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Regional and local Snow Grain Size variations in Dronning Maud Land, Antarctica and analysis of various distribution scales
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology (INK).
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology (INK).
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology (INK).
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Understanding spatial snow particle size variations are key to help interpretation of remotely sensed data of snow cover. In the case of Antarctica, remote sensing is the only viable option to estimate the surface mass balance of the ice sheet on continental scale. We have investigated snow particle size variability along a transect from the coast onto the polar plateau in Dronning Maud Land, Antarctica, to better understand the spatial and temporal variations in surface snow properties. Two daily samples were collected during a 55 day traverse to capture the regional variability. Local variability was assessed by sampling in grids at selected locations and the particle size and shape distributions for each site was analysed through digital image analysis, which has the benefit of yielding large quantities of reproducible quantitative data without the need for advanced laboratory analysis. The results provide an understanding of the complexity of snow particle size variability at different scales and show a variability range from 0.18–3.31 mm depending on the sample type (surface, grid or pit). We can verify relationships between grain size and both elevation and distance to the coast (moisture source) but have also identified regional seasonal changes, particularly on the lower elevations of the polar plateau. Our data provide possibilities to quantitatively assess the optical properties of the surface snow for remote sensing. The details of the spatial and temporal variations observed in our data provides a basis for further studies of the complex and coupled processes affecting snow particle size and the interpretation of remote sensing of snow covered areas.

Keywords [en]
Antarctica, particle size, snow, traverse, JASE
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
URN: urn:nbn:se:su:diva-62810OAI: oai:DiVA.org:su-62810DiVA, id: diva2:444914
Available from: 2011-09-30 Created: 2011-09-30 Last updated: 2022-02-24Bibliographically approved
In thesis
1. Snow particle size investigations using digital image analysis - implications for ground observations and remote sensing of snow
Open this publication in new window or tab >>Snow particle size investigations using digital image analysis - implications for ground observations and remote sensing of snow
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

During the past century climate warming has caused rapid changes in the Cryosphere. This has increased the need to accurately monitor rates of change in snow and ice in remote or sparsely populated areas where environmental observing capacity is limited. Monitoring snow cover requires understanding of the snow pack and the snow surface attributes. Snow particle size is an important parameter for characterization of snow pack properties. The size and shape of the snow particles affects the snow/air-ratio which in turn affect how energy is reflected on the snow surface. This governs the snow pack energy balance by changing the albedo or backscattering properties of the snow. Both the albedo and the snow particle size can be quantified by remote sensing. However, the snow particle size estimated by remote sensing, also called the optically equivalent particle size, represents only an approximation of the true or physical particle size of snow. Thus, there is demand for methods that relate both parameters and help to improve the interpretation of remote sensing data of snow at higher spatial and temporal scales. To address this demand the aim of this dissertation thesis is to improve existing sampling methods of the physical snow particle size to retrieve high-resolution, spatial and temporal data sets for validation of remote sensing data. A field sampling method based on object-oriented analysis of digital images was developed that allows measurements of various snow particle size parameters such as length, width, area, specific surface area and shape. The method generates a continuous snow particle size distribution that supports the detailed statistical characterization of a large number of samples. The results show its possibility to compare data from different existing methods. The sampling method was applied in field sites in Antarctica and in northern Sweden, to characterize the spatial variability in the physical snow particle size and to estimate correlations between various remote sensing products and the observed physical snow particle size. The results of the presented studies show that more detailed measurements of snow particle size in the field at higher temporal and spatial scales can improve the interpretation of active and passive satellite retrieved data.

Place, publisher, year, edition, pages
Stockholm: Department of Physical Geography and Quaternary Geology (INK), Stockholm University, 2011. p. 38
Series
Dissertations from the Department of Physical Geography and Quaternary Geology, ISSN 1653-7211 ; 27
Keywords
snow, remote sensing, particle size, Antarctica, in-situ sampling, seasonal snow
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-62800 (URN)978-91-7447-371-1 (ISBN)
Public defence
2011-11-11, De Geersalen, Geovetenskapens hus, Svante Arrhenius väg 14, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 2: Submitted. Paper 4: Manuscript. Paper 5: Accepted. Available from: 2011-10-20 Created: 2011-09-30 Last updated: 2022-02-24Bibliographically approved

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Ingvander, SusanneJansson, PeterBrown, Ian A.Holmlund, Per

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