Skip to main content

Gridding for auroral and ionospheric modeling

Project description

https://zenodo.org/badge/36744963.svg https://travis-ci.org/scivision/gridaurora.svg?branch=master https://ci.appveyor.com/api/projects/status/2jjhaq3rqjrw77vg?svg=true https://coveralls.io/repos/scivision/gridaurora/badge.svg?branch=master&service=github

gridaurora

Discretizations of space (grids) and time conversions useful for aeronomy and auroral modeling.

Install

python -m pip install -e .

Note: you will need a Fortran compiler on your system so that f2py can work. Yes, it’s possible on Windows too.

Eigenprofiles

Currently GLOW and Rees-Sergienko-Ivanov are available (Transcar in future). You will need to separately install scivision/reesaurora and scivision/glowaurora. This is to keep the install process from becoming gigantic when you just want some of the models.

Once installed, select model by:

-M option

Model used

-M rees

Rees-Sergienko-Ivanov

-M glow

Stan Solomon’s GLOW model

Command Line Options

-t

time, format yyyy-mm-ddTHH:MM:SSZ where Z sets UTC time zone

-c

lat, lon WGS84 geodetic degrees

-o

output, hDF5 ends in .h5

-M

model select (see table above)

-z

min,max altitude to plot [km]

Example Command

python MakeIonoEigenprofile.py -t 2013-01-31T09:00:00Z -c 65 -148 -o out.h5 -M rees

Auroral Data Files

The functions in gridaurora/calcemissions.py, based on work by Zettergren, computes per-wavelength volume emission rate along a flux tube as a function of altitude along the tube. Starting with quantities such as neutral densities computed by MSIS, differential number flux as a function of energy and altitude along the tube (this is what TRANSCAR computes), excitation cross sections as a function of energy, Franck-Condon factors and Einstein coefficients, the prompt volume emission rate may be computed.

precompute/vjeinfc.h5

compiled from tables in Vallance Jones Aurora 1974 and other sources by Matthew Zettergren, and corrected and put into HDF5 format by Michael Hirsch. The information within concerns:

N2+1NG

N2+ first negative group

N2_1PG

N2 first positive group

N2_2PG

N2 second positive group

N2+Meinel

N2+ Meinel band

atomic

atomic oxygen

metastable

metastable O and O+

Einstein coefficient matrix A

arranged A(𝜈’,𝜈’’) where:

𝜈’

upper state vibrational levels, excited from ground state 𝜈’’’ by particle impact

𝜈’’

lower state vibrational levels, decayed into from the upper state

as discussed in Appendix C of Zettergren PhD thesis, Eqn. (C.2), photon volume emission rate follows the relation P𝜈’,𝜈’’ = A(𝜈’,𝜈’’) n𝜈’

lamdba

wavelength in nanometers corresponding to the Einstein coefficient matrix A except atomic that uses the reaction rates directly.

Franck-Condon factor fc

as described in Zettergren thesis Appendix C, specifically for Eqn (C.6-C.8), the Franck-Condon factors modify the total upper state excitation cross section multiplicitively.

Function Description

function

description

ztanh.py

continuously varying grid using hyperbolic tangent. Inspired by suggestion from Prof. Matt Zettergren of ERAU.

References

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gridaurora-1.2.0.tar.gz (30.3 kB view details)

Uploaded Source

Built Distribution

gridaurora-1.2.0-py3-none-any.whl (34.8 kB view details)

Uploaded Python 3

File details

Details for the file gridaurora-1.2.0.tar.gz.

File metadata

  • Download URL: gridaurora-1.2.0.tar.gz
  • Upload date:
  • Size: 30.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for gridaurora-1.2.0.tar.gz
Algorithm Hash digest
SHA256 f7e2352bd955e470f030c63b9ef0e0c7093237ea14d1f832e43c15b6208d8649
MD5 d74add7bf108b6060a24a4d0ef347aa4
BLAKE2b-256 2a2d7ae5e5078cd169acad43e3397f62c3e635b21da26e21ae1c3c79828a1a7e

See more details on using hashes here.

File details

Details for the file gridaurora-1.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for gridaurora-1.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 126baf0690c7a1008047d3a30beacaec8bee98ac20da139d24bc495b7ef00b54
MD5 ee0dbe141a86139606d98646ff9cd8b9
BLAKE2b-256 2336fc9b5f85ead646bc83b5acd24aab203404c8276279c3122efab9a8c83014

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page