Developing a Method for Estimating Accumulation Rates using

Developing a Method for Estimating Accumulation Rates using

Developing a Method for Estimating Accumulation Rates using CReSIS Airborne Snow Radar from
Ryan Lawrence (ECSU), Mentors: Dr. Ian Joughin (UW), Ms. Brooke Medley (UW)
West Antarctica
CONCLUSION
West Antarctica has some of the highest
accumulation rates; however, there is a lot of
uncertainty in those measurements [4]. In contrast to
previous estimates, the Amundsen Sea sector of West
Antarctica and the western Antarctic Peninsula, both
data sparse regions, are found to receive 8096%
more accumulation than previously assumed [4]. For
the Pine Island and Thwaites Glaciers (West
Antarctica), which have recently undergone rapid
acceleration and thinning, this means a downward
adjustment of their contribution to global sea level
rise [4].

ABSTRACT

For more than 50 years, scientists have retrieved ice cores from
the world's ice sheets to study ice dynamics as well as past and
present climatic and atmospheric conditions, including the
accumulation rate. The ice-sheet accumulation rate is not only an
important climate indicator but also a significant component of
ice-sheet mass balance, which is the total mass gained or lost over
a prescribed period of time. Snow accumulation is the primary
mass contributor while ice flux into the ocean and surface melting
are the primary mass loss mechanisms. As concern over sea-level
change and ice-sheet stability increases, more accurate and
spatially complete estimates of the accumulation rate are
required. Therefore, the sparse point estimates of the
accumulation rate (i.e., ice cores) no longer give sufficient data for
regional mass balance estimates because of their limited spatial
coverage, but remain important paleoclimate records due to their
exceptional temporal resolution. In order to constrain current
mass balance estimates at the regional scale, improvement in the
spatial resolution of accumulation rate estimates is necessary.
West Antarctica in particular is seriously lacking in point based
measurements of the accumulation rate, whether through snow
pit or ice core analysis. Climate models show the region along the
Amundsen Coast receives snowfall amounts unprecedented across
most of the continent, yet these models lack any ground-truthing
and are limited in their spatial resolution. Thus, any estimates of
mass balance over this region are ill-constrained and are in need
of much better estimates of the snow accumulation rate.
The spatial pattern of accumulation in West Antarctica will be
determined using the CReSIS developed Snow Radar, which is
capable of imaging near surface layers in the uppermost part of
the ice sheet at a very fine vertical resolution. Estimates of very
recent firn accumulation rates over the Thwaites glacier along the
Amundsen Coast of West Antarctica were calculated using data
from Flight One, Segment 02 of the 10/18/2009 flight.
The short segment layer (~130.76km) mean accumulation
(temporal variation, accumulation rate changing with time) rate
was 0.4m and the long segment layer (~297.874km) was 0.44m.
The standard deviation (how much the accumulation rate varies in
space) for the short segment layer was 0.052m and 0.068m for
the long segment layer. The derived dataset estimates are
within range of previous estimates; however, the continent wide
published estimates do not correspond well with each other or
the specific dataset for Thwaites Glacier.

Figure 3: Several bright firn layers intersect the ITASE
01-2 core site (red line) and the CReSIS accumulation
radar (yellow line). *Note: Image without geospatial
reference due to begin in ArcGIS

METHODOLOGY
During the months of October and November
of 2009, several of NASAs Operation IceBridge
missions flew the CReSIS developed Snow
Radar over West Antarctica (Figure 1) [11];
however, we selected one as our flight of
interest. We then used radar collected during
that flight to map internal layers in the ice
sheet, which we converted to accumulation
rates with knowledge of the layer ages and the
firn density profile. To calculate the
accumulation rate, the total mass of snow
above a layer was divided by the age the layer
was deposited.

RESULTS AND DISCUSSION
Two radar segments were mapped, which are
referred to as the short segment (130 km)
and the long segment (297 km) (Figure 7).
Two measurements, the variation in mean
and the standard deviation, were examined.
The variation in mean is a measurement of
the temporal variation in the accumulation
rate, or how much the accumulation rate
changes with time. Thus, it was important to
map very recent firn deposits, past firn
deposits, and document the age of each
layer. The standard deviation is a measure of
spatial variation, or how much the
accumulation rate varies in space, along the
flight path. Mathematically, if the standard
deviation is low, the accumulation rate is
consistent and does not change much.
However, if it is high, accumulation rates vary
along the flight path significantly. Figure 8
shows the average variation in mean and the
standard deviation for the short and long
segment.

Figure 4: Potentially due to radar operation issues, there
are information gaps. These information gaps can omit
temporal and geospatial data ranging from shallow layers
to deeper layers, as well as spanning meters to several
kilometers of data when exported to ArcMap and
geospatially (latitude and longitude) referenced.

Figure 1: An aerial map depicting the sixth flight paths
using the CReSIS developed snow radar over West
Antarctica, and the ITASE core site, during the months of
October and November of 2009 during NASAs Operation
IceBridge Missions [11].

Figure 2: Flight 1 of the 10/18/2009 Operation IceBridge
Mission shown in ArcMap intersecting the ITASE 01-2
core site and geospatially covering the interior glacial
region of the Thwaites Glacier.

Table I: Listed below are the published accumulation rate datasets for the entire Antarctic continent, specifically
detailing the values for 1) variation in mean and 2) standard deviation [14][15] [16].
Author

Figure 5: Bright firn layers are spatially shown; however,
there is a place of poor spatial and temporal quality (as
encompassed by the red oval) in the radar echogram.

Figure 6: Several digitized firn layers beginning at the
ITASE 01-2 core site which were used in estimating the
accumulation rates for the Thwaites Glacier.

Figure 7: The digitized short and long segments
along the 10/18/2009 Operation IceBridge Flight 1 Segment 02, as well as the ITASE core site is shown in
ArcMap.

NSF REU ANT-0944255: CReSIS - NSF FY 2005-108CM1

Figure 8: Average measurements of the dataset derived
for the Thwaites Glacier region utilizing data collected
from the snow radar. The short segment has a
variation in mean accumulation of 0.40 and a standard
deviation of 0.052. The long segment is shown to have
a variation in mean accumulation of 0.44 and a standard
deviation of 0.069.

FUTURE WORKS
Firn accumulation rates need to be completed for the remaining
snow radar flights during the 2009 International Polar Year.
Furthermore, it is pertinent to include the data and research
from Ms. Brooke Medley and the CreSIS developed
Accumulation Radar to assist in deriving the depth to age scale
for the uppermost firn layers of West Antarctica (Figure 12).
Published datasets for Antarctica are to be compared to provide
a baseline for the firn estimates, as well as data regarding
possible climatic indicators that affect the mass balance. Due to
Ms. Medley and I developing MATLAB that could be easily
modifieed and adapted for the downloading and analysis of the
remaining NASA Operation IceBridge missions, it is our goal to
complete the research for other flights in the area, as well as for
the upcoming IceBridge Missions.

Published Continent wide Accumulation Rate Datasets
Short segment
Short segment
Long segment
mean
std. dev.
mean

Long segment std.
dev.

Arthern et.al (2006)

0.361

0.025

0.362

0.031

Monaghan et.al (2006)

0.553

0.079

0.556

0.092

van der Berg (2005)

0.469

0.124

0.483

0.140

Figure 9: Depicting the shallowest short digitized layer
(0. 805 m) and the deepest digitized layer (36.12 m), the
chart also included the age of the layer, minimum
accumulation rate, maximum accumulation rate,
variation in mean, and standard deviation for each
digitized firn layer.

Figure 12: An image in ArcMap of the 2009 Operation
IceBridge flights (represented by the colored lines), the
ITASE core sites (represented by the black dots), and the
flight path of the CReSIS developed accumulation radar
used by Ms. Brooke Medley to derive accumulation rates
of Antarctica (2009-2010).

Figure 10: Depicting the shallowest long digitized layer
(0. 311 m) and the deepest digitized layer (52.24 m), the
chart also included the age of the layer, minimum
accumulation rate, maximum accumulation rate,
variation in mean, and standard deviation for each
digitized firn layer.

Figure 11: Continent wide datasets (specifically
measurements of the variation in mean and standard
deviations for the short and long segments) from
Arthern et. al (2006), Monaghan et. al (2006) , and van
de Berg (2005) were compared to the derived Thwaites
Glacier dataset from Ms. Brooke Medley and Mr. Ryan
Lawrence.

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