easyclimate.interp.modellevel2pressure#

Interpolate from model level layers to pressure layer

Functions#

interp1d_vertical_model2pressure(→ xarray.DataArray)

Interpolating variables from the model levels (e.g., sigma vertical coordinate) to the standard pressure levels by 1-D function.

Module Contents#

easyclimate.interp.modellevel2pressure.interp1d_vertical_model2pressure(pressure_data: xarray.DataArray, variable_data: xarray.DataArray, vertical_input_dim: str, vertical_output_dim: str, vertical_output_level: list[int | float], kind: str = 'linear', bounds_error=None, fill_value=np.nan, assume_sorted: bool = False) → xarray.DataArray#

Interpolating variables from the model levels (e.g., sigma vertical coordinate) to the standard pressure levels by 1-D function.

pressure_data: xarray.DataArray.

The pressure on each model level.

variable_data: xarray.DataArray.

variable to be interpolated on model levels.

vertical_input_dim: str.

The name of the model levels dimension.

vertical_output_dim: str.

The name of the standard pressure levels dimension, often assigned the value ‘plev’ (Pa) or ‘lev’ (hPa).

vertical_output_level: list[int | float].

Customized standard pressure levels to be interpolated, e.g., [5000, 10000, 15000, 20000, 25000, 30000, 40000, 50000, 60000, 70000, 85000, 92500, 100000].

Note

The unit of vertical_output_level shuold be same as pressure_data, e.g., the unit of pressure_data is Pa, and the unit of vertical_output_level shuold be Pa.

kind: str or int, default: ‘linear’.

Specifies the kind of interpolation as a string or as an integer specifying the order of the spline interpolator to use. The string has to be one of ‘linear’, ‘nearest’, ‘nearest-up’, ‘zero’, ‘slinear’, ‘quadratic’, ‘cubic’, ‘previous’, or ‘next’. ‘zero’, ‘slinear’, ‘quadratic’ and ‘cubic’ refer to a spline interpolation of zeroth, first, second or third order; ‘previous’ and ‘next’ simply return the previous or next value of the point; ‘nearest-up’ and ‘nearest’ differ when interpolating half-integers (e.g. 0.5, 1.5) in that ‘nearest-up’ rounds up and ‘nearest’ rounds down.

bounds_error: bool, default: None.

If True, a ValueError is raised any time interpolation is attempted on a value outside of the range of pressure_data (where extrapolation is necessary). If False, out of bounds values are assigned fill_value. By default, an error is raised unless fill_value=”extrapolate”.

fill_value: array-like or (array-like, array_like) or “extrapolate”, default: np.nan.

If a ndarray (or float), this value will be used to fill in for requested points outside of the data range. If not provided, then the default is NaN. The array-like must broadcast properly to the dimensions of the non-interpolation axes.
If a two-element tuple, then the first element is used as a fill value for x_new < x[0] and the second element is used for x_new > x[-1]. Anything that is not a 2-element tuple (e.g., list or ndarray, regardless of shape) is taken to be a single array-like argument meant to be used for both bounds as below, above = fill_value, fill_value. Using a two-element tuple or ndarray requires bounds_error=False.
If “extrapolate”, then points outside the data range will be extrapolated.

assume_sortedbool: bool, default: False.

If False, values of x can be in any order and they are sorted first. If True, pressure_data has to be an array of monotonically increasing values.