Winter forest processes : measurements and modeling

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 schem...

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Bibliographic Details
Main Author: Lundberg, Angela
Format: Article in Journal/Newspaper
Language:English
Published: Luleå tekniska universitet, Geovetenskap och miljöteknik 2006
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Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-32071
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Summary: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. Godkänd; 2006; 20070319 (ysko)