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Winter forest processes: measurements and modeling
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Geosciences and Environmental Engineering.
2006 (English)In: EOS: Transactions, ISSN 0096-3941, E-ISSN 2324-9250, Vol. 87, no 52Article in journal, Meeting abstract (Other academic) Published
Abstract [en]

Winter-forest processes affect global and local climates. Weather-forecast, climate and hydrological modelers incorporate increasingly realistic surface schemes into their models, and algorithms describing snow accumulation and snow-interception sublimation are now finding their way into these schemes. Both point and spatially variable data for calibration and verification of wintertime dynamics are therefore needed for such modeling schemes. Snow forest atmosphere interaction studies at Luleå University of Technology (in co-operation with researchers in Sweden, Finland, UK and Japan) show that seasonal sublimation fraction of snow precipitation in confined coniferous forests range about 0.35 and single events with sublimation rates of up to 3.9 mm in 7 h were observed. The most important factors for calculating the sublimation were: the relative humidity, the aerodynamic resistance, the wind speed and the intercepted mass. The techniques used to study processes and rates were weighing cut tree and weighing througfall (in Sweden) γ-ray attenuation and tree weighing systems, combined with plastic sheet net rainfall gauges for throughfall (in UK) and snow course measurements in combination with forest density measurements (in Finland) and with sky view fraction (SVF) measurements (fish eyed camera)(in Japan). For the last study forest snow accumulation (SF) could be estimated from snowfall in open fields (SO) and from SVF according to: SF = SO (0.56 + 0.6 × SVF) for SVF < 0.72 and SF = SO for SVF > 0.72 (R2 = 0.86) as well as from leaf area index (LAI). For observation plots exceeding 1 ha the SVF was correlated to the normalized difference snow index (NDSI) using a Landsat-TM image and SF was related to SO and NDSI according to SF = SO (0.81 - 0.37 × NDSI). Plot-size limitations allowed inclusion of only one sparse forest observation so the relationship.

Place, publisher, year, edition, pages
2006. Vol. 87, no 52
National Category
Geochemistry
Research subject
Applied Geology
Identifiers
URN: urn:nbn:se:ltu:diva-32071Local ID: 66edc080-d61b-11db-8550-000ea68e967bOAI: oai:DiVA.org:ltu-32071DiVA: diva2:1005305
Conference
American Geophysical Union. 2006 Fall meeting : 11/12/2006 - 15/12/2006
Note

Godkänd; 2006; 20070319 (ysko)

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-06-26Bibliographically approved

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http://www.agu.org/meetings/fm06/

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