Climate Change and Interannual Variations
in Arctic Snow Cover and Vegetation Activity inferred from Satellite Data
during 1981-2001.
The overall objectives of the
project are:
Analysis of
AVHRR (Advanced Very High Resolution Radiometer) time series in order to model
spatial
And emporal
variations in snow cover and terrestrial vegetation in Greenland in the period
1981-200
Incorporation of
knowledge from improved descriptions of Arctic land surfaces into climate
models
To gain
understanding of the effects of climate change on the vegetation and energy,
water and carbon dioxide balances of Arctic ecosystems
Background
Recent studies of surface temperature variations based on meteorological station measurements show a pronounced warming in the high latitudes during the past 25-30 years. The warming occurs especially during the winter and spring periods in Alaska, Northern Canada and northern Eurasia. The same studies also indicate a slight cooling trend in the northeastern parts of United States and in the southwestern parts of Greenland. As most studies focus on a global warming, a possible warming in NE-Greenland combined with a possible cooling in SW-Greenland makes Greenland a very suitable area for a retrospective analysis of the interannual variation of snow cover and vegetation activity.
Associated with
the warming is a reduction in annual snow cover and earlier disappearance of
snow in spring. Interannual variations in climate influence global biospheric
activity and it has been reported that the photosynthetic activity of
terrestrial vegetation has increased in the Arctic areas as a result of the
warming. This manner suggests an increase in plant growth associated with a
lengthening of the active growing season. Several other recent studies have also
reported warming related phenological changes in plants, birds and poleward
range extensions in the case of birds and butterflies. The global carbon cycle
has apparently also responded to the recent warm period and the amplitude of
the seasonal CO2 cycle in the north has increased.
Project
description and methodology
The project will
aim to analyse time series of high resolution AVHRR derived NDVI (Normalised
Difference Vegetation Index) data from Greenland from 1981‑2001 in order
to determine the trend in terrestrial snow cover and vegetation change over
this time period and relate this to climate changes. This analysis will provide
important information related to topics such as global warming and the carbon
cycle. Additionally, comparison of the trend in snow cover depletion and NDVI
with data of other environmental parameters such as land temperature,
atmospheric carbon dioxide levels, sea‑surface temperature, and mean sea
level would increase the understanding of the feedback loops which connect
these factors, and our ability to accurately identify, measure, and model
global climate change.
Modelling of snow
cover depletion curves using AVHRR data has been carried out in the Alps and in
the United States and has been used with great success in water management
modelling, but similar studies has not been carried out in Greenland. Ongoing
studies use global resolution AVHRR derived NDVI to show that the length of the
growing season increased throughout the 1990's for northern latitudes and that
this increase correlates well with an increase in the amplitude of the seasonal
cycle of atmospheric carbon dioxide, and increased global temperature. These
studies are, however, based on data with poor temporal (twice monthly maximum
value composite) and spatial (8x8 km) resolution and will therefore not be
suitable for arctic areas where snowmelt occurs within few days and where the
growing season is very short and the vegetation is very heterogenous and
consist of many small patches. Further studies of modelling of the parameters
based on data with higher resolution are therefore needed.
The concept of the
project has been explored in a pilot project in the autumn 2000. At a few plots
along the coast of Greenland a Sigmoid symmetric transition function was used
to model snow depletion curves using data from all five AVHRR channels. A
double logistic function and NDVI time series was used to model temporal
metrics as a function of Julian date. Using daily 1x1 km AVHRR data the results
were very promising. With a very high accuracy the function could estimate the
time of snowmelt onset and ending, beginning of growing season and end, time of
maximum greenness occurrence and length of growing season. The NDVI analysis
also showed promising results for modelling regional and interannual variations
in biophysical components such as leaf area index and green biomass, which are
important input parameters in CO2-modelling.
A combination of
the snow cover and vegetation activity modelling will contribute significantly
to the farming and wildlife management in Greenland, but it will also
contribute significantly to other terrestrial/ecological and global change
studies in the area. The twice-daily 1 km NOAA-AVHRR Polar Pathfinder data
archive at the National Snow and Ice Data Center (NSIDC) in Boulder will be the
database for the project. The models will be validated with fielddata from
Zackenberg and Jameson Land on the Eastcoast and Kangerlussuaq and Nuuk on the
Westcoast of Greenland. The project/thesis will be carried out in collaboration
with NSIDC, Institute of Natural Resources in Greenland, National Environmental
Research Institute, Dep. for Arctic Environment and Institute of Geography,
University of Copenhagen.
Contact
Associate
Professor Birger Ulf Hansen, Ph.D., Institute of Geography, University of
Copenhagen.
Mikkel P.
Tamstorf, National Environmental Research Institute, Dep. for Arctic
Environment