Data Set ID:
NSIDC-0592

WAIS Divide Sonic Log Data, Version 1

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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NSIDC does not archive these data.

Geographic Coverage

Parameter(s):
  • Sea Ice > Ice Depth/Thickness > Depth
  • Snow/Ice > Ice Velocity
Spatial Coverage:
  • N: -79.467, S: -79.467, E: -112.085, W: -112.085

Spatial Resolution:
  • 3 m to 200 m
Temporal Coverage:
  • 8 December 2011 to 3 January 2012
Temporal Resolution: Not specified
Data Format(s):
  • ASCII Text
Platform(s) GROUND STATIONS
Sensor(s): PROBES
Version: V1
Data Contributor(s): Edwin Waddington, Kenichi Matsuoka, Dan Kluskiewicz, Michael McCarthy, Sridhar Anandakrishnan
Please contact the data provider for the correct Data Citation for this data set.

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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.

velocity profile
Figure 1. Smoothed Velocity Profile
Format

Data are provided in tab-delimited text (.txt) format.

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File and Directory Structure

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.

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File Naming Convention

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:

Table 2. File Naming Convention
Variable Description
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
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File Size

Files range from 7.9 KB to 1.7 MB.

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Volume

8 MB

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Spatial Coverage

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)

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Temporal Coverage

Data were collected from 08 December 2011 to 03 January 2012.

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Parameter or Variable

Depth (m)
Velocity (m/s)

Sample Data Record

Figure 2 is sample data from the WAIS_Sonic_Profile.txt data file.

sample data
Figure 2. Sample Data Record
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Software and Tools

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Data Acquisition and Processing

Theory of Measurements

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.

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Derivation Techniques and Algorithms

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

(Equation 1)

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

(Equation 2)

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:

equation 3
(Equation 3)

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).

equation 3
Figure 4. Vp for Different Single Pole and Vertical Girdle Fabrics.

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.

individual velocities
Figure 5. Individual Velocity Measurements
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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

Acknowledgments: 

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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