pymsis 0.6.0

A Python wrapper around the NRLMSIS model.

pymsis: A python wrapper of the NRLMSIS model

Pymsis is meant to be a minimal and fast Python wrapper of the NRLMSIS models. Documentation to get started quickly can be found on the home page. It includes some examples that demonstrate how to access and plot the data.

Quickstart

A few short lines of code to get started quickly with pymsis. Use Numpy to create a range of dates during the 2003 Halloween storm. Then run the model at the location (lon, lat) (0, 0) and 400 km altitude. 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 note that for this example we only have one longitude, latitude, and altitude. The 11 is for each of the species MSIS calculates at each point of input. The first element is the Total Mass Density (kg/m3) and if we plot that over time, we can 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.tight_layout()
plt.show()

Additional examples that demonstrate how to access and plot the data.

API Documentation with details about the various options and configurations available.

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.

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.

1. 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.

2. 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/
   

3. Install the Python package

   pip install .