Save the Earth from Another Carrington Event!

The Earth Observing Dashboard showcases examples of global environmental changes for 7 themes: Atmosphere, Water and Ocean, Biomass, Cryosphere, Agriculture, Covid-19, and Economy. You can explore countries and regions around the world to see how the indicators in specific locations changed over time.

https://cdaweb.gsfc.nasa.gov/pub/data/wind/mfi/mfi_h2/2022/
To obtain BW(t) data for other years, replace the “2022” in the above URL with the desired year (e.g., 2021, 2020).

Tips on How to Open/Read a CDF File:
These instructions serve to cover the basics of how to open and read data saved in the cdf format. This will assume you have the following packages installed in your python environment:
cdflib
spacepy
matplotlib
numpy
wget

• Install CDF library
  • CDF library version 3.8 can be downloaded here: https://spdf.gsfc.nasa.gov/pub/software/cdf/dist/cdf38_0/
  • For Windows, it is suggested you use the InstallMate installer to automatically set paths. For MacOS, the universal installer is probably easiest.
  • Another option is to use https://pypi.org/project/cdflib/ which can be installed without having to first install and configure the CDF software from NASA above.
• Install python packages to read CDF
  • The two python packages we will use here to read CDF files are the pycdf package found within the spacepy toolset, and cdflib. These can be installed easily using pip, and possible conda (depending on your version of python). Depending on how you have your environment set up, it should be as simple as:
    • pip install cdflib
    • pip install spacepy
• Open a cdf file

>from spacepy import pycdf

>cdf_pycdf = pycdf.CDF(whateverfilename.cdf)

• Example Inspection

>print('These are the variables within this file:\n')

>print(cdf_pycdf)

>print('This is the global metadata record of the file:\n')

>print(cdf_pycdf.attrs)

To obtain BD(t) data for other years, replace the “2022” in the above URL with the desired year (e.g., 2021, 2020).

https://cdaweb.gsfc.nasa.gov/pub/data/wind/swe/swe_h1/2022/

To obtain Wind ion parameters for other years, replace the “2022” in the above URL with the desired year (e.g., 2021, 2020).

Information on the DSCOVR spacecraft's instruments and test plan

Near real-time space weather data from DSCOVR is used by NOAA's Space Weather Prediction Center to produce this collection of plots of weather measurements

More background information on the Faraday Cup and how it operates, including photos

The DSCOVR Data can be accessed from NOAA's DSCOVR Space Weather Data Portal

More info on the DSCOVR mission

To obtain the fc1 data, scroll down to the Faraday Cup, fc1 row in the “Data Product Documentation” section to access the data via the Portal or NEXT.

The Canadian Array for Realtime Investigations of Magnetic Activity (CARISMA) project is a series of ground-based sensors that detect disturbances in the Earth's magnetosphere (often related to solar winds). It could be useful for validating the DSCVR dataset.

Data from the Canadian solar flux archive could help you validate the data and your results from the DSCVR mission.

INPE, developed among other activities also, has been researching the spatial phenomena, from the Sun, interplanetary space, and magnetosphere to the ionosphere, the upper and middle atmosphere, and geomagnetism since its inception in 1964. In addition to the constant and essential scientific research activity of geospatial phenomena is the growing need for information on Space Weather from the technological and socio-economic communities.