the grid onto which the data will be converted
:return:
NCEP/NCAR surface relative humidity data
"""
dataset = custom_readers.NCEPReader('water')
humidity = dataset.collect_timed_layered_data('rhum', year)
# Regrid the humidity variable to the specified grid, if necessary.
regridded_humidity = _regrid_netcdf_variable(humidity, grid, 4)
grid_by_count = grid.dims_by_count()
top_atm_shape = (humidity.shape[0], 5, grid_by_count[0], grid_by_count[1])
high_layer_humidity = np.zeros(top_atm_shape)
regridded_humidity = np.hstack((regridded_humidity, high_layer_humidity))
return regridded_humidity
def ncar_pressure_levels() -> np.array:
"""
:param grid:
:type grid:
:param year:
:type year:
:return:
:rtype:
"""
dataset = custom_readers.NCEPReader('temperature')
return dataset.pressure()
def ncar_temperature_data(grid: 'GridDimensions' = GridDimensions((10, 20)),
year: int = None) -> np.array:
"""
:param grid:
:type grid:
:param year:
:type year:
:return:
:rtype:
"""
dataset = custom_readers.NCEPReader('temperature')
temp = dataset.collect_timed_layered_data('air', year)
# Regrid the humidity variable to the specified grid, if necessary.
regridded_temp = _regrid_netcdf_variable(temp, grid, 4)
ground_temp = regridded_temp[:, 0, ...]
ground_temp = ground_temp[:, np.newaxis, ...]
regridded_temp = np.hstack((ground_temp, regridded_temp))
return regridded_temp