3. IRIS Level 2 Data

IRIS Level 2 data can be retrieved from the mission web page [http://iris.lmsal.com/search] or through the European Hinode/IRIS Science Data Center [http://sdc.uio.no]. The IRIS Level 2 files are designed to allow the user to easily read and access the data and keywords contained in IRIS Level 2 FITS files.

The IRIS Level 2 data files have been designed to allow easy access to the data using the IRIS QL software, e.g., the widgets called iris_xfiles and CRISPEX.

3.1. What Are IRIS Level 2 FITS Files?

IRIS Level 2 data are the combination of individual frames for the duration of a given observing sequence (defined by an OBSID number). For a given sequence, there are two kinds of FITS files, grouped by observable:

  1. SJI FITS - files of the 1330, 1400, 2796, or 2832 slit-jaw filters
  2. Spectrograph FITS - FITS files containing the FUV1/2 and NUV spectrograph images

In each case the FITS files have binary tables corresponding to each frame and/or raster step. Therefore, the IRIS Level 2 data are arranged as:

  • SJI = FITS [Spatial X, Spatial Y, Time]
  • SG = FITS [[NUV, FUV1, FUV2](λ), Spatial Y, Spatial X OR Time]

The typical mode is a raster, where IRIS has been commanded to scan across a solar region, the third dimension is a spatial one (depending on the roll angle of the spacecraft). Naturally, because the spectrograph takes time to compose a raster image the third dimension also reflects some temporal evolution.

For IRIS “sit-n-stare” observations (where IRIS slit is pointed at one solar location taking continuous data) the third dimension contains each exposure arranged by time in the FITS file.

For repeated IRIS rasters of the same region (observations that have the same OBSID) the spectrograph FITS files of each raster in the sequence form an ordered series. These repeated raster Level 2 FITS files are amenable to analysis by CRISPEX, the IRIS Level 3 data manipulation tool (see below).

3.2. Searching and Downloading

3.2.1. Using the IRIS Data Search Webpage

The IRIS data search webpage (http://iris.lmsal.com/search) is designed to quickly guide researchers to IRIS datasets appropriate for their research. It consists of five graphical elements and three steps to the data:

  1. IRIS Banner
  2. Selection widgets
  3. Graphical display of search results on a solar image
  4. Tabular display of search results
  5. Dataset browser/inspector with links to download the data sets

The IRIS data search tool is optimized for use on landscaped displays of at least 1280x768 pixels. The banner and the solar image can be hidden (displayed) by clicking on the red (green) buttons in their upper left corners to accommodate smaller screens. The tool has been tested with recent versions Firefox, Safari and Chrome browsers. If you have difficulty with the tool, you might first try one of these.


IRIS search sample screenshot


IRIS search selection widgets

Selection widgets: There are six widgets available for customized, dynamic, data searches. At the most basic this search consists of specifying the start and end of a time range of interest. When first loaded these default to select the a week surrounding the current date. The start and end times can be moved forward and back a day or a week by using the single and double arrow buttons. Specific dates can be entered directly into the text boxes or by using the calendars that popup when one clicks on them. The total count of datasets available within the time range appears at the bottom left of this selection area. By default, only datasets that are completely processed are displayed. If you wish to include ones that are still processing, uncheck the only Obs with data box below count (not shown in figure).

The remaining widgets are used to filter the selections within the specified time range. The count of available data sets updates dynamically to reflect the effects of your selections.

Raster: Limit results to datasets with rasters within a (min, max) range of: fields of view in arcseconds; number of repeats (count); and of the cadence in seconds and with raster steps within a range of number (count); size in arcseconds and cadence in seconds.

Slit Jaw Imager (SJI): Limit results to datasets with slitijaw images within a range of fields of view and cadences for each wavelength band.

Exposure time: Limit results to datasets within a range of minimum exposure and mean exposure times based on all images within the dataset.

Target: Limit results to a range of target positions relative to disk center in arcseconds either as an bounding box (xcen, ycen) or an annulus between radii. Limit sets to specific IRIS Observation IDs or target. The colors of these last two change to indicate the presence (green) or absence (red) of matching datasets based upon other selections.

When all selections are made, clicking the search button refreshes the results in the display area. Note that the display does not update while you are constructing a search. A range of background SDO/AIA images of the sun corresponding to the start time of query can be selected for the display. All filters (other than dates) and displays are cleared by clicking the reset button.


IRIS search display widget

Display Widget: The results of a search are displayed on a co-temporal AIA image that is selectable from the search widget. The default setting displays the bounding boxes for the slit jaw (raster) image as green (red) rectangles on an 193 Å AIA image. Unchecking the boxes button in the search widget displays IRIS logos instead of bounding boxes. A sortable list of IRIS observations on the right presents details of the dataset including the time interval, short descriptions, pointing, fields of view, cadences and observation IDs. Clicking on an entry in either widget, highlights the selection in the table (and in the image when logos are displayed) along with a detailed description in the inspection widget.


IRIS search inspection widget

Inspection Widget: The inspection widget shows more details of the dataset, including a thumbnail slitjaw image, pointing information and links to and sizes of the data products (when they become available). Clicking on the image or title will bring up a separate details page with summary movies, paths to the data and links to the AIA cutout service. Clicking on the data links will immediately download the corresponding gzipped dataset.

3.2.2. Using SSW IDL

IRIS Level 2 data can be accessed via the SSW command line using a simple extension of the IDL/SSW timeline queries used above. So, our earlier example:

IDL> t0 = '2013-08-20 00:00:00' & t1 = '2013-08-21 00:00:00'
IDL> tl = iris_time2timeline(t0,t1)
IDL> info = get_infox(tl, tag_names(tl), /more)

returns the details of all IRIS observations taken on August 20, 2013. If we want to browse those sequences with OBSID = 4182010156 then we can use the following command to return the internet folders where the IRIS Level 2 data reside for each relevant sequence:

IDL> l2_folder = iris_ssw_l2_query(t0, t1, obsid = 4182010156)
IDL> print, l2_folder

The www subfolder in each example contains a collection of browsable movies of the slit-jaw and spectrograph image sequences taken during the observation like that shown below. These movies can be used to view the data before downloading the (large) Level 2 FITS files.


Browsable movies from data webpage.

Extending this example to a more specific case let’s pick the first of these OBSID = 4182010156 observations and recover the URLs for the IRIS Level 2 FITS files from the command line:

IDL> tmp = where(tl.obsid eq 4182010156)
IDL> tl = tl[tmp[0]]
IDL> l2_fits = iris_ssw_l2_query(tl.DATE_OBS, t1.DATE_END, /fits)
IDL> help, l2_fits
L2_FITS         STRING    = Array[5]
IDL> print, l2_fits

Naturally these files could have been viewed by opening the web folder found earlier. These L2 FITS files can be downloaded to your local folder using a web browser or by using the SSW command:

IDL> sock_copy, l2_fits, dir='./'

Once the files are finished downloading you are ready for the next step - read them or use our tools to dig a little deeper.

3.3. Browsing Level 2 Data with iris_xfiles

One way to browse and manipulate Level 2 IRIS data is to use the widget routine iris_xfiles. This routine is run from the IDL command line as follows:

IDL> iris_xfiles

The iris_xfiles interface appears as below. The search directory window will let you browse your IRIS data directory tree. But in this case it is better to remove the file search filter so that you can see where you are navigating. When navigating double click on a directory name in order to enter the directory.


IRIS_xfiles main interface.

If the user is downloading Level 2 FITS files on a locally mounted drive (like the example we show here) then the user should edit the “search pattern” tab (below) to the folder in which the IRIS Level 2 FITS files are contained. Click on the edit button to change the configuration.

Level 2 FITS files of two types can be picked from the file picker: iris_l2*SJI*.fits & iris_l2*_raster_*.fits which, as we have discussed above, contain the slit jaw images in a given filter taken during an observing sequence, or the spectral images of an observing sequence, respectively.


IRIS_xfiles file picker.

Selecting one of the slit-jaw raster FITS files - by clicking on Confirm Selection, or just double-clicking the file - will bring up the widget called iris_ximovie. iris_ximovie (which can also be used individually on FITS data loaded at the command line) allows the user to view the slit jaw sequence as a movie. It contains a number of options for playback speed, change of magnification, zooming, blinking, and the generation of postscript, jpeg or gif output as well as MPEG movies through the “file/save_as menu”.


iris_ximovie widget.

iris_xfiles can multi-task so you can have multiple analysis/movie/widget windows open simultaneously while you study your data. So, selecting the raster FITS file you will see the following X11 window pop up, the iris_xcontrol widget. In this case the requested raster is read, as are the available slit jaw images that were taken during this particular raster.


iris_xcontrol main interface.

iris_xcontrol (above) is the main control widget for the IRIS L2 quicklook software. It launches an array of other QL widget programs.

An overview of the raster is given in the middle top window that includes the OBSID, the number of raster positions, the number of spectral (line) windows, their wavelength and pixel ranges on the IRIS CCDs as well as their name - the names are usually associated with the principal spectral line in the window.

Many of the other quicklook widgets driven by iris_xcontrol require a line list given by this selectable list. The “Generate Level 3 files” button of iris_xcontrol will generate a set of Level 3 files for analysis like CRISPEX.

The left of the iris_xcontrol widget is an SDO/AIA 171Å image of the Sun taken closest in time to the start of the observation. The location of the IRIS scan or sit-and-stare observation on the Sun is shown as a box or a vertical line respectively. The image, if found, should be current in the sense that it is taken on the same day as the raster. Right clicking on the solar image will toggle between various AIA images. Left clicking will bring up a widget containing a magnified copy of the image including the raster pointing.


iris_xdetector widget.

The lower middle window of iris_xcontrol show the layouts of the spectral windows (or regions) on the NUV (top) and FUV (bottom) CCDs. The lower window shows the combined FUV1 and FUV2 CCDs (see the introduction for further information). Clicking on these windows will start the “Detector” quicklook widget (below) which shows the layout of the spectral windows on the CCDs with options to cycle through the exposures of the raster, plot/print pixel values, change the color table, etc. This widget can also be started by clicking on the “Detector” button. The “Create Animation” button often provides a very interesting movie of the spectral evolution during the observation - particularly for sit-n-stare observations.

The right column of iris_xcontrol shows up to four slit jaw images taken during the raster. Clicking on any of these will bring up a widget (iris_sji_image; see below) containing a magnified image of the slit jaw, sliders to cycle through the slit jaws taken during the raster, and the option to plot the location of the raster exposures taken (compare with iris_ximovie). An instance of ximovie can be started for the SJI sequence by clicking on the button.


iris_sji_image widget.

Below the “Detector” button on iris_xcontrol - in the center of left column - are the buttons for starting the “Browser”, the “Spectroheliogram”, “Whisker” and “Intensity Map” widgets.


iris_xfiles browser.

Browser: The “Browser” is similar to the Hinode/EIS quicklook browser tool (above), and has recently been modified for IRIS. We note that the browser routine (iris_raster_browser) can run independently of iris_xfiles by calling:

IDL> iris_raster_browser, l2f
; where l2f can be an IRIS data object or a Level 2 FITS file

Spectroheliogram: Selecting one or more line windows in the upper left panel of iris_xcontrol and clicking the “Spectroheliogram” button will bring up a widget that contains images of the spectral windows taken during the raster (see below). The spectral movie strips are arranged vertically according to line window and horizontally according to exposure number. Options in the spectroheliogram widget include setting the spectra on pixel or Å wavelength scales and/or pixel or arcsec.


iris_xfiles spectroheliogram.

Whisker: Select one (or more) spectral windows in order to view the windows arranged according to raster position (or exposure number) at a given slit position. This is a widget that presumably is best used for “sit and stare” type observations where one can follow the time evolution of a given location on the sun in a specific spectral line.

Intensity: The new “Intensity Map” function of iris_xfiles is very powerful and will integrate the selected spectral windows over a given range of wavelengths and display the result as an image (see below). This is an excellent tool for examining the wing behavior, or the properties of the complex Mg II h &k (below and left) lines or the C II 1330Å lines.


iris_xfiles intensity map.

By default “Intensity” will integrate over the entire spectral window chosen. However, by clicking on the “Define Line” button parts of the spectral line (or the continuum) can be chosen for integration and presentation in the image window. When “Define Line” is pressed a small widget is brought up (see below) where one can define properties such as the “line start” and “line stop” locations. The integration of the line intensity is done between these locations. Further, when the “Continuum Start” and “Continuum Stop” sliders are used “Intensity” will compute an average intensity of the continuum that is then subtracted from the line intensity integral. The example shown above (for the Mg II h line) shows an image of the integrated core reversal wing minus a small continuum patch in the red wing.


Define line dialong for intensity map or profile moments.

As with the other tools there are options to zoom in on the images, plot pixel values, change color tables and gamma factors in the images, vary between pixel and arcsec spatial scales, etc.

The “Line Fit” gadget: The Line Fit gadget on the iris_xcontrol interface can perform rudimentary spectral analysis of the optically thin FUV lines. It can also be used to inspect the optically thick Mg II and C II lines, but the analysis required for these lines is significantly more complex than this tool permits (see chapter on IRIS Level 3 Data).

The “Profile moments” pull down menu will do simple calculations of line moments (see below), either directly or via Gaussian fits to the selected lines. The results of these calculations will be displayed with the Intensity map tool, now with the possibility of choosing whether to view intensities, velocities, widths, or continuum intensities.


Profile moments dialog.

Running with “moments” is relatively straightforward. This will compute the zeroth (intensity), first (doppler velocity), and second (line width) moments of the intensity profile. First, the “define line” window will pop up, once for each line checked off in the “select line” pane. Thereafter, the “intensity map” tool will pop up with some extra options for displaying the intensity, velocity, or line width of the various lines chosen. The image can be resized, with or without the aspect ratio being retained. The height of this image is the same as that produced by the slit jaw viewer (“xsji_image”) so the images should be directly comparable.

3.4. Reading Level 2 Data in IDL

3.4.1. Using The IRIS Level 2 Data Object

If you wish to look a little deeper and have grabbed some Level 2 IRIS FITS files lets read a set. The IRIS level 2 software is designed to allow the user to easily read and access the data and keywords contained in IRIS level 2 fits files. It is also designed to be used by the IRIS QL software, i.e. those widgets called by iris_xfiles. The software is built up of several objects; iris_data, iris_aux, iris_sji, iris_cal, iris_moment, etc, the most important of which is by far the iris_data object. The casual user does not have to worry too much about this, at least not initially. Let us instead look at some simple examples that show how to read the fits file header, load an IRIS raster window (region) into memory, as well as locate important auxiliary information.

To construct an iris_data object one first need to find a set of iris files. Go to a directory that contains such, or make a text variable “path” that contains the path to iris files. The function iris_files has been constructed to aid in that:

IDL> f = iris_files(path=path)

returns the list of fits files in the directory path (default './') and prints this list on the screen. Then, assuming that f[X] is a level 2 iris raster file:

IDL> d = iris_load(f[X])

This populates the data object with the fits header, auxiliary information, and (pointers to) the data itself. To retrieve the fits header type:

IDL> hdr = d->gethdr(iext, struct=struct)

The function gethdr takes a parameter iext (default 0) which gives the extension to be displayed (remember that the level 2 fits files have a main header “0” and one header for each line window or region). There is one keyword, /struct which when set, return the header as a IDL structure instead of a string array. Or if one wants to look at a specific keyword tag:

IDL> print, d->getinfo('tag')

will produce it. In addition to tag this function takes another parameter iext (default 0) and a keyword sji such that /sji will return the value of the keyword tag in slit jaw header iext.

A very useful procedure at this point is:

IDL> d->show_lines
Spectral regions(windows)
0   1335.71   C II 1336
1   1349.43   Fe XII 1349
2   1351.17   1351
3   1355.60   O I 1356
4   1393.78   Si IV 1394
5   1402.77   Si IV 1403
6   2786.52   2786
7   2796.20   Mg II k 2796
8   2831.33   2831
Loaded Slit Jaw images
0   SJI_1330
1   SJI_1400
2   SJI_2796

which gives an overview of the line(s) and SJI windows loaded into the object. This function only works on raster FITS files, not SJI FITS files.

To actually look at the data, use:

IDL> win = d->getvar(iwin, load=load)

to get data for window number iwin. The win variable now contains a three dimensional array win[lambda, ypos, xpos and/or exposure nr]. The data is by default returned as a pointer to a location in the fits file and that access to the data therefore is through the IDL assoc mechanism. That is:

IDL> dum = win[*,*,12]


IDL> dum = (d->getvar(iwin))[*,*,12]

will contain the 12th exposure (raster position) of window iwin.

If one requires the entire window to be read into memory instead of looking at one exposure at a time, a /load option should be passed to getvar:

IDL> win = d->getvar(iwin, /load)

Note that the /load option will also descale the data (using the descale_array method). At this point you may decide that you have had enough of objects. “Just give me the data”:

IDL> s = d->getdata()

Will return a structure that contains the “entire” object, along with various auxilary information. Note that IRIS level 2 files can be quite large, so do not use this method uncritically. Note that reading in data to the structure may take some time (for reasons that are a bit obscure to this author).

For those sticking with objects, the wavelength lambda for window iwin is given by:

IDL> lambda = d->getlam(iwin)

where iwin can be either the window number or the approximate wavelength of the window (the software will find the window if the wavelength given lies inside the wavelength range of the spectral window).

The slit position (y) is given by:

IDL> y = d->getypos()

The method getypos takes an iwin argument, but all windows share the same y-scale so it is not necessary to specify it. The raster (x) and/or time (t) coordinate are found via:

IDL> x = d->getxpos(iwin=iwin)
IDL> t = d->gettime()

The time returned is relative to STARTOBS, note that you can also get the absolute time via:

IDL> tai=d->ti2tai()    ; Atomic time in seconds
IDL> tutc=d->ti2utc()   ; UT

Here is a simple IDL script that shows how this can be done avoiding the sight of objects all together (the script can be found in the “utils” directory of the SSW distribution):

    if n_elements(extension) eq 0 then extension=0
    d = iris_obj(f)
    hdr = d->gethdr(extension,struct=struct)
    obj_destroy, d
    return, hdr

The gethdr method by default will return the main (extension=0) fits header, but since the various IRIS line windows (regions) are stored as extensions 1, ..., NWIN, there is a small header associated with each which may be useful. Using the struct keyword will return the header as an idl structure instead of as a string array. In the latter case header tags (keywords) can be accessed with the usual SSW fxpar(hdr, tag) routines. Note that since the main header is contained in extension=0, the window headers are accessed as extension=window nr + 1.

In general, this should be the recipe for writing small “one-liners”:

  • open and load the object, viz d = iris_obj()
  • call the methods needed to do what you want to do
  • manipulate and make the output available
  • destroy the object

Other examples (of many, see below) are:

IDL> exp = d->getexp(iexp, iwin=iwin)


IDL> xpos = d->getxpos(indx, iwin=iwin)

to get the exposure time for exposure number iexp or spatial index indx in window number iwin. These functions return an array of exposure times or spatial positions if no parameter iexp or indx is given, and default to the default window (the first one read) if no iwin keyword is given.

Another couple of useful methods for checking the data integrity and ancestry return structures containing the data contained in the latter two fits file extensions after the window data:

IDL> s = d->aux_info() ; extension nwin+1
IDL> s = d->obs_info() ; extension nwin+2

return structures containing these data:

IDL> help, s ; will show their content.

There are a number of objects that are detailed in IRIS Technical Note 28 as are a list of other methods that can be applied to the data. However, if you only want to read the SJI data you can shortcut this with:

IDL> d = iris_sji([{SJI}])
IDL> sji = d->getvar(lwin)

Where the latter command fills the variable sji with the Level 2 slit jaw images contained window lwin.

3.4.2. Using read_iris_l2.pro

IRIS Level 2 FITS files can be read into memory using the read_iris_l2 procedure:

read_iris_l2, l2files, index, data, _extra=_extra, keep_null=keep_null, $
          append=append, silent=silent, wave=wave, remove_bad=remove_bad

where l2files can be an array of Level 2 FITS files. The wave keyword can be used to select a specific wavelength window (e.g., wave = 'Si IV 14') for a raster FITS file. The option has no impact on SJI FITS files. An example call to read_iris_l2 to read an SJI Level 2 FITS file:

IDL> sjifile = 'iris_l2_20131025_050530_3880013447_SJI_1400_t000.fits'
IDL> read_iris_l2,sjifile, index, data
IDL> help, index, data
INDEX           STRUCT    = -> <Anonymous> Array[48]
DATA            FLOAT     = Array[1214, 1092, 48]
IDL> rastfile = 'iris_l2_20131025_050530_3880013447_raster_t000_r00000.fits'
; define the object (see below) - convenient way to show spectral windows
IDL> d = iris_obj(rastfile)     IDL> d->show_lines
Spectral regions(windows)
0   1335.71   C II 1336
1   1393.78   Si IV 1394
2   2796.20   Mg II k 2796
IDL> read_iris_l2,rastfile,index,data, WAVE= 'C II' ; default C II
; other WAVE options in this IRIS line list would be 'Si IV', or 'Mg II'
; NOTE: often there is more than one Si IV and one can extend to the
; string to make it unique
; 'Si IV 13' or 'Si IV 14'
IDL> help, index, data
INDEX           STRUCT    = -> <Anonymous> Array[96]
DATA            FLOAT     = Array[2062, 1092, 96]

where, naturally index and data are arrays that contain the header information for each raster step and the corresponding spectrograph data.

3.5. NUV Data Analysis

3.5.1. Mg II Diagnostics

In the following sub-sections we’ll document a couple of methods to extract physical information from the IRS NUV spectra. These optically thick lines are typically tough to interpret but the IRIS team has done some exploratory work to help the community get as much from the data as possible. The singly ionized Mg II h&k lines (http://adsabs.harvard.edu/abs/1997SoPh..172..109U) provide information that spans from the photosphere to the upper chromosphere (and possibly as high as the transition region).

The image below shows a comparison synthetic and observed Mg II spectra adapter from the paper by Pereira et al. (2013) The h and k emission cores are typically double-peaked - and can be characterized on the violet ‘V’ or red ‘R’ side of the rest wavelength - see the inset.


IRIS Technical Note 37, as well as the three IRIS diagnostic papers from the ITA/UiO team:

provide a comprehensive review of how these parameters can be interpreted in terms of the Bifrost simulations (see IRIS Technical Note 33). The interested IRIS user should consult these papers before studying FUV data in detail. The table below gives a summary of the basic physical properties that can be extracted from the Mg II h&k lines, the bonus being that having two lines that there is some level of comfort in getting consistent measures.

Spectral observable Atmospheric property
\(\Delta v_{k3}\) or \(\Delta v_{h3}\) upper chomospheric velocity
\(\Delta v_{k2}\) or \(\Delta v_{h2}\) mid chromospheric velocity
\(\Delta v_{k3} - \Delta v_{h3}\) upper chromospheric velocity gradient
\(k\) or \(k\) peak separation mid chromospheric velocity gradient
\(k_2\) or \(h_2\) peak intensities chromospheric temperature
\((I_{k2v}-I_{k2r}) / (I_{k2v}+I_{k2r})\) sign of velocity above \(z(\tau=1)\) of \(k_2\)


The above table shows a simplified view, and all the correlations have scatter.

The codes discussed below provide measures of these properties and a few others.

3.5.2. Mg II Line Peak Information Extraction

Tiago Pereira (ITA/UiO) has developed a piece of IDL software which will permit IRIS users to extract properties of the Mg II h&k lines in the NUV spectra. The code, when given an IRIS Level 2 data file, will return the properties of the red peak, blue peak and central reversals of the Mg II h&k line spectra based on a relatively straightforward peak finding algorithm.

The code, iris_get_mg_features_lev2 is executed in the following way:

IDL> myfile = 'iris_l2_20131013_090250_3821104045_raster_t000_r00000.fits'
IDL> d = iris_obj(myfile)
; Find the index of the Mg II window:
IDL> d->show_lines
Spectral regions(windows)
0   1335.71   C II 1336
1   1349.43   Fe XII 1349
2   1355.60   O I 1356
3   1393.78   Si IV 1394
4   1402.77   Si IV 1403
5   2832.75   2832
6   2814.47   2814
7   2796.20   Mg II k 2796
IDL> vr = [-40, 40] ; Velocity Range about line center to search for features
IDL> iris_get_mg_features_lev2, myfile, 7, vr, lc, rp, bp

Sample Mg II h/k velocities obtained with iris_get_mg_features_lev2.

In this example the results are stored in the lc, rp, bp arrays corresponding to the central reversal, red and blue peaks respectively. Each of these arrays is organized [line, feature, slit position, raster position]. The line index corresponds to Mg II k [0] and Mg II h [1]. The feature index corresponds to Doppler shift [0] and intensity [1]. Bad values are marked with NaN. There are also keyword options for calculating these properties for the Mg II h line (/onlyh) or Mg II k line (/onlyk) only. The images below show the h3 and k3 shift from iris_get_mg_features_lev2 and are largely although there are differences which, as indicated in the table, provide information about the line-of-sight component of velocity gradient in the upper chromosphere.

Some of the current limitations of iris_get_mg_features_lev2:

  • Single-peaked profiles off-limb don’t work well - the algorithm was designed for double peaked or strongly shifted single peak (i.e., not for the optically thin regime). See the following sub-section for a possible alternative method.
  • There are many instances where noisy line profiles can represent many peaks in the spectra. In short exposure observations, or complex regions, this presents the biggest problem to the approach. The IRIS team strongly suggests that the user explore different noise filtering to approaches to avoid these issues and identify robust features in the spectra.
  • The line centre properties (k3, h3) are set to NaN when the result is believed to be unreliable. The same setting is used for the peak properties, but it is considerably harder to verify when the peak properties are not reliable, so more ‘dark noise’ will appear in the peak properties.

The ITA/UiO team welcome users to explore, modify and re-share the code given their experiences with it.

3.5.3. Mg II Line Variable Component Fitting

Coming Soon: Document application of the Mg II line fitting approach.

3.6. FUV Data Analysis

3.6.1. “moment” Fitting

Coming Soon: Document application of the moment fitting approach.

3.6.2. Single Gaussian Fitting

Coming Soon: Document application of the SGF fitting approach.

3.6.3. “Red-Blue” Asymmetry Analysis

Coming Soon: Document application of the RB analysis approach.

3.6.4. Double Gaussian Fitting

Coming Soon: Document application of the DGF fitting approach.