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A full implementation of the ICAO standard atmosphere 1993

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Ambiance is a full implementation of the ICAO standard atmosphere 1993 written in Python.

Basic usage

Atmospheric properties are computed from an Atmosphere object which takes the altitude (geometric height) as input. For instance, to simply retrieve sea level properties, you can write:

>>> from ambiance import Atmosphere
>>> sealevel = Atmosphere(0)

>>> sealevel.temperature

>>> sealevel.pressure

>>> sealevel.kinematic_viscosity

List of available atmospheric properties

  • Collision frequency (collision_frequency)

  • Density (density)

  • Dynamic viscosity (dynamic_viscosity)

  • Geometric height above MSL (h)

  • Geopotential height (H)

  • Gravitational acceleration (grav_accel)

  • Kinematic viscosity (kinematic_viscosity)

  • Layer names (layer_name) [string array]

  • Mean free path (mean_free_path)

  • Mean particle speed (mean_particle_speed)

  • Number density (number_density)

  • Pressure (pressure)

  • Pressure scale height (pressure_scale_height)

  • Specific weight (specific_weight)

  • Speed of sound (speed_of_sound)

  • Temperature (temperature, temperature_in_celsius)

  • Thermal conductivity (thermal_conductivity)

Vector and matrix inputs

Ambiance also handles list-like input (list, tuples, Numpy arrays). The following code demonstrates how to produce a temperature plot with Matplotlib. In the example, Numpy’s linspace() function is used to produce an array with altitudes.

import numpy as np
import matplotlib.pyplot as plt
from ambiance import Atmosphere

# Create an atmosphere object
heights = np.linspace(-5e3, 80e3, num=1000)
atmosphere = Atmosphere(heights)

# Make plot
plt.plot(atmosphere.temperature_in_celsius, heights/1000)
plt.ylabel('Height [km]')
plt.xlabel('Temperature [°C]')

The output is

Temperature plot

Similarly, you can also pass in entire matrices. Example:

>>> import numpy as np
>>> from ambiance import Atmosphere

>>> h = np.array([[0, 11, 12], [20, 21, 35], [0, 80, 50]])*1000
>>> h  # Geometric heights in metres
array([[    0, 11000, 12000],
       [20000, 21000, 35000],
       [    0, 80000, 50000]])

>>> Atmosphere(h).temperature
array([[288.15      , 216.7735127 , 216.65      ],
       [216.65      , 217.58085353, 236.51337209],
       [288.15      , 198.63857625, 270.65      ]])

>>> Atmosphere(h).speed_of_sound
array([[340.29398803, 295.15359145, 295.06949351],
       [295.06949351, 295.70270856, 308.29949587],
       [340.29398803, 282.53793156, 329.798731  ]])

>>> Atmosphere([30000, 0]).layer_name
array(['stratosphere', 'troposphere'], dtype='<U42')

Instantiating from given pressure or density

In some contexts it may be convenient to instantiate an Atmosphere object from a given ambient pressure or density. This can be easily achieved by using the Atmosphere.from_pressure() or Atmosphere.from_density() methods, respectively. Both methods return Atmosphere objects from which all other properties, like temperature, can be requested.

>>> Atmosphere.from_pressure([80e3, 20e3])  # 80 kPa and 20 kPa
Atmosphere(array([ 1949.58557497, 11805.91571135]))

>>> Atmosphere.from_pressure([80e3, 20e3]).pressure
array([80000., 20000.])

>>> Atmosphere.from_density(1.0)  # 1.0 kg/m^3

Complete user guide

For a comprehensive and detailed user guide, please see the complete documentation.



The package can be installed via the Conda environment with

conda install -c conda-forge ambiance
Conda Recipe Conda Downloads Conda Version


Using Ambiance requires

  • Python 3.6 or higher

  • NumPy

  • SciPy

For developers: Recommended packages may be installed with the requirements.txt.

pip install -r requirements.txt


License: Apache-2.0

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