scholarly journals Constraints on snow accumulation and firn density in Greenland using GPS receivers

2015 ◽  
Vol 61 (225) ◽  
pp. 101-114 ◽  
Author(s):  
Kristine M. Larson ◽  
John Wahr ◽  
Peter Kuipers Munneke
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Vertical Displacement ◽  
Snow Accumulation ◽  
Vertical Position ◽  
Snow Surface ◽  
Snow Layer ◽  
Gps Antenna ◽  
Better Than

AbstractData from three continuously operating GPS sites located in the interior of the Greenland ice sheet are analyzed. Traditionally these kinds of GPS installations (where the GPS antenna is placed on a pole deployed into the firn) are used to estimate the local horizontal speed and direction of the ice sheet. However, these data are also sensitive to the vertical displacement of the pole as it moves through the firn layer. A new method developed to measure snow depth variations with reflected GPS signals is applied to these GPS data from Greenland. This method provides a constraint on the vertical distance between the GPS antenna and the surface snow layer. The vertical positions and snow surface heights are then used to assess output from surface accumulation and firn densification models, showing agreement better than 10% at the sites with the longest records. Comparisons between the GPS reflection method and in situ snow sensors at the Dye-2 site show good agreement, capturing the dramatic changes observed in Greenland during the 2012 summer melt season. The geocentric elevation of the snow surface can be inferred by subtracting the snow surface height estimates from the vertical position measurements. It should be possible to use those surface elevation estimates to help validate elevation results obtained from satellite altimetry.

scholarly journals Katabatic winds and piteraq storms: observations from the Greenland ice sheet

1969 ◽  
Vol 33 ◽  
pp. 83-86 ◽  
Author(s):  
Dirk Van As ◽  
Robert S. Fausto ◽  
Konrad Steffen
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Surface Mass ◽  
Surface Ablation ◽  
Iceberg Calving ◽  
Energy Exchanges ◽  
In Situ Observations ◽  
Insight Into

In 2007 the Programme for Monitoring the Greenland Ice Sheet (PROMICE) was initiated to observe and gain insight into the mass budget of Greenland ice masses. By means of in situ observations and remote sensing, PROMICE assesses how much mass is gained as snow accumulation on the surface versus how much is lost by iceberg calving and surface ablation (Ahlstrøm et al. 2008). A key element of PROMICE is a network of automatic weather stations (AWSs) designed to quantify components of the surface mass balance, including the energy exchanges contributing to surface ablation (Van As et al. 2013).

scholarly journals Deep Learning on Airborne Radar Echograms for Tracing Snow Accumulation Layers of the Greenland Ice Sheet

2021 ◽  
Vol 13 (14) ◽  
pp. 2707
Author(s):  
Debvrat Varshney ◽  
Maryam Rahnemoonfar ◽  
Masoud Yari ◽  
John Paden ◽  
Oluwanisola Ibikunle ◽  
...  
Keyword(s):  
Deep Learning ◽  
Mass Loss ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Airborne Radar ◽  
Snow Layer ◽  
Surface Mass ◽  
Radar Images

Climate change is extensively affecting ice sheets resulting in accelerating mass loss in recent decades. Assessment of this reduction and its causes is required to project future ice mass loss. Annual snow accumulation is an important component of the surface mass balance of ice sheets. While in situ snow accumulation measurements are temporally and spatially limited due to their high cost, airborne radar sounders can achieve ice sheet wide coverage by capturing and tracking annual snow layers in the radar images or echograms. In this paper, we use deep learning to uniquely identify the position of each annual snow layer in the Snow Radar echograms taken across different regions over the Greenland ice sheet. We train with more than 15,000 images generated from radar echograms and estimate the thickness of each snow layer within a mean absolute error of 0.54 to 7.28 pixels, depending on dataset. A highly precise snow layer thickness can help improve weather models and, thus, support glaciological studies. Such a well-trained deep learning model can be used with ever-growing datasets to aid in the accurate assessment of snow accumulation on the dynamically changing ice sheets.

scholarly journals In situ measurements of polarization properties of snow surface under the Brewster geometry in Hokkaido, Japan, and northwest Greenland ice sheet

2014 ◽  
Vol 119 (24) ◽  
pp. 13,946-13,964 ◽  
Author(s):  
Tomonori Tanikawa ◽  
Masahiro Hori ◽  
Teruo Aoki ◽  
Akihiro Hachikubo ◽  
Katsuyuki Kuchiki ◽  
...  
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
In Situ Measurements ◽  
Snow Surface

Changes in Greenland ice sheet elevation attributed primarily to snow accumulation variability

Nature ◽  
2000 ◽  
Vol 406 (6798) ◽  
pp. 877-879 ◽  
Author(s):  
J. R. McConnell ◽  
R. J. Arthern ◽  
E. Mosley-Thompson ◽  
C. H. Davis ◽  
R. C. Bales ◽  
...  
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Accumulation

XXV.—The Determination of Temperature Gradients over the Greenland Ice Sheet by Optical Methods

1957 ◽  
Vol 64 (4) ◽  
pp. 381-397
Author(s):  
R. A. Hamilton
Keyword(s):  
Temperature Gradient ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Temperature Gradients ◽  
Lower Atmosphere ◽  
Optical Methods ◽  
Snow Surface ◽  
Vertical Angle ◽  
Gradient Measurements

SynopsisThe temperature gradient in the lower atmosphere can be directly determined by measuring the optical refractive index of the air. This method is suitable for use on the Greenland ice sheet where errors introduced by water vapour are small, and where the strong solar radiation reflected by the snow surface makes it difficult to measure temperature differences over height differences of about I metre.The refraction was measured by observing the apparent vertical angle of each of a set of targets at distances up to 4 km. from a theodolite. The refraction was found to vary linearly with the distance of the target. The true vertical angle to the targets was determined when a second theodolite was available and reciprocal sights could be taken with it from the site of target to the fixed theodolite. The true vertical angle varied with time due to slow descent of the theodolite as the firn slumped; a correction for this was made. The standard error of the temperature gradient measurements was about 1.5 × 10−2 C.° per metre. It is considered that the method could be developed and improved so that over a range of only 100 metres temperature gradients could be measured to an accuracy of about 0·1° C. per metre.

Mapping the aerodynamic roughness of the Greenland ice sheet surface using ICESat-2

2021 ◽  
Author(s):  
Maurice van Tiggelen ◽  
Paul C.J.P. Smeets ◽  
Carleen H. Reijmer ◽  
Bert Wouters ◽  
Jakob F. Steiner ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Elevation ◽  
Spatiotemporal Variability ◽  
Atmospheric Models ◽  
Laser Altimeter ◽  
Eddy Covariance Measurements ◽  
Aerodynamic Roughness

<p>The roughness of a natural surface is an important parameter in atmospheric models, as it determines the intensity of turbulent transfer between the atmosphere and the surface. Unfortunately, this parameter is often poorly known, especially in remote areas where neither high-resolution elevation models nor eddy-covariance measurements are available.</p><p>In this study, we take advantage of the measurements of the ICESat-2 satellite laser altimeter. We use the geolocated photons product (ATL03) to retrieve a 1-m resolution surface elevation product over the K-transect (West Greenland ice sheet). In combination with a bulk drag partitioning model, the retrieved surface elevation is used to estimate the aerodynamic roughness length (z<sub>0m</sub>) of the surface.</p><p>We demonstrate the high precision of the retrieved ICESat-2 elevation using co-located UAV photogrammetry, and then evaluate the modelled aerodynamic roughness against multiple in situ eddy-covariance observations. The results point out the importance to use a bulk drag model over a more empirical formulation.</p><p>The currently available ATL03 geolocated photons are used to map the aerodynamic roughness along the K-transect (2018-2020). We find a considerable spatiotemporal variability in z<sub>0m</sub>, ranging between 10<sup>−4</sup> m for a smooth snow surface to more than 10<sup>−1</sup> m for rough crevassed areas, which confirms the need to incorporate a variable aerodynamic roughness in atmospheric models over ice sheets.</p>

scholarly journals In-Situ LED-Based Observation of Snow Surface and Depth Transects

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2292
Author(s):  
Celeste Barnes ◽  
Chris Hopkinson ◽  
Thomas Porter ◽  
Zhouxin Xi
Keyword(s):  
Snow Depth ◽  
Surface Albedo ◽  
Surface Condition ◽  
Field Of View ◽  
Snow Surface ◽  
Depth Measurement ◽  
Individual Distance ◽  
Strong Linear Relationship ◽  
Better Than

As part of a new snowpack monitoring framework, this study evaluated the feasibility of using an LED LIDAR (Leddar) time of flight sensor for snowpack depth measurement. The Leddar sensor has two additional features over simple sonic ranging sensors: (i) the return signal is divided into 16 segments across a 48° field of view, each recording individual distance-to-target (DTT) measurements; (ii) an index of reflectance or intensity signal is recorded for each segment. These two features provide information describing snowpack morphology and surface condition. The accuracy of Leddar sensor DTT measurements for snow depth monitoring was found to be < 20 mm, which was better than the 50 mm quoted by the manufacturer, and the precision was < 5 mm. Leddar and independent sonic ranger snow depth measurement showed strong linear agreement (r2 = 0.98). There was also a strong linear relationship (r2 = 0.98) between Leddar and manual field snow depth measurements. The intensity signal response was found to correlate with snow surface albedo and inversely with air temperature (r = 0.77 and −0.77, respectively).

scholarly journals Snow Accumulation Studies on the Thule Peninsula, Greenland

1968 ◽  
Vol 7 (49) ◽  
pp. 59-76 ◽  
Author(s):  
Steven J. Mock
Keyword(s):  
Regional Scale ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Accumulation Rates ◽  
Surface Slope ◽  
Ice Flow ◽  
Accumulation Pattern ◽  
Flow Phenomena ◽  
Independent Parameters

AbstractData from stake measurements, marker boards and pits along a 136 km trail crossing the Thule peninsula sector of the Greenland ice sheet have been used to determine both the regional and local distribution of snow accumulation, On a regional scale trend surfaces of mean annual accumulation can be adequately predicted from a model using distance from moisture source and elevation as independent parameters. A series of step- or wave-like features break the smooth profile of the ice. sheet and cause profound changes in accumulation rates on a local scale. The accumulation pattern over these features can be predicted from surface slope and departure from regional elevation. Profiles of’ surface and subsurface topography indicate a direct relationship between subsurface hills and step-like features, but cannot be quantitatively accounted for by existing ice-flow theory. Detailed accumulation studies in conjunction with a program of spirit leveling in the vicinity of Camp Century has revealed the development a shallow valley-like feature. Within this feature accumulation rates have increased indicating that it is the result of flow phenomena.

scholarly journals The darkening of the Greenland ice sheet: trends, drivers, and projections (1981–2100)

2016 ◽  
Vol 10 (2) ◽  
pp. 477-496 ◽  
Author(s):  
Marco Tedesco ◽  
Sarah Doherty ◽  
Xavier Fettweis ◽  
Patrick Alexander ◽  
Jeyavinoth Jeyaratnam ◽  
...  
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Aerosol Deposition ◽  
Near Surface ◽  
Multispectral Data ◽  
Warming Climate ◽  
Air Temperatures ◽  
Increasing Trends ◽  
Snow And Ice

Abstract. The surface energy balance and meltwater production of the Greenland ice sheet (GrIS) are modulated by snow and ice albedo through the amount of absorbed solar radiation. Here we show, using space-borne multispectral data collected during the 3 decades from 1981 to 2012, that summertime surface albedo over the GrIS decreased at a statistically significant (99 %) rate of 0.02 decade−1 between 1996 and 2012. Over the same period, albedo modelled by the Modèle Atmosphérique Régionale (MAR) also shows a decrease, though at a lower rate ( ∼ −0.01 decade−1) than that obtained from space-borne data. We suggest that the discrepancy between modelled and measured albedo trends can be explained by the absence in the model of processes associated with the presence of light-absorbing impurities. The negative trend in observed albedo is confined to the regions of the GrIS that undergo melting in summer, with the dry-snow zone showing no trend. The period 1981–1996 also showed no statistically significant trend over the whole GrIS. Analysis of MAR outputs indicates that the observed albedo decrease is attributable to the combined effects of increased near-surface air temperatures, which enhanced melt and promoted growth in snow grain size and the expansion of bare ice areas, and to trends in light-absorbing impurities (LAI) on the snow and ice surfaces. Neither aerosol models nor in situ and remote sensing observations indicate increasing trends in LAI in the atmosphere over Greenland. Similarly, an analysis of the number of fires and BC emissions from fires points to the absence of trends for such quantities. This suggests that the apparent increase of LAI in snow and ice might be related to the exposure of a "dark band" of dirty ice and to increased consolidation of LAI at the surface with melt, not to increased aerosol deposition. Albedo projections through to the end of the century under different warming scenarios consistently point to continued darkening, with albedo anomalies averaged over the whole ice sheet lower by 0.08 in 2100 than in 2000, driven solely by a warming climate. Future darkening is likely underestimated because of known underestimates in modelled melting (as seen in hindcasts) and because the model albedo scheme does not currently include the effects of LAI, which have a positive feedback on albedo decline through increased melting, grain growth, and darkening.

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