Erebus GPS timeseries

We use NASA's Jet Propulsion Laboratory's (JPL) GipsyX software in PPP mode with ambiguity resolution applied to 24 hour segments of data to generate daily position solutions. We use JPL's orbit and clock products and International GNSS Service (IGS) antenna phase center models. Where...

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Bibliographic Details
Main Author: Grapenthin, Ronni
Format: Dataset
Language:English
Published: U.S. Antarctic Program (USAP) Data Center 2021
Subjects:
GPS
Online Access:https://dx.doi.org/10.15784/601471
https://www.usap-dc.org/view/dataset/601471
Description
Summary:We use NASA's Jet Propulsion Laboratory's (JPL) GipsyX software in PPP mode with ambiguity resolution applied to 24 hour segments of data to generate daily position solutions. We use JPL's orbit and clock products and International GNSS Service (IGS) antenna phase center models. Where available, we use JPL's second order ionospheric corrections, otherwise we fall back on those provided by the IGS. To correct tropospheric delays, we use the GPT2 model as implemented in GipsyX. Ocean tidal loading corrections utilize the TPXO7.2 and ATLAS model, a combination of hydrodynamic model and altimetry data, with respect to Earth's Center of Mass implemented in SPOTL. We obtain position solutions for each station day in a fiducial-free reference frame, which we then transform into the 2014 International Reference Frame using JPL's transformation coefficients and generate timeseries of position change relative to the first epoch, given in the *.series files which are ASCII files with the following columns: decimal year displacement east (m) displacement north (m) displacement up (m) sigma east (m) sigma north (m) sigma up (m) east-north covariance east-up covariance north-up covariance Year (YYYY) Month (MM) Day (DD) Hour (hh) Minute (mm) Second (ss) Solution path We generate position time series relative to stable Antarctic plate by removing the plate velocities modeled by Argus et al (2010). These are provided in the *.npy files that be readily read into python scripts: pos_ts = np.load('test.npy').flatten()[0] pos_ts['itrf'] provides the ITRF data as above pos_ts['plate'] provides the data with Antarctic plate motion removed.