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Table of Contents
Data analysis user's manual
This manual is very preliminary, please be patient or help adding what is missing.
Introduction
SPICE instrument and capabilities
SPICE papers:
- In-flight calibration: Not available yet
- Other papers can be found in the SPICE ADS library
SPICE online information:
- Wiki (including this page)
Data products
The data levels, FITS files, and headers are described in
- The Data Products Description Document (DPDD)
- The LLDPDD for the Low-Latency (LL) files
The full SPICE data set (to be cited in papers) has a DOI: doi:10.5270/esa-lbmdy7c. DOIs will also be attributed to each data release.
When browsing the SPICE catalog and archive you will see the following codes:
n-ras: a raster scan with one of the narrow slits (2“, 4” or 6“)
w-ras: a raster scan with the wide slit (30”)
n-sit: a sit-and-stare study with one of the narrow slits
w-sit: a sit-and-stare study with the wide slit
n-exp: a single exposure with a narrow slit that yields the entire spectrum
w-exp: a single exposure with the wide slit that yields the entire spectrum
For the “ras” data, the FITS file contains a single raster scan. If the raster is repeated, then each repeat goes in a new file.
Rasters can be performed in the “exp” mode, but each exposure will end up in a different FITS file.
Find data
UiO catalogue:
- Can be generated with IDL/SolarSoft (SSW) from a local data tree:
- Make sure
$SPICE_DATApoints to the data tree you want to have catalogued - Run SPICE_GEN_CAT. The catalogue file will be written to the data tree root directory (you need to have write access)
- Run SPICE_CAT
- The catalogue file generated from all SPICE files is accessible through the UiO website (restricted to SPICE team)
- How to use it in Python
- How to use it in IDL: see below
- A CSV export of the part of the catalogue corresponding to each release is provided with the release.
SOAR (and institute mirrors):
Quicklooks:
- Quicklook archive (to be developed)
In the future: VSO. VSO through SSW or sunpy. Sunpy/Fido
Tips and Advice on Analyzing SPICE Data
Doppler Maps
WARNING: Doppler maps created from SPICE lines show unusual patterns that we believe are due to the point spread function of the instrument. Work is underway on a deconvolution procedure that will correct for this effect. If you need advice on features you see in a Doppler map, please contact the SPICE PI at frederic.auchere -at- universite-paris-saclay.fr or another member of the SPICE team.
Burn-in Effects
The SPICE detectors have microchannel plates (MCPs). Over time, the sensitivity of MCPs decreases at the locations of strong emission lines. This effect is referred to as “burn-in” and results in a flat-top or “self-reversal” to the line profile. This has already been noticed for the C III 977 line. The SPICE team plans to provide a correction to this effect once it is fully characterized.
Flare lines
The two key flare lines for EIS are Fe XVIII 974.86 and Fe XX 721.56 that are formed around 7 MK and 10 MK, respectively. The Fe XVIII line will probably be seen in active region cores (at least from bright active regions).
The Fe XVIII line is located between the stronger H I 972.54 (Lyman-gamma) and C III 977.02, but measurements should be possible.
The Fe XX line lies close to Fe VIII 721.26. One can estimate the strength of this line by comparing with Mg IX 706.06. The latter will be about a factor 10 stronger.
To determine if a flare is occurring at the time of a SPICE observation, check the STIX Data Browser at:
Access data
SPICE team internal access:
- UiO website (restricted).
Once the data will be released:
- SOAR (and institute mirrors)
- VSO. VSO through SSW or sunpy. Sunpy/Fido
Read and display data (IDL)
External links:
- Oslo's quicklook tools spice_data, spice_object...
- Peter Young's SPICE Analysis Guide
Environment variables
Choose a location to store your SPICE data (e.g., '/my_data/spice') and then point the environment variable $SPICE_DATA to it:
setenv,'SPICE_DATA=/my_data/spice'
This line should be added to your IDL_STARTUP file.
Data are organized under $SPICE_DATA with a year/month/day subdirectory structure. See the “Ingesting downloaded data” section below.
The SPICE catalog
The SPICE catalog can be accessed by doing:
IDL> spice_cat
Use the “SPICE_GEN_CAT” button to make sure you have the most up-to-date list.
Reference data-sets
Perhaps the most useful data from the early commissioning phase (before July 2020) are the raster scans on 28-May-2020.
16:05, 16:50 - disk center rasters with 20s exposures
17:50, 18:35 - north limb rasters with 20s exposures
19:35, 20:20 - south limb rasters with 20s exposures
21:20, 22:05 - west limb rasters with 20s exposures
23:05, 23:47 - east limb rasters with 20s exposures
The first true science observations were obtained during 18 to 22 November 2020. For example, an active region can be seen in the raster beginning 19:57 UT on 18-Nov-2020.
Ingesting downloaded data
After you have downloaded some SPICE FITS files, you can ingest them into your data directory with spice_ingest:
IDL> spice_ingest, files
This routine automatically creates the sub-directory structure (year/month/day) within $SPICE_DATA for the files.
Finding and reading a FITS file
Once a file has been ingested, then you can find it with spice_find_file using the observation time:
IDL> file=spice_find_file('28-may-2020 16:05')
A file can be read into an IDL object with:
IDL> d=spice_object(file)
Extracting information from the data object
The table below gives some methods for extracting information out of the data object. Where “i” is given, it means the index of a wavelength window should be specified (indices begin at 0).
You can get a list of all methods by doing:
IDL> d→help
| Command | Function |
|---|---|
| d→get_number_windows() | No. of spectral windows |
| d→get_window_data(i,/load) | Extract a data window |
| d→get_lambda_vector(i) | Get wavelength vector for the window |
| d→get_header(i) | Extract a data window header |
| d→get_window_id(i) | Get the data window ID |
| d→get_start_time() | Start time of observation |
| d→get_end_time() | End time of observation |
| d→get_sit_and_stare() | Set to 1 if sit-and-stare observation |
| d→get_number_exposures() | Number of exposures in raster |
| d→get_xcen(i) | Get the X-center for the window |
| d→get_ycen(i) | Get the Y-center for the window |
Quicklook tools
A set of five widget-based tools are available for browsing SPICE data, and these can be accessed through spice_xfiles:
IDL> spice_xfiles
This allows you to select a FITS file from your SPICE data directory. A new widget appears from which you can then select one of the five quicklook tools: Detector, Raster Browser, Raster, Whisker and Intensity map. These tools mimic software that were available for EIS and IRIS.
For further details, please visit the SPICE Quicklook and Data Analysis Software Page.
Raster Browser
This is useful for browsing the 3D data cubes from SPICE rasters. In addition to being called from spice_xfiles (see above), it can also be called directly from the command line:
IDL> spice_raster_browser,file
Use a 3-button mouse to browse the images and spectra: the middle button allows you to select a new pixel, the left button zooms in and the right button zooms out.
Ephemeris information
You can access ephemeris information from the SPICE headers. For example, the keywords:
DSUN_AU - distance of the spacecraft from the Sun in AU
EAR_TDEL - light travel time from the spacecraft to Earth (seconds)
The full list of keywords is given in the DPDD - search for “Solar ephemeris keywords”.
Users should make sure to correct the SPICE observing times for EAR_TDEL in order to compare with observations from Earth-orbiting spacecraft. This is especially important for highly-dynamic structures such as flares or CMEs.
Read and display data (Python)
Links:
Analyze data
Instrument performance
Calibration reports (links)
Data calibration applied to L2 data (links)
Known instrumental artefacts: see release notes.
Line fitting
TBW
