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Add the USSA 1976 up to 86km

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Chunxiao Li 2020-03-30 11:07:55 +08:00
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README.md
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# Welcome to ATMOS # Welcome to ATMOS
The pyatmos package is an archive of scientific routines that can be used to handle atmospheric models. Currently, only nrlmsise00 is feasible. 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:
## How to Install 1. International Standard Atmosphere(ISA) Model up to 86km
2. NRLMSISE-00
## How to install
pyatmos can be installed with
```sh ```sh
pip install pyatmos pip install pyatmos
``` ```
## How to Use ## How to use
### International Standard Atmosphere
Calculate the ISA at an altitude(default is geometric) of 10km.
```python ```python
from pyatmos.msise import download_sw,read_sw >>> from pyatmos import isa
from pyatmos.atmosclasses import Coordinate >>> isa(10)
{'temperature[K]': 223.25186489868483,
# Download or update the space weather file from www.celestrak.com 'pressure[Pa]': 26499.756053713343,
swfile = download_sw() 'density[kg/m^3]': 0.41350863360218376}
# Read the space weather data
sw_obs_pre = read_sw(swfile)
``` ```
``` Calculate the ISA at a geopotential altitude of 50km.
# Test 1
# 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]
# Initialize a coordinate instance by a space-time point
st = Coordinate(t,lat,lon,alt)
para_input,para_output = st.nrlmsise00(sw_obs_pre) ```python
print(para_input,'\n') >>> isa(50,'geopotential')
print(para_output) {'temperature[K]': 270.65,
'pressure[Pa]': 75.94476758456234,
'density[kg/m^3]': 0.0009775244455727493}
``` ```
``` Calculate the ISA at 90km.
{'doy': 278, 'year': 2015, 'sec': 10800.0, 'alt': 70, 'g_lat': 25, 'g_long': 102, 'lst': 9.8, 'f107A': 150, 'f107': 150, 'ap': 4, 'ap_a': array([4, 4, 4, 4, 4, 4, 4])}
{'d': {'He': 9100292488300570.0, 'O': 0, 'N2': 1.3439413974205876e+21, 'O2': 3.52551376755781e+20, 'AR': 1.6044163757370681e+19, 'RHO': 8.225931818480755e-05, 'H': 0, 'N': 0, 'ANM O': 0}, 't': {'TINF': 1027.3184649, 'TG': 219.9649472491653}} ```python
>>> 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
# Test 2
t = '2004-07-08 10:30:50' Get the space weather data
lat,lon,alt = -65,-120,100
st = Coordinate(t,lat,lon,alt) ```python
para_input,para_output = st.nrlmsise00(sw_obs_pre) >>> from pyatmos import download_sw,read_sw
print(para_input,'\n') >>> # Download or update the space weather file from www.celestrak.com
print(para_output) >>> 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.
{'doy': 190, 'year': 2004, 'sec': 37850.0, 'alt': 100, 'g_lat': -65, 'g_long': -120, 'lst': 2.5138888888888893, 'f107A': 109.0, 'f107': 79.3, 'ap': 2, 'ap_a': array([2. , 2. , 2. , 2. , 2. , 3.125, 4.625])}
{'d': {'He': 119477307274636.89, 'O': 4.1658304136233e+17, 'N2': 7.521248904485598e+18, 'O2': 1.7444969074975662e+18, 'AR': 7.739495767665198e+16, 'RHO': 4.584596293339505e-07, 'H': 22215754381448.5, 'N': 152814261016.3964, 'ANM O': 1.8278224834873257e-37}, 't': {'TINF': 1027.3184649, 'TG': 192.5868649143824}}
```
``` ```
# Test 3 >>> from pyatmos import nrlmsise00
t = '2010-02-15 12:18:37' >>> # Set a specific time and location
lat,lon,alt = 85,210,500 >>> t = '2015-10-05 03:00:00' # time(UTC)
st = Coordinate(t,lat,lon,alt) >>> lat,lon = 25,102 # latitude and longitude [degree]
para_input,para_output = st.nrlmsise00(sw_obs_pre,'NoOxygen','Aph') >>> alt = 70 # altitude [km]
print(para_input,'\n') >>> para_input,para_output = nrlmsise00(t,lat,lon,alt,swdata)
print(para_output) >>> 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.
{'doy': 46, 'year': 2010, 'sec': 44317.0, 'alt': 500, 'g_lat': 85, 'g_long': 210, 'lst': 2.310277777777779, 'f107A': 83.4, 'f107': 89.4, 'ap': 14, 'ap_a': array([14. , 5. , 7. , 6. , 15. , 5.375, 4. ])}
{'d': {'He': 3314507585382.5425, 'O': 3855595951659.0874, 'N2': 19285497858.028534, 'O2': 395599656.3119481, 'AR': 146073.85956102316, 'RHO': 1.2650700238089615e-13, 'H': 171775437382.8238, 'N': 38359828672.39737, 'ANM O': 5345258193.554493}, 't': {'TINF': 776.3155804924045, 'TG': 776.3139192714452}}
```
``` ```
# Test 4 >>> t = '2004-07-08 10:30:50'
t = '2019-08-20 23:10:59' >>> lat,lon,alt = -65,-120,100
lat,lon,alt = 3,5,900 >>> para_input,para_output = nrlmsise00(t,lat,lon,alt,swdata)
st = Coordinate(t,lat,lon,alt) >>> print(para_input,'\n')
para_input,para_output = st.nrlmsise00(sw_obs_pre,aphmode = 'Aph') >>> print(para_output)
print(para_input,'\n') {'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])}
print(para_output)
{'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.
{'doy': 232, 'year': 2019, 'sec': 83459.0, 'alt': 900, 'g_lat': 3, 'g_long': 5, 'lst': 23.51638888888889, 'f107A': 67.4, 'f107': 67.7, 'ap': 4, 'ap_a': array([4. , 4. , 3. , 3. , 5. , 3.625, 3.5 ])}
{'d': {'He': 74934329990.0412, 'O': 71368139.39199762, 'N2': 104.72048033793158, 'O2': 0.09392848471935447, 'AR': 1.3231114543012155e-07, 'RHO': 8.914971667362366e-16, 'H': 207405192640.34592, 'N': 3785341.821909535, 'ANM O': 1794317839.638502}, 't': {'TINF': 646.8157488121493, 'TG': 646.8157488108872}} ```
>>> 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}}
``` ```
For more details, please refer to `st.nrlmsise00?`. 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
- **1.1.0 — Mar 29, 2020**
- Added the International Standard Atmosphere(ISA) Model up to 86kms
## Next release ## Next release
- Complete the help documentation - Complete the help documentation
- Improve the code structure to make it easier to read - Improve the code structure to make it easier to read
- Add other atmospheric models - 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 ## Reference
- U.S. Standard Atmosphere, 1976, U.S. Government Printing Office, Washington, D.C.
- [Public Domain Aeronautical Software](http://www.pdas.com/atmos.html)
- https://gist.github.com/buzzerrookie/5b6438c603eabf13d07e
- https://ww2.mathworks.cn/help/aerotbx/ug/atmosisa.html
* [Original Fortran and C code](https://ccmc.gsfc.nasa.gov/pub/modelweb/atmospheric/msis/) * [Original Fortran and C code](https://ccmc.gsfc.nasa.gov/pub/modelweb/atmospheric/msis/)
* [MSISE-00 in Python and Matlab](https://github.com/space-physics/msise00) * [MSISE-00 in Python and Matlab](https://github.com/space-physics/msise00)
* [NRLMSISE-00 Atmosphere Model - Matlab](https://ww2.mathworks.cn/matlabcentral/fileexchange/56253-nrlmsise-00-atmosphere-model?requestedDomain=zh) * [NRLMSISE-00 Atmosphere Model - Matlab](https://ww2.mathworks.cn/matlabcentral/fileexchange/56253-nrlmsise-00-atmosphere-model?requestedDomain=zh)

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pyatmos/msise/nrlmsise00.py
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@ -1022,7 +1022,7 @@ def gts7(inputp,flags,gsurf,re):
# ============================ nrlmsise00 =========================== # # ============================ nrlmsise00 =========================== #
def nrlmsise00(t,lat,lon,alt,SW_OBS_PRE,omode='Oxygen',aphmode='NoAph'): def nrlmsise00(t,lat,lon,alt,SW_OBS_PRE,omode='NoOxygen',aphmode='NoAph'):
t = Time(t) t = Time(t)
lon_wrap = wraplon(lon) lon_wrap = wraplon(lon)
t_yday = t.yday.split(':') t_yday = t.yday.split(':')