pymsis 0.9.0

Description:

pymsis 0.9.0

pymsis: A python wrapper of the NRLMSIS model






Pymsis is a minimal and fast Python wrapper of the NRLMSIS
models (MSISE-00, MSIS2.0, MSIS2.1).
Quickstart
Web viewer: An interactive website using pymsis through cloud-based serverless functions.
Project homepage: Location for all documentation.
API Reference: Details about the various options and configurations available in the functions.
Examples: Demo for how to access and plot the data.
A few short lines of code to get started quickly with pymsis.

Create a range of dates during the 2003 Halloween storm.
Run the model at the desired location (lon, lat) (0, 0) and 400 km altitude.
Plot the results to see how the mass density increased at 400 km altitude during this storm.

import numpy as np
from pymsis import msis

dates = np.arange(np.datetime64("2003-10-28T00:00"), np.datetime64("2003-11-04T00:00"), np.timedelta64(30, "m"))
# geomagnetic_activity=-1 is a storm-time run
data = msis.run(dates, 0, 0, 400, geomagnetic_activity=-1)

# Plot the data
import matplotlib.pyplot as plt
# Total mass density over time
plt.plot(dates, data[:, 0, 0, 0, 0])
plt.show()


note

The model will automatically download and access the F10.7 and ap data for you if you have an internet connection.
The returned data structure has shape [ndates, nlons, nlats, nalts, 11], but for this example we only have one point with many dates [ndates, 1, 1, 1, 11].
The 11 is for each of the species MSIS calculates for each input point. The first element is the Total Mass Density (kg/m3).


NRL Mass Spectrometer, Incoherent Scatter Radar Extended Model (MSIS)
The MSIS
model
is developed by the Naval Research Laboratory.
Note that the MSIS2 code is not available for commercial use without
contacting NRL. See the MSIS2 license file for explicit
details. We do not repackage the MSIS source code in this
repository for that reason. However, we do provide utilities to easily
download and extract the original source code. By using that code you
agree to their terms and conditions.
References
Please acknowledge the University of Colorado Space Weather Technology,
Research and Education Center (SWx TREC) and cite the original papers if
you make use of this model in a publication.
Python Code


Lucas, G. (2022). pymsis [Computer software]. doi:10.5281/zenodo.5348502

MSIS2.1

Emmert, J. T., Jones, M., Siskind, D. E., Drob, D. P., Picone, J. M.,
Stevens, M. H., et al. (2022). NRLMSIS 2.1: An empirical model of nitric
oxide incorporated into MSIS. Journal of Geophysical Research: Space
Physics, 127, e2022JA030896. doi:10.1029/2022JA030896

MSIS2.0

Emmert, J. T., Drob, D. P., Picone, J. M., Siskind, D. E., Jones, M.,
Mlynczak, M. G., et al. (2020). NRLMSIS 2.0: A whole‐atmosphere
empirical model of temperature and neutral species densities. Earth
and Space Science, 7, e2020EA001321.
doi:10.1029/2020EA001321

MSISE-00

Picone, J. M., Hedin, A. E., Drob, D. P., and Aikin, A. C.,
NRLMSISE‐00 empirical model of the atmosphere: Statistical comparisons
and scientific issues, J. Geophys. Res., 107( A12), 1468,
doi:10.1029/2002JA009430,
2002.

Geomagnetic Data
If you make use of the automatic downloads of the F10.7 and ap data,
please cite that data in your publication as well. The data is downloaded
from CelesTrak, which has filled in missing data from the source. Both citations
are given below.

CelesTrak. https://celestrak.org/SpaceData/


Matzka, J., Stolle, C., Yamazaki, Y., Bronkalla, O. and Morschhauser, A.,
2021. The geomagnetic Kp index and derived indices of geomagnetic activity.
Space Weather, doi:10.1029/2020SW002641.

Installation
The easiest way to install pymsis is to install from PyPI.
pip install pymsis

For the most up-to-date pymsis, you can install directly from the git
repository
pip install git+https://github.com/SWxTREC/pymsis.git

or to work on it locally, you can clone the repository and install the
test dependencies.
git clone https://github.com/SWxTREC/pymsis.git
cd pymsis
pip install .[tests]

Remote installation
The installation is dependent on access to the NRL source code. If the
download fails, or you have no internet access you can manually install
the Fortran source code as follows. A script to help with this or give
ideas on how to achieve this remote installation are provided in the
tools directory.


Download the source code
The source code is hosted on NRL's website:
https://map.nrl.navy.mil/map/pub/nrl/NRLMSIS/NRLMSIS2.0/
Download the NRLMSIS2.0.tar.gz file to your local system.


Extract the source files
The tar file needs to be extracted to the src/msis2.0 directory.
tar -xvzf NRLMSIS2.0.tar.gz -C src/msis2.0/



Install the Python package
pip install .