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Comparison between digital and manual methods of snow grain size determination
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
2012 (English)In: Hydrology Research, ISSN 0029-1277, Vol. 43, no 3, 192-202 p.Article in journal (Refereed) Published
Abstract [en]

Maintaining long time series of observations of the Cryosphere is a key issue in climate research. Long observational time series involve problems due to change in methodology or observers. In order to extend time series and introduce new methods, careful comparisons must be made to ensure homogeneity in the observational data. We have compared an established method for snow grain-size observations used by the Abisko Scientific Research Station (ASRS) in northern Sweden, based on visual interpretation, with a newly developed method for Digital Snow Particle Properties (DSPP) analysis. Transition from subjective visual method into digital reproducible analysis creates less subjective and more comparable results. The ASRS method generates size classifications excluding quantitative analysis size ranges. By determining the sizes of the classified snow using the DSPP-method, actual size ranges for classified snow can be established. By performing a digital analysis of the reference samples and the snow samples classified, we can compare the ASRS classification system to existing official classification systems. The results indicate underestimation of the visual particle size in comparison to the reference samples. Our results show how to quantify the historical data set, which enables us to perform quantitative analysis on the historical data set.

Place, publisher, year, edition, pages
2012. Vol. 43, no 3, 192-202 p.
Keyword [en]
Abisko Scientific Research Station, classification, methods, particle size, snow
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
URN: urn:nbn:se:su:diva-62809DOI: 10.2166/nh.2012.078ISI: 000300635000003OAI: oai:DiVA.org:su-62809DiVA: diva2:444909
Available from: 2011-09-30 Created: 2011-09-30 Last updated: 2013-01-28Bibliographically 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. 38 p.
Series
Dissertations from the Department of Physical Geography and Quaternary Geology, ISSN 1653-7211 ; 27
Keyword
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: 2011-10-03Bibliographically approved

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