| dc.description.abstract | The effect of albedo variability induced by meteorological parameters in
snow-covered forested areas at local scale is poorly known. Few meteorological
stations measure albedo, even though the effect on albedo caused by
land use changes is well known. The boreal forest is mainly comprised of
coniferous tree species and represents the largest terrestrial biome which is
characterised by long winters with seasonal snow cover. Since boreal forests
alter the albedo through snow interception by the canopy, they are subjects
of this investigation. This study evaluates the induced effect of meteorological
variations and forest metric variations on albedo fluctuations at three
different forested sites in the boreal zone during winter season. All study
sites belong to the Integrated Carbon Observation System (ICOS) network
where meteorological variables are measured from towers on the three individual
study sites named Svarberget (SE-Svb), Norunda (SE-Nor) and Hyytiälä
(FI-Hyy). SE-Svb and SE-Nor is located in the boreal forest of Sweden while
FI-Hyy is located in the boreal forest of Finland. The influences of several
meteorological parameters were investigated by use of correlation analysis
first and then regression analysis. Forest metrics were derived from Light
Detection And Ranging (LiDAR) data and further related to mean albedo.
The influence of temperature on albedo was seen at every study site investigated
in this study. When the temperature is below freezing and the albedo
is initially high (0.3), a decrease in albedo to a value of around 0.1 is observed
when the temperature increases to above freezing. This relation is ascribed
to the temperature influence of snow properties and snow appearance which
further is connected to albedo. Apart from this, precipitation was related to
albedo but the strength of the relationship was difficult to interpret since the
correlation analysis demonstrated both a positive and negative connection to
albedo. This could possibly derive from the form of the precipitation, snow
or rain, and further be temperature dependent. However, snow depth and
increased snow amount were parameters that induced an increase in albedo,
although the relationship was not that prominent (varied between insignificant up to correlation coefficient of 0.51 in the correlation analysis). The use
of forest structural metrics, canopy density, tree height and Canopy Relief
Ratio (CRR), did not show any clear relationship to mean albedo. However,
the variable model output from the regression analysis highlights that
there is a need for site-specific investigation to better understand local albedo
variability in snow-covered forested areas. | en_US |
