From a point to a basin: comparing continuous, point snow depth measurements from an automatic
weather station with extensive, high resolution basin-wide depths in Senator Beck Basin, CO
1
1
2
Hans-Peter Marshall, Andy Gleason, Chris Landry, James McCreight
3
1. Institute of Arctic and Alpine Research, University of Colorado at Boulder
2. Center for Snow and Avalanche Studies, Silverton, Colorado
3. National Snow and Ice Data Center, Boulder, Colorado
Corresponding author: H.P. Marshall, marshalh@colorado.edu, 303-859-3106
Figure 1: Measuring snow depth, stratigraphy, and snow water equivalent (SWE)
using a portable microwave radar. Radar unit is the white box attached to pole
between skiers. Ruggedized laptop in backpack controls data acquisition.
Survey-grade GPS antenna shown in backpack on left. Senator Beck Study Plot
is the tower to the right (see Figure 2 and 11).
Figure 14: Senator Beck Basin, Colorado, USA. Location of radar measurements made
during 3 day intensive campaign are shown in blue, green, and red, and in addition
measurements made during 2 other days are also shown. The two Automatic Weather
Stations (AWS) are shown with red X's, and the manual depth sampling locations for the
annual spring survey are shown with blue X's.
ABSTRACT
Estimating the distribution of seasonal snow is important for water resource management, as
one-sixth of the world's population depends on snowmelt for their water supply. In addition, snow
water equivalent (SWE) estimates are important for flood and hydropower forecasting, and are
critical for understanding surface and ground water systems. Because the snow cover has such a
large effect on the global energy balance, accurate SWE estimates over large areas are necessary
for evaluating future climate change scenarios. Due to high spatial variability in snow depth and
SWE that exists at scales less than 100m, the relationship between point measurements of snow
and the basin-wide and regional mean depth and SWE is complex. Models typically use statistical
relationships between point measurements of depth/SWE and measured stream flow, however
these relationships will change with changes in climate. In addition, in locations with a short
history of measurements, stream flow estimates are subject to large uncertainties. Extensive,
basin-wide measurements with a highly portable microwave radar have been made throughout
Senator Beck Basin over the past 2 years. These measurements are used to estimate snow depth
and SWE at several million locations throughout the basin and this detailed spatial distribution is
compared with snow depth measurements at two automatic weather stations, one above and one
below treeline.
Figure 2: Topographic map of Senator Beck Basin, Colorado, USA.
Location of radar measurements made during 3 day intensive campaign
are shown in blue, green, and red, and in addition measurements made
during 2 other days are also shown. The two Automatic Weather Stations
(AWS) are shown with red X's, and the manual depth sampling locations
for the annual spring survey are shown with blue X's.
Figure 11: Time series of snow depth at Senator Beck Study Plot during the
winter 2006-2007. Continuous snow depth measurement in blue, red line
shows the date of the radar measurements in Figure 7. The SBSP snow depth
on this date was 1.8 m, which is within 10 cm of the mean manually measured
depth (Fig 10), and is within 60 cm of the mean radar depth. Snow depth
distribution is largely controlled by the small scale topography, therefore it is
possible that the relationship between SBSP depth and basin mean depth is
stationary from year to year.
METHODS
A portable microwave (2-10 GHz) Frequency Modulated Continuous Wave (FMCW) radar was used to
Figure 10: Distribution of snow depth measurements in the upper
measure snow depth, stratigraphy, and snow water equivalent (SWE). Impulse radar measurements have
basin. Histogram is shown in blue, non-parametric PDF in red, and
Figure 7: Radar image from the upper basin, above treeline, covering more than 1.6
been used previously to measure snow depth in Scandanavia (e.g. Sand and Bruland, 1998; Lundberg et al.,
mean in green. Box plot is shown at top. Blue box spans the middle
km at 10 cm measurement spacing. Large variability in snow depth exists, ranging
2000), and to document spatial variability of snow on glaciers (Harper and Bradford, 2003).
50% of the measurements, short vertical red line is the median, and
from less than 30 cm to more than 500 cm. Major stratigraphic boundaries
FMCW radar has been used to measure layering in firn and ice in Greenland (Kanagaratnam et al,
representing different storm events are clearly visible and can be followed over large whiskers span the middle 95% of the data. The upper panel shows the
2001), snow depth in the Alaskan arctic (Holmgren et al, 1998), and to measure the speed of avalanches
distribution of 16,000 radar snow depth measurements over 1.6 km in
(Gubler and Hiller, 1984). Early work (Ellerbruch and Boyne, 1980) with a large stationary system showed distances. Variability in layers which are closer to the surface is lower, as the
the technique could be used to estimate snow depth and SWE. More recently, Koh et al. (1996) showed that underlying topography is smoothed by the older snow layers.
the upper basin (see Fig X), and the lower panel shows the distribution
a several different frequency ranges were necessary for measurements in a wide range of snow conditions,
of 263 manual measurements. The large number of measurements at
and Yankielun et al. (2004) demonstrated that the technique could be used with success from an areal
300 cm in the lower pannel indicate snow depths that were 300 cm or
tramway. Marshall and Koh (2007) give a detailed review of previous FMCW radar measurements in
greater (length of depth probe).
seasonal snow.
Strong, continuous reflections occur at the snow surface and the snow ground interface, and the
Two-way Travel time (TWT) of the electromagnetic signal between these two boundaries can be used to
estimate snow depth and SWE, typically to within less than 10% (Marshall et al., 2005). With an accurate
RESULTS
estimate of density, the error can be much lower. In addition, reflections from major stratigraphic
Radar profiles above and below treeline show drastically different snow depth and SWE patterns, due to
boundaries within the snowpack can be used to measure individual snow layer thicknesses (Marshall et al,
differing environmental controls. Figure 6 shows a radar profile below treeline near the Swamp Angel Study
2007). Here we focus on snow depth and SWE, as these are more important variables from a hydrologic
Site (see Figures 2 and 14 for location). Two different profile directions are shown, both indicating very little
perspective.
variability in snow depth and SWE at this site. These radar-estimated snow depths agreed with measurements
Our previous work used a large stationary radar system (Marshall et al., 2004), however here we use a
from the Swamp Angel Study Plot continuous gauge to within 5%, indicating that the continuous
recently developed lightweight portable system, coupled with survey-grade GPS, to cover large distances in
measurements accurately represent the depth throughout this open meadow. This site therefore provides an
an alpine basin. Measurements were made at frequencies from 2-10 GHz, resulting in a vertical resolution
Figure 3: Radar measurements below treeline at the Swamp Angel
of less than 2 cm. Radar traces were recorded at a rate of 40 Hz, resulting in an average horizontal spacing
advantageous location for stationary, continuous radar measurements, as ground truth measurements in nearby
Study Plot (tower on left). This area is characterized by little variability between measurements of less than 10 cm. Frequent sky calibration measurements were made with the
pits are representative of the undisturbed snow at the weather station. This winter we are operating 2
radar, which were used in post-processing to remove instrumentation-related noise. Surface and ground
as the site is very wind-protected in a relatively flat meadow (see
stationary radars at this site, one buried underneath the snowpack pointed upwards and another mounted on
reflections were located using an automatic, global, threshold-based picking algorithm.
the tower and an incidence angle of 35 degrees. The buried radar will provide non-destructive temporal
Five manual measurements, spanning a 50 cm X 50 cm area representing the radar footprint at that
measurements of snow depth, stratigraphy, and SWE, while the tower-mounted system will simulate
point, were made at each of many frequent stopping points. These manual measurements were used to
measurements from air- and space-borne platforms for evaluation of radar SWE retrieval algorithms.
calibrate and verify the radar-derrived snow depths. Radar profiles were made between 5 different snowpits
Figure 8: Variogram of snow depth in the lower basin
Figure 7 shows a radar profile in the upper Senator Beck Basin, above treeline, and indicates large
throughout the basin, where manual measurements of snow water equivalent and layering were made. At
(Figure 6). The blue curve shows the variogram from
each pit, a metal reflector was inserted horizontally at major stratigraphic layers, while the radar was
variability in snow depth and SWE over short distances. This area has much higher wind speeds that cause
the East-West profile, and the red curve shows the
positioned near the wall of the pit (Figure 5). This allowed interpretation and identification of the major
the new low density snow to be easily transported. Radar derrived snow depths along this profile covering
results
from
the
East-West
line.
The
average
difference
reflections within the snowpack in the radar images. Comparison with manual measurements (Fig 12,13)
more than 1.6 km indicate variations from less than 30 cm to more than 500 cm.
between
points
separated
by
15
meters
is
less
than
4
cm.
show the radar-estimated snow depths are accurate to within 5% except in very shallow snow (less than 30
Variograms were calculated for the profiles in 2 different directions in the lower basin (Figure 8) and show
cm, where the accuracy is within 4 cm. Most of the errors in measurements can be explained by variation in
very low variances. The square-root of the average variance at each lag is shown to provide a measure with
snow depth within the radar footprint, and changes in snow density which cause small errors in the radar
physical significance, and shows that points separated by 15 meters on average vary by less than 4 cm, or less
estimate of depth (but less in the SWE estimate, see Fig 5).
Figure 4: Radar measurements at wall of pit. Metal snow saw shown
was inserted at visually identified stratigraphic layers, causing a large
reflection in the radar data. This experiment allows interpretation of
radar reflections within snowpack along profiles in the context of
snowpit measurements.
Figure 9: Variogram of snow depth in the upper basin.
Calculated variance from all 16,000 points over the 1.6 km
is shown in blue, and the red, greenm and black lines show
variograms calculated from 3 separate 500 m sections of
the data to illustrate the variability in the variogram.
Figure 5: Comparison of errors in estimated snow water equivalent
(SWE) from manual depth measurements (blue) and radar
measurements, caused by changes in estimated mean snow density.
Radar SWE estimates are less sensitive to errors in estimated snow
Figure 6: Radar image from the lower basin, below treeline. Upper pannel shows a 30 meter
profile from North to South near the Swamp Angel Study Site, and the lower pannel shows a
30 meter East to West profile. Very little variability in snow depth and layer thickness exists
at this wind protected site, and radar measurements agreed with snow depth measured at the
Swamp Angel Study Plot continuous depth gauge to within 5%.
than 5%. Due to this very small variance, inferences about the range of these variograms are difficult to make,
since these variances are on the order of the accuracy of the radar derrived snow depths. There is little
difference in variance between the profiles in the two different directions.
Figure 9 shows the variogram for the profile in the upper basin. This much longer profile was also divided
into three separate 500 m sections, and variograms for each section are also shown. All 4 of these variograms
are very similar, and indicate that the processes controlling snow depth distribution are fairly constant along
this 1.5 km transect. All of these variograms show a range of approximately 80 meters, and in addition a scale
break at approximately 3 meters is suggested. In sharp contrast to the measurements below treeline, points
separated by 15 meters on average vary by almost 100 cm.
The top plot in Figure 10 shows the distribution of 16,000 radar snow depths in the upper basin, and the
lower plot shows the distribution of 263 manual depth measurements along the same transect shown in Figure
7. The large peak in the lower plot at 300 cm is caused by 38 measurements that were deeper than the 3 m
probe. These manual measurements underestimate the mean depth by more than 60 cm, and are not able to
accurately represent the range of depths nor the spatial structure. Portable radar provides an advantageous
tool in this environment, where manual probing is time consuming and a sled-based radar is not practical due
to the rugged terrain.
Figure 11 shows the time series of snow depth at the Senator Beck Study Plot, with the date of the radar
survey indicated in red. The measurement at this site was 1.8 m during the radar survey, which is 60 cm less
than the average depth of all 16,000 radar measurements in the upper basin. However, the snow depth
distribution is controlled by small scale topography, which may be constant year-to-year. Future work will
involve studying the relationship between snow depth measured at the study plot, and the mean snow depth
above treeline over multiple years.
Clearly optimal sampling strategies will vary with location in this basin, and future work will include
quantifying the accuracy of different sampling patterns. Similar intensive radar sampling campaigns will take
place throughout the next winter, and the temporal variations in the spatial patterns of snow depth and SWE
will be studied. This work will help to quantify the accuracy of spatially distributed snow modeling, and
improve techniques and sampling strategies for estimating SWE at the basin scale.
Figure 15: Radar measurements above treeline in rugged
terrain. These steeper slopes preclude radar measurements
using a sled, however the lightweight portable radar, weighing
less than 20 lbs, can be easily operated by two skiers, even on
the way down!
ACKNOWLEDGEMENTS
This work was funded by the NASA Energy and Water cycle Sponsored (NEWS) research
program and the NASA Terrestrial Hydrology Program, through grant #NNG06GE70G,
"Investigation of spatial and temporal variations in snowpack properties using ground-based
high resolution microwave radar combined with detailed snowpack characterization." James
McCreight is funded under a NASA Earth Systems Science Graduate Fellowship.
Figure 12: Accuracy of FMCW radar-derived snow
depths, from 3 different surveys at sites with different
snow depths. The red line indicates a 1:1 relationship,
and the gray shaded region is the 95% confidence
interval for the regression. The colored image shows the
2-D non-parametric estimate. The vertical errorbars on
the deeper snow depths show the spread of 3 manual
measurements within the radar footprint at the
comparison point, and the horizontal errorbars indicate
the uncertainty in the radar estimate.
Figure 13: Accuracy of FMCW snow depth
measurements from a 4th survey, in which 5 manual
snow depth measurements were made within the radar
footprint at each comparison point. Vertical errorbars
show the spread in these measurements, and horizontal
error bars show the uncertainty in the radar estimate
due to changes in snow density.
The authors would like to thank Tom Painter (University of Utah) and Andy Barrett (NSIDC)
for coordinating these measurements coincident with their annual survey of Senator Beck
Basin for their NSF project, "Radiative effects of desert dust deposits in alpine snow." Future
work will include comparisons of manual measurements made during this survey and their
ongoing modeling efforts with the snow depth and SWE estimates from the radar
measurements. Gary Koh provided access to microwave radar equipment. Michael Barton
and Jeff Deems helped with snowpit measurements that provided ground-truth for the radar
data. Yukon the Arctic husky provided moral support and added dog hair to all clothing and
equipment.
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