This data set contains a record of speeds for vertically-propagating compression-waves measured throughout the depth of ice that surrounds the WAIS-D borehole. Multiple logs provide redundant measurements for all depths. Data for individual wave-speed measurements were included, as well as 3 m running averages for each log. A Takeaway Profile that represents our interpretation of the combined data set is also included.
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WAIS Divide Sonic Log Data, Version 1
Geographic Coverage
Spatial Coverage: |
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Spatial Resolution: |
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Temporal Coverage: |
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Temporal Resolution: | Not specified |
Parameter(s): |
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Platform(s) | GROUND STATIONS |
Sensor(s): | PROBES |
Data Format(s): |
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Version: | V1 |
Data Contributor(s): | Edwin Waddington, Kenichi Matsuoka, Dan Kluskiewicz, Michael McCarthy, Sridhar Anandakrishnan |
Metadata XML: | View Metadata Record |
Data Citation
As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.
Waddington, E. D., D. Kluskiewicz, K. Matsuoka, M. McCarthy, and S. Anandakrishnan. 2014. WAIS Divide Sonic Log Data, Version 1. [Indicate subset used]. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: http://dx.doi.org/10.7265/N5T72FD2. [Date Accessed].Detailed Data Description
This data set contains a record of speeds for vertically-propagating compression-waves measured throughout the depth of ice that surrounds the WAIS-D borehole. Multiple logs provide redundant measurements for all depths. We include data for individual wave-speed measurements, as well as 3 m running averages for each log. We also include a takeaway profile that represents our interpretation of the combined data set. Refer to Figure 1. It is a running average of the best parts of our sonic logs, and has 200 m resolution for the upper 2300 m of ice and 3 m resolution for ice below 2300 m. The change in resolution is because of pervasive error in our logs for the upper 2300 m of ice.

Data are provided in tab-delimited text (.txt) format.
Data are available on the FTP site in the ftp://sidads.colorado.edu/pub/DATASETS/AGDC/nsidc0592_waddington directory. Within this directory, there are two folders, individual runs and takeaway profile. In the individual runs folder, there are seven subfolders, two for each date (except Dec. 8) for direction of the tool motion (Up/Down). Each subfolder contains two text files: one for the individual measurements and one with three meter averages. The takeaway profile folder contains one data summary file: WAIS_Sonic_Profile.txt and one image file: smoothProfile.png. Each text file has two columns. The first column contains depth in meters, and the second column contains velocity in meters per second.
This section explains the file naming convention used for this product with an example.
Example File Names: WAIS_Dec_12_Up_3m_avr.txt
WAIS_mmm_dd_up/down_3m_avr.txt
Refer to Table 2 for the valid values for the file name variables listed above.
Where:
Variable | Description |
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WAIS | Cores collected through the WAIS (West Antarctic Ice Sheet) project. |
mmm | 3-digit month |
dd | 2-digit day |
up/down | Direction of tool motion (Up or Down) |
3m_avr | 3 meter average |
Files range from 7.9 KB to 1.7 MB.
8 MB
WAIS Divide, Antarctica: 79.467° S, 112.085° W
Spatial Resolution
Wave-speed measurements range from ~3 m (below 2300 m) to ~200 m (2300 m and higher)
Data were collected from 08 December 2011 to 03 January 2012.
Depth (m)
Velocity (m/s)
Sample Data Record
Figure 2 is sample data from the WAIS_Sonic_Profile.txt data file.

Software and Tools
Data Acquisition and Processing
Sonic methods provide a continuous record of Crystal Orientation Fabric (COF) throughout the entire depth of ice surrounding the WAIS core. An ice crystal is stiffer along its c-axis than orthogonal to it. As a consequence, p- (compressional) waves travel fastest in ice that has crystal c-axes oriented along the direction of wave propagation. The data reports velocities for vertically-traveling p-waves, which are a proxy for vertical clustering of ice crystal c-axes.
Wave Speed Measurements
The 2SAA-1000-F Sonic Probe tool measures the propagation time for p-waves that travel vertically along the ice surrounding the borehole wall. The arrival times of active-source signals that are separated by a vertical distance of 3 m was recorded. This signal travels from a source at the bottom of the tool, through the borehole fluid, along the borehole wall, and back through the fluid to each receiver. Because of the geometry of the borehole, ice, and logging tool, the p-wave speed, Vp, in the sampled ice can be measured as the distance between receivers, δ, divided by the difference between arrival times Δt.
Vp = δ/Δt
Temperature and Pressure
Sound wave velocities in ice are affected by temperature and pressure. In order to correct for this effect, the velocities need to be adjusted as:
Vp-corr. = Vp - A * (T - Tr) - B * p
Where:
A = -2.7 m/s⋅K
B = .2 m/s⋅Mpa
Tr = -16°C
Fabric Inference
The speed of a vertically propagating p-wave is a proxy for the vertical clustering of ice crystal c-axes. For a given fabric, the compression wave speed Vp can be approximated using the average of the slownesses that would be expected for the same wave travelling through each individual crystal:

Where N is the number of crystals. In order to predict crystal fabric from a 1-component velocity measurement, it is necessary to make assumptions about the type of fabric being measured. For a simple translation from sound speeds to COF eigenvalues, we consider hypothetical COFs for which crystal c-axes are uniformaly distributed within a certain range of zenith angles, as in the girdle/cone angles described by Bennet (1968). For a description of eigenvalues as a fabric description, see Gusmeroli et al. (2012) or Gagliardini et al. (2009). A relationship between compression-wave velocities and fabric eigenvalues is shown in Figure 4. Pole fabrics are paramaterized by eigenvalue λ1, girdles by λ3. λ1 = 1 for a pure single pole; λ1 = λ2 = λ3 = .33 for an isotropic fabric; λ3 = 0 for a pure vertical girdle. In general, λ1 + λ2 = λ3 = 1. Wave speed predictions for ice crystal aggregates are sensitive to elasticity constants for the individual crystals; different studies claim different values for these constants, and lead to substantially differing (+- 75 m/s) wave speed prediction. The depicted relationship follows from elasticity constants measured by Dantle as described and recommended in Gusmeroli et al. (2012).

Error Sources
The method for measuring sound wave velocities is most accurate when the receivers and emission source are centered in the ice borehole. The primary source of error for our logs is off-center drift for these components; this can result in systematic error as is evident in the separation between Vp measurements in repeat logs, and in velocity 'streaks' (abrupt, transient shifts in velocity with depth) that are not seen in repeat measurements at the same depth. Both are most prevalent in upper 2000 m of ice and are minimal below 2300 m (see Figure 5). There is also noise in the data associated with error in wave-arrival picks and short term movement of the tool components while logging. We estimate a .5 µs error in arrival time picks, which accounts for approximately +- 2.5 m/s of error for Vp; this is small compared to error from receiver drift. Unfortunately, errors for our velocity measurements above 2300 m depth are too pervasive and large for us to accurately describe crystal fabric. Below 2300 m, low noise and trend agreement between redundant measurements lend confidence that our Vp measurements correspond to crystal orientation fabric and represent real abrupt fabric changes.

References and Related Publications
Contacts and Acknowledgments
Edwin Waddington
University of Washington
Department of Earth and Space Sciences
Seattle, WA 98195-1310
Dan Kluskiewicz
University of Washington
Department of Earth and Space Sciences
Seattle, WA 98195-1310
Kenichi Matsuoka
Norwegian Polar Institute
Fram Center, N-9296
Tromsø, 9296, NORWAY
Michael McCarthy
University of Washington
Department of Earth and Space Sciences
Seattle, WA 98195-1310
Sridhar Anandakrishnan
Department of Geosciences
Penn State
442 Deike Building
University Park, PA 16802
This research was supported by NSF Division of Polar Programs (PLR) Grant Number 0944199
Document Information
Document Creation Date
August 25, 2014
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