Fourth Study Conference on BALTEX Scala Cinema Gudhjem

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Spatial Variability of Snow Cover and its Implication for the Forest
Regeneration at the Northern Climatological Tree-line (Finnish Lapland)
Andrea Vajda 1 , Ari Venäläinen 1 , Pekka Hänninen 2 and Raimo Sutinen 3
1 Finnish Meteorological Institute, PO Box 503, FIN-00101 Helsinki, Finland, e-mail: claudia.vajda@fmi.fi
2 Geological Survey of Finland, PO Box 96, FIN-02151 Espoo, Finland
3 Geological Survey of Finland, PO Box 77, FIN-96101 Rovaniemi, Finland
1. Introduction
The presence of permanent snow cover for 200-220 days of
the year has a determining role in the energy, hydrological
and ecological processes at the climate-driven spruce (Picea
abies) timberline in Lapland. Due to its high albedo values,
the snow cover modifies the surface radiation budget,
changes the aerodynamic characteristics of the surface, and
influences significantly the runoff (Harding et al. 2001). An
important interaction exists between snow and vegetation.
Thick snow cover may provide protection for plants during
winter by reducing or preventing soil frost. There is a
feedback mechanism, through which vegetation influences
the accumulation, spatial distribution and physical
characteristics of snow cover (Scott et al. 1995, Press et al.
1998, Sturm et al. 2001, Liston et al. 2002), e.g. more
vegetation captures and holds more snow, the length of the
snow-covered period increases and melt water production
increases late in the melt season. Disturbances, such as
forest fires or forest harvesting change the vegetation pattern
and influence in this way the spatial variation of snow cover.
This variability in altered snow conditions (in subarctic
Fennoscandia) is still poorly understood.
The objective of the current study is to examine how
vegetation influences the spatial variation of snow depth on
the small scale at the fire-disturbed (in 1960) tree-line in the
Tuntsa area of Finnish Lapland. Despite intensive planting
attempts, reforestation has largely failed in the study area.
This study aims at providing new information about the
feedback mechanisms between the atmosphere and the
surface in the sensitive region near the climatological
borderline of forests. In addition, the study compares two
different snow-depth measurement methods: the traditional
manual measurement and radar measurement.
2. Methods and data
Snow depth and density were measured on a 1*0.6 km site
over two vegetation types, the spruce-dominated fire refuge
and post-fire treeless tundra. The snow thickness was
determined manually and with radar. The spatial variation of
wind speed and direction over the study area was estimated
using the WAsP model (Wind Atlas Analysis and
Application Program) described by Troen and Peterson
(1989). Based on the measured wind climate from two
representative stations and using a 10*10 m resource grid
squares, we calculated the mean wind speed and wind speed
distribution (Weibull A and k) at a height of 10 metres above
the surface. For a more substantial analysis the mean wind
speed was calculated for one location in the middle of the
study area at heights of 10 and 2 metres. Based on the
manual and radar snow measurements, maps giving the
spatial distribution of snow depth were prepared using the
kriging spatial interpolation method for the same 10*10 m
grid squares that were used in the wind simulations. Thus
the snow depth of every grid-square was calculated, so the
spatial distribution of snow depth could be compared with
surface characteristics, wind flow and vegetation types.
3. Results
The correlation (0.84) between the datasets of the two
types of measurements was high; however the radar
measurements provide a more detailed picture of snow
thickness. Due to its high resolution (10 cm), the radar is
capable of detecting small relief variations, which affect
the snow thickness at the respective location. According to
the spatial variation of the differences between the manual
measurement and radar values, the usual deviation is 5-15
cm, with larger values in the S and SE part of the western
edge of the area studied (30-45 cm) and in some places in
the transition between the forest and the open area.
Although radar measurements give a better depiction of
the spatial variation of the snow cover than the manual
ones, manual measurements can be regarded as being
more precise in measurement location.
The simulated wintertime, October-March, wind climate
for Tuntsa indicates a mean wind speed of 3.9 m s -1 at a
height of 10 metres above the surface. The most frequent
(14%) wind direction was from the sector 225-255 and the
most frequent wind speed range, using a 1 m s -1 class
interval, was 5-6 m s -1 (10.1%). The spatial distribution of
the average wind speed is mainly influenced by the
surface roughness. A strong mean wind (3.5-4 m s -1 ) is
frequent over the open area, with the highest value (4.5 m
s -1 ) in these locations and in the south-east. Over the
transition between the forest and the open area the wind
speed is higher as well, as consequence of winds from the
northern and eastern sectors, which only decrease
gradually over the surface with a higher roughness.
Snow depth (cm)
> 140
130 - 140
120 - 130
110 - 120
100 - 110
90 - 100
80 - 90
70 - 80
60 - 70
50 - 60
40 - 50
30 - 40
< 30
A B
Figure 1. Snow-depth distribution based on the
manually measured data (A) and radar data (B).
The spatial distribution of snow cover is mainly influenced
by the vegetation type and the wind velocity (linear
regression coefficient: 0.90). The distribution of snow
cover (Fig. 1) indicates the lower snow depths (40-70 cm)