temperature

Functions to make adjustments to temperature maps.

lapse_rate_to_all(ds, *args)

Applies lapse rate correction to variables whose name contains “t_air”.

Parameters:: ds (xr.Dataset) – Dataset on whose variables containing “t_air” a lapse rate correction will be applied.
Returns:: Dataset on whose variables containing “t_air” a lapse rate correction has been applied.
Return type:: xr.Dataset

template(ds, var, out_var=None)

Example enhancer function.

Parameters:

ds (xr.Dataset) – Input dataset.
var (str) – Variable to adjust.
out_var (str, optional) – variable to store new variable, by default None.

Returns:

Output dataset.

Return type:

xr.Dataset

kelvin_to_celsius(ds, var, in_var=None, out_var=None)

Convert units of a variable from Kelvin to degrees Celsius.

Parameters:

ds (xr.Dataset) – Dataset containing var.
var (str) – Variable name.
in_var (str, optional) – Overwrites var, by default None.
out_var (str, optional) – Instead of overwriting var, store the new data in out_var, by default None.

Returns:

Adjusted data.

Return type:

xarray.Dataset

celsius_to_kelvin(ds, var, out_var=None)

Convert units of a variable from Kelvin to degrees Celsius.

Parameters:

ds (xr.Dataset) – Dataset containing var.
var (str) – Variable name.
out_var (str, optional) – Instead of overwriting var, store the new data in out_var, by default None.

Returns:

Adjusted data.

Return type:

xarray.Dataset

lapse_rate(ds, var, out_var=None, lapse_var='z', radius=0.25, lapse_rate=-0.006)

Apply a lapse-rate to var inside ds based on the difference between the actual value of lapse_var and its local (defined by radius) mean.

Parameters:

ds (xarray.Dataset) – Dataset with the data.
var (str) – Name of the variable inside ds to apply this function to (y).
out_var (str, optional) – Instead of overwriting var, store the new data in out_var, by default None.
lapse_var (str, optional) – The variable used to calculate dx.
radius (float, optional) – The local altitude is compared to the local mean altitude, radius (in degrees) defines over which area to calculate the mean, by default 0.25.
lapse_rate (float, optional) – dy/dx, i.e. how much should var be adjusted per difference in lapse_var, by default -0.006.

Returns:

Adjusted data.

Return type:

xarray.Dataset

create_circle(pixel_size_x, pixel_size_y, radius, boolean=False)

Create a 2d array with pixel values representing the distance to the center of the array.

Parameters:

pixel_size_x (float) – Size of a pixel in the x-direction. Unit can be anything, as long as it is the same as for pixel_size_y and radius.
pixel_size_y (float) – Size of a pixel in the y-direction. Unit can be anything, as long as it is the same as for pixel_size_x and radius.
radius (float) – Size of the circle. Unit can be anything, as long as it is the same as for pixel_size_x and pixel_size_y.
boolean (bool, optional) – Return distances to center (False) or whether or not the distance to the center is smaller than radius (True), by default False.

Returns:

Values representing the distance to the center of the array.

Return type:

ndarray

local_mean(array, pixel_size, radius, method=3)

Calculate local means.

Parameters:

array (ndarray) – Two dimensional array for which local means will be calculated.
pixel_size (tuple) – Size of the pixels in array in x and y direction respectively.
radius (float) – Size of the circle around each pixel from which to calculate the local mean.

Returns:

Array with the local mean of each pixel.

Return type:

ndarray

bt_to_lst(ds, x, ndvi_s=0.2, ndvi_v=0.5, emis_s=0.97, emis_v=0.985)

Convert brightness temperature to land surface temperature according to Sobrino et al (2008).

Parameters:

ds (xr.Dataset) – Input.
x (None) – Not used.
ndvi_s (float, optional) – Threshold value, by default 0.2
ndvi_v (float, optional) – Threshold value, by default 0.5
emis_s (float, optional) – Threshold value, by default 0.97
emis_v (float, optional) – Threshold value, by default 0.985

Returns:

Dataset in which bt has been replaced with lst.

Return type:

xr.Dataset