Data Processing for NECKLACE

Standardised processing methods for NECKLACE contributions are still under development. For now, we suggest that contributors apply a monthly mean through their processed timeseries, and provide details of their processing method.

Some potential issues during ApRES data processing to watch out for:

  • Has there been any clipping of the signal? Clipping has been known to result in artefacts and can cause miscalculation of internal ice thickness changes (see Vaňková et al. 2020)
  • Does the internal strain rate change over time? This can occur on tidal, fortnightly, and longer-term timescales depending on local ice dynamics.
  • Is the most prominent basal reflector consistent over time? Changes in basal return can occur if nearby basal crevasses change geometry, or can be caused by off-nadir reflectors (see Vaňková et al. 2021).

The NECKLACE team are happy to provide advice and assistance with data processing. Please contact Keith Nicholls

Metadata guidelines for contributors

We strongly recommend that contributors to NECKLACE share raw data from their instruments in an open-access data repository. This will allow us to update the collated dataset as our processing software continues to develop and improve. Most contributors should be able to host data in their National Antarctic Data Centre, but if this facility is not available then Pangaea provides a good free alternative. Many data centres allow data to be embargoed for a period to allow the field team first right of publication.

We have created some guidelines to help make sure that all NECKLACE-related datasets have appropriate metadata and can be linked easily to the NECKLACE project. See the downloadable document below.

Converting raw data to netCDF

Paul Breen from the NERC Polar Data Centre, located at BAS, has developed a Python package to convert binary ApRES .DAT files into netCDF format, suitable for archiving at data centres requiring open access formatting. The package also contains code to revert to a .DAT file that is byte-identical to the original data file. This will allow processing scripts developed for the original .DAT files can be used on re-converted versions of data retrieved from data centres.

The code does not work on data from older RMB1 instruments. Two other limitations, which will be relaxed in future releases, are that the code does not handle datasets using multiple antennas pairs (ie MIMO configurations); nor does it currently handle cases where nAttenuators>1.

The package can be installed into a suitable Python environment with: pip install bas-apres

Release information can be found below