IERS data access (astropy.utils.iers)#


The iers package provides access to the tables provided by the International Earth Rotation and Reference Systems (IERS) service, in particular the Earth Orientation data allowing interpolation of published UT1-UTC and polar motion values for given times. The UT1-UTC values are used in Time and Dates (astropy.time) to provide UT1 values, and the polar motions are used in astropy.coordinates to determine Earth orientation for celestial-to-terrestrial coordinate transformations.


The package also provides machinery to track leap seconds. Since it generally should not be necessary to deal with those by hand, this is not discussed below. For details, see the documentation of LeapSeconds.

There are two IERS data products that we discuss here:

  • Bulletin A (IERS_A) is updated weekly and has historical data starting from 1973 and predictive data for 1 year into the future. It contains Earth orientation parameters x/y pole, UT1-UTC and their errors at daily intervals.

  • Bulletin B (IERS_B) is updated monthly and has data from 1962 up to the time when it is generated. This file contains Earth’s orientation in the IERS Reference System including Universal Time, coordinates of the terrestrial pole, and celestial pole offsets.

Since astropy v6.0, both files are provided by the astropy-iers-data package, which is automatically installed when astropy itself is installed.

Getting started#

By default, files are used from the astropy-iers-data package which is regularly updated.

In some cases, the latest IERS-A values (which include approximately one year of predictive values) may be automatically downloaded from the IERS service as required. This happens when a time or coordinate transformation needs a value which is not already available via existing files in astropy-iers-data. In most cases there is no need for invoking the iers classes oneself, but it is useful to understand the situations when a download will occur and how this can be controlled.

Basic usage#

By default, the IERS data are managed via instances of the IERS_Auto class. These instances are created internally within the relevant time and coordinate objects during transformations. If the bundled files or the astropy data cache are not recent enough then astropy will request the file from the IERS service. Here is an example that shows the typical download progress bar:

>>> from astropy.time import Time
>>> t = Time('2016:001')
>>> t.ut1  
|==================================================================| 3.0M/3.0M (100.00%)         6s
<Time object: scale='ut1' format='yday' value=2016:001:00:00:00.082>

Note that you can forcibly clear the download cache as follows:

>>> from import clear_download_cache
>>> clear_download_cache()  

The default IERS-A data used automatically is updated by the service every 7 days and includes transforms dating back to 1973-01-01.


The IERS_Auto class contains machinery to ensure that the IERS table is kept up to date by auto-downloading the latest version as needed. This means that the IERS table is assured of having the state-of-the-art definitive and predictive values for Earth rotation. As a user it is your responsibility to understand the accuracy of IERS predictions if your science depends on that. If you request UT1-UTC or polar motions for times beyond the range of IERS table data then the nearest available values will be provided.

Configuration parameters#

There are a number of IERS configuration parameters in astropy.utils.iers.Conf that relate to automatic IERS downloading. Four of the most important to consider are the following:


Enable auto-downloading of the latest IERS data. If set to False then the local IERS-A and IERS-B files will be used by default (even if the full IERS file with predictions was already downloaded and cached). This parameter also controls whether internet resources will be queried to update the leap second table if the installed version is out of date.


Maximum age of predictive data before auto-downloading (days). See next section for details. (default=30)


Remote timeout downloading IERS file data (seconds)


Some time conversions like UTC -> UT1 require IERS-A Earth rotation data for full accuracy. In cases where full accuracy is not required and downloading the IERS-A is not possible or desired (for instance running on a cluster) then this option can be set to either 'warn' or 'ignore'. The default is 'error' which will raise an exception if full accuracy is not possible for a time conversion, 'warn' will issue a warning, and 'ignore' will ignore the problem and use available IERS-B data.

Auto refresh behavior#

The first time that one attempts a time or coordinate transformation that requires IERS data, if the bundled versions of the files in astropy-iers-data are not recent enough, the latest version of the IERS table (from 1973 through one year into the future) will be downloaded and stored in the astropy cache.

Transformations will then use the cached data file if possible. However, the IERS_Auto table is automatically updated in place from the network if the following two conditions a met when the table is queried for UT1-UTC or polar motion values:

  • Any of the requested IERS values are predictive, meaning that they have been extrapolated into the future with a model that is fit to measured data. The IERS table contains approximately one year of predictive data from the time it is created.

  • The first predictive values in the table are at least conf.auto_max_age days old relative to the current actual time (i.e. This means that the IERS table is out of date and a newer version can be found on the IERS service.

The IERS Service provides the default online table (set by astropy.utils.iers.IERS_A_URL) and updates the content once each 7 days. The default value of auto_max_age is 30 days to avoid unnecessary network access, but one can reduce this to as low as 10 days.

Working offline#

If you are working without an internet connection and doing transformations that require IERS data, there are a couple of options.

Ensure astropy-iers-data is up to date

If you are planning to work without an internet connection, we recommend updating the astropy-iers-data package to the latest available version, using e.g., pip or conda, as this will ensure that you have the most recent IERS and leap second data.

Disable auto downloading

Here you can do:

>>> from astropy.utils import iers
>>> iers.conf.auto_download = False  

In this case any transforms will use the bundled IERS data which are included in the astropy-iers-data package and include data up to the release date of that package (which is why it is important to ensure that package is up to date as described above). Any transforms outside of this range will not be allowed.

Set the auto-download max age parameter

Only do this if you understand what you are doing, THIS CAN GIVE INACCURATE ANSWERS! Assuming you have previously been connected to the internet and have downloaded and cached the IERS auto values previously, then do the following:

>>> iers.conf.auto_max_age = None  

This disables the check of whether the IERS values are sufficiently recent, and all the transformations (even those outside the time range of available IERS data) will succeed with at most warnings.

Allow degraded accuracy

Only do this if you understand what you are doing, THIS CAN GIVE INACCURATE ANSWERS!

Set astropy.utils.iers.conf.iers_degraded_accuracy to either 'warn' or 'ignore'. These prevent the normal exception that occurs if a time conversion falls outside the bounds of available local IERS-B data.

Direct table access#

In most cases the automatic interface will suffice, but you may need to directly load and manipulate IERS tables. IERS-B values are provided as part of astropy and can be used to calculate time offsets and polar motion directly, or set up for internal use in further time and coordinate transformations. For example:

>>> from astropy.utils import iers
>>> t = Time('2010:001')
>>> iers_b =
>>> iers_b.ut1_utc(t)  
<Quantity 0.1141359 s>
>>> iers.earth_orientation_table.set(iers_b)
<ScienceState earth_orientation_table: <IERS_B length=...>...>
>>> t.ut1.iso
'2010-01-01 00:00:00.114'

Instead of local copies of IERS files, one can also download them, using iers.IERS_A_URL (or iers.IERS_A_URL_MIRROR) and iers.IERS_B_URL, and then use those for future time and coordinate transformations (in this example, just for a single calculation, by using earth_orientation_table as a context manager):

>>> iers_a =  
>>> with iers.earth_orientation_table.set(iers_a):  
...     print(t.ut1.iso)
2010-01-01 00:00:00.114

To reset to the default, pass in None (which is equivalent to passing in

>>> iers.earth_orientation_table.set(None)  
<ScienceState earth_orientation_table: <IERS...>...>

To see the internal IERS data that gets used in astropy you can do the following:

>>> dat = iers.earth_orientation_table.get()  
>>> type(dat)  
<class 'astropy.utils.iers.iers.IERS...'>
>>> dat  
<IERS_Auto length=16196>
 year month  day    MJD   PolPMFlag_A ... UT1Flag    PM_x     PM_y   PolPMFlag
                     d                ...           arcsec   arcsec
int64 int64 int64 float64     str1    ... unicode1 float64  float64   unicode1
----- ----- ----- ------- ----------- ... -------- -------- -------- ---------
   73     1     2 41684.0           I ...        B    0.143    0.137         B
   73     1     3 41685.0           I ...        B    0.141    0.134         B
   73     1     4 41686.0           I ...        B    0.139    0.131         B
   73     1     5 41687.0           I ...        B    0.137    0.128         B
  ...   ...   ...     ...         ... ...      ...      ...      ...       ...
   17     5     2 57875.0           P ...        P 0.007211  0.44884         P
   17     5     3 57876.0           P ...        P 0.008757 0.450321         P
   17     5     4 57877.0           P ...        P 0.010328 0.451777         P
   17     5     5 57878.0           P ...        P 0.011924 0.453209         P
   17     5     6 57879.0           P ...        P 0.013544 0.454617         P

The explanation for most of the columns can be found in the file named iers.IERS_A_README. The important columns of this table are MJD, UT1_UTC, UT1Flag, PM_x, PM_y, PolPMFlag:

>>> dat['MJD', 'UT1_UTC', 'UT1Flag', 'PM_x', 'PM_y', 'PolPMFlag']  
<IERS_Auto length=16196>
  MJD    UT1_UTC   UT1Flag    PM_x     PM_y   PolPMFlag
   d        s                arcsec   arcsec
float64  float64   unicode1 float64  float64   unicode1
------- ---------- -------- -------- -------- ---------
41684.0     0.8075        B    0.143    0.137         B
41685.0     0.8044        B    0.141    0.134         B
41686.0     0.8012        B    0.139    0.131         B
41687.0     0.7981        B    0.137    0.128         B
    ...        ...      ...      ...      ...       ...
57875.0 -0.6545408        P 0.007211  0.44884         P
57876.0 -0.6559528        P 0.008757 0.450321         P
57877.0 -0.6573705        P 0.010328 0.451777         P
57878.0 -0.6587712        P 0.011924 0.453209         P
57879.0  -0.660187        P 0.013544 0.454617         P