pyatmos 1.1.2

A package to estimate the atmosphere parameters

Welcome to ATMOS

The pyatmos package is an archive of scientific routines that aims to implement the estimation of atmospheric properties for various atmosphere models. Currently, feasible atmosphere models include:

1. International Standard Atmosphere(ISA) Model up to 86km
2. NRLMSISE-00

How to install

pyatmos can be installed with

pip install pyatmos

How to use

International Standard Atmosphere

Calculate the ISA at an altitude(default is geometric) of 10km.

>>> from pyatmos import isa
>>> isa(10)
{'temperature[K]': 223.25186489868483,
 'pressure[Pa]': 26499.756053713343,
 'density[kg/m^3]': 0.41350863360218376}

Calculate the ISA at a geopotential altitude of 50km.

>>> isa(50,'geopotential')
{'temperature[K]': 270.65,
 'pressure[Pa]': 75.94476758456234,
 'density[kg/m^3]': 0.0009775244455727493}

Calculate the ISA at 90km.

>>> isa(90)
Exception: geometric altitude should be in [-0.611, 86.0] km
>>> isa(90,'geopotential')    
Exception: geopotential altitude should be in [-0.610, 84.852] km    

NRLMSISE-00

Get the space weather data

>>> from pyatmos import download_sw,read_sw
>>> # Download or update the space weather file from www.celestrak.com
>>> swfile = download_sw() 
>>> # Read the space weather data
>>> swdata = read_sw(swfile) 
Updating the space weather data ... Finished

Calculate the temperatures, densities not including anomalous oxygen using the NRLMSISE-00 model at 70km, 25 degrees latitude, 102 degrees longitude on the date October 5, 2015 at 03:00:00 UTC.

>>> from pyatmos import nrlmsise00
>>> # Set a specific time and location
>>> t = '2015-10-05 03:00:00' # time(UTC)
>>> lat,lon = 25,102 # latitude and longitude [degree]
>>> alt = 70 # altitude [km]
>>> para_input,para_output = nrlmsise00(t,lat,lon,alt,swdata)
>>> print(para_input,'\n')
>>> print(para_output)
{'Year': 2015, 'DayOfYear': 278, 'SecondOfDay': 10800.0, 'Latitude[deg]': 25, 'Longitude[deg]': 102, 'Altitude[km]': 70, 'LocalSolarTime[hours]': 9.8, 'f107Average[10^-22 W/m^2/Hz]': 150, 'f107Daily[10^-22 W/m^2/Hz]': 150, 'ApDaily': 4, 'Ap3Hourly': array([4, 4, 4, 4, 4, 4, 4])} 

{'Density': {'He[1/m^3]': 9100292488300570.0, 'O[1/m^3]': 0, 'N2[1/m^3]': 1.3439413974205876e+21, 'O2[1/m^3]': 3.52551376755781e+20, 'AR[1/m^3]': 1.6044163757370681e+19, 'H[1/m^3]': 0, 'N[1/m^3]': 0, 'ANM O[1/m^3]': 0, 'RHO[kg/m^3]': 8.225931818480755e-05}, 'Temperature': {'TINF[K]': 1027.3184649, 'TG[K]': 219.9649472491653}}

Calculate the temperatures, densities not including anomalous oxygen using the NRLMSISE-00 model at 100km, -65 degrees latitude, -120 degrees longitude on the date July 8, 2004 at 10:30:50 UTC.

>>> t = '2004-07-08 10:30:50' 
>>> lat,lon,alt = -65,-120,100 
>>> para_input,para_output = nrlmsise00(t,lat,lon,alt,swdata)
>>> print(para_input,'\n')
>>> print(para_output)
{'Year': 2004, 'DayOfYear': 190, 'SecondOfDay': 37850.0, 'Latitude[deg]': -65, 'Longitude[deg]': -120, 'Altitude[km]': 100, 'LocalSolarTime[hours]': 2.5138888888888893, 'f107Average[10^-22 W/m^2/Hz]': 109.0, 'f107Daily[10^-22 W/m^2/Hz]': 79.3, 'ApDaily': 2, 'Ap3Hourly': array([2.   , 2.   , 2.   , 2.   , 2.   , 3.125, 4.625])} 

{'Density': {'He[1/m^3]': 119477307274636.89, 'O[1/m^3]': 4.1658304136233e+17, 'N2[1/m^3]': 7.521248904485598e+18, 'O2[1/m^3]': 1.7444969074975662e+18, 'AR[1/m^3]': 7.739495767665198e+16, 'H[1/m^3]': 22215754381448.5, 'N[1/m^3]': 152814261016.3964, 'ANM O[1/m^3]': 1.8278224834873257e-37, 'RHO[kg/m^3]': 4.584596293339505e-07}, 'Temperature': {'TINF[K]': 1027.3184649, 'TG[K]': 192.5868649143824}}

Calculate the temperatures, densities including anomalous oxygen using the NRLMSISE-00 model at 500km, 85 degrees latitude, 210 degrees longitude on the date February 15, 2010 at 12:18:37 UTC.

>>> t = '2010-02-15 12:18:37' 
>>> lat,lon,alt = 85,210,500 
>>> para_input,para_output = nrlmsise00(t,lat,lon,alt,swdata,omode='Oxygen')
>>> print(para_input,'\n')
>>> print(para_output)
{'Year': 2010, 'DayOfYear': 46, 'SecondOfDay': 44317.0, 'Latitude[deg]': 85, 'Longitude[deg]': 210, 'Altitude[km]': 500, 'LocalSolarTime[hours]': 2.310277777777779, 'f107Average[10^-22 W/m^2/Hz]': 83.4, 'f107Daily[10^-22 W/m^2/Hz]': 89.4, 'ApDaily': 14, 'Ap3Hourly': array([14.   ,  5.   ,  7.   ,  6.   , 15.   ,  5.375,  4.   ])} 

{'Density': {'He[1/m^3]': 2830075020953.2334, 'O[1/m^3]': 5866534735436.941, 'N2[1/m^3]': 59516979995.87239, 'O2[1/m^3]': 1558775273.2950978, 'AR[1/m^3]': 825564.7467165776, 'H[1/m^3]': 142697077779.00586, 'N[1/m^3]': 53473812381.891624, 'ANM O[1/m^3]': 4258921381.0652237, 'RHO[kg/m^3]': 1.790487924033088e-13}, 'Temperature': {'TINF[K]': 850.5598890315023, 'TG[K]': 850.5507885501303}}

Calculate the temperatures, densities including anomalous oxygen using the NRLMSISE-00 model at 900km, 3 degrees latitude, 5 degrees longitude on the date August 20, 2019 at 23:10:59 UTC. It uses not only Daily AP but also 3-hour AP magnetic index.

>>> t = '2019-08-20 23:10:59' 
>>> lat,lon,alt = 3,5,900 
>>> para_input,para_output = nrlmsise00(t,lat,lon,alt,swdata,omode='Oxygen',aphmode = 'Aph')
>>> print(para_input,'\n')
>>> print(para_output)
{'Year': 2019, 'DayOfYear': 232, 'SecondOfDay': 83459.0, 'Latitude[deg]': 3, 'Longitude[deg]': 5, 'Altitude[km]': 900, 'LocalSolarTime[hours]': 23.51638888888889, 'f107Average[10^-22 W/m^2/Hz]': 67.4, 'f107Daily[10^-22 W/m^2/Hz]': 67.7, 'ApDaily': 4, 'Ap3Hourly': array([4.   , 4.   , 3.   , 3.   , 5.   , 3.625, 3.5  ])} 

{'Density': {'He[1/m^3]': 74934329990.0412, 'O[1/m^3]': 71368139.39199762, 'N2[1/m^3]': 104.72048033793158, 'O2[1/m^3]': 0.09392848471935447, 'AR[1/m^3]': 1.3231114543012155e-07, 'H[1/m^3]': 207405192640.34592, 'N[1/m^3]': 3785341.821909535, 'ANM O[1/m^3]': 1794317839.638502, 'RHO[kg/m^3]': 8.914971667362366e-16}, 'Temperature': {'TINF[K]': 646.8157488121493, 'TG[K]': 646.8157488108872}}

Change log

• 1.1.2 — Jul 26, 2020
  • Added progress bar for downloading data
• 1.1.0 — Mar 29, 2020
  • Added the International Standard Atmosphere(ISA) Model up to 86km

Next release

• Complete the help documentation
• Improve the code structure to make it easier to read
• Add other atmospheric models, such as the U.S. Standard Atmosphere 1976(USSA1976) or Committee on Extension to the Standard Atmosphere(COESA) up to 1000km, Unofficial Australian Standard Atmosphere 2000(UASA2000), and the Jacchia-Bowman 2008 Empirical Thermospheric Density Model(JB2008)

Reference

• U.S. Standard Atmosphere, 1976, U.S. Government Printing Office, Washington, D.C.
• Public Domain Aeronautical Software
• https://gist.github.com/buzzerrookie/5b6438c603eabf13d07e
• https://ww2.mathworks.cn/help/aerotbx/ug/atmosisa.html

• Original Fortran and C code
• MSISE-00 in Python and Matlab
• NRLMSISE-00 Atmosphere Model - Matlab
• NRLMSISE-00 Atmosphere Model - Aerospace Blockset
• NRLMSISE-00 Atmosphere Model - CCMC
• NRLMSISE-00 empirical model of the atmosphere: Statistical comparisons and scientific issues