Processed line aerogravity data over the Thwaites Glacier region (2018/19 season) ...
Aerogravity data has an important role to play in constraining sub-surface geology under grounded ice and bathymetry beneath floating ice shelves. This dataset contains aerogravity collected by the British Antarctic Survey as part of the International Thwaites Glacier Collaboration (ITGC). Data were...
Main Authors: | , , , , |
---|---|
Format: | Dataset |
Language: | English |
Published: |
UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation
2020
|
Subjects: | |
Online Access: | https://dx.doi.org/10.5285/b9b28a35-8620-4182-bf9c-638800b6679b https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/01241 |
Summary: | Aerogravity data has an important role to play in constraining sub-surface geology under grounded ice and bathymetry beneath floating ice shelves. This dataset contains aerogravity collected by the British Antarctic Survey as part of the International Thwaites Glacier Collaboration (ITGC). Data were collected using both a traditional stabilised platform approach, and a more modern strapdown gravity system. Flights were flown at a constant altitude ~450 m above the ice surface where surface topography was flat. Gravity data is also recovered along draped sections by the strapdown system. In total 9872 km of data is presented, of this 6033 km was collected in the main survey area, while other data was collected on input and output transit flights. The aircraft used was the BAS twin otter VP-FBL equipped for aerogeophysical surveys. Data are available in ASCII file format (.xyz). Three databases are provided with aerogravity data: one with the Strapdown processing flow, a second with the LaCoste & Romberg ... : PROCESSING: Gravity data during the ITGC survey were collected using both a strapdown (Jordan and Becker 2018) and traditional stabilised platform approach (Valliant 1992). The initial strapdown gravity signal was recovered from raw INS and GPS data using a Kalman filtering technique implemented in the TerraPos GPS processing software. Raw data were processed in a tightly coupled manner solving for gravity, position, and sensor orientation simultaneously. Ionospheric and clock errors were solved using Precise Point Positioning (PPP) technique with accurate satellite clock and orbit corrections used in the 'Final' ephemeris data downloaded more than a month after the survey was completed. The applied Kalman filter included a gravity smoothing filter assuming a 5km gravity correlation constant and 10 mGal permitted standard deviation. In order to minimise thermal effects on the QA2000 accelerometers, the IMU was warmed up from ambient temperatures inside an insulating enclosure for at least three hours before ... |
---|