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|TanDEM-X Science Service System|
|Title||Estimation of thaw processes in an arctic tundra landscape|
|Investigator||Sobiech, Jennifer - Alfred Wegener Institute, Geosciences, Periglacial Research|
|Summary||The projects overall goal is to examine the hydrology and energy fluxes of a polygonal arctic tundra landscape at a regional scale and to determine its spatial and temporal response to thawing and freezing processes.|
The arctic hydrological cycle plays a critical role in the linking land, atmosphere, and oceans of the Arctic System and in determining the part that terrestrial ecosystems play in feedbacks to climatic change. Point measurements of ground and soil temperatures as well as energy fluxes or associated surface parameters like land cover, however, do not adequately represent the spatial heterogeneity and complexity of Arctic environments. Remote sensing on the other hand provides a means of obtaining information of a regional nature in the High Arctic where existing data networks are sparse.
The Lena Delta is located in Northern Siberia (72.0-73.8°N, 122.0-129.5°E). It covers 29000km² and is the largest arctic river delta. The Delta consists of three different geomorphologic terraces. We focus on the first terrace, characterized by ice-rich deltaic sediments and consisting of a polygonal tundra landscape dominated by sedges and a moss cover. The generally flat wetland exhibits a patchy landcover pattern where small ponds and lakes alternate with wet and dry ground in a range of only a few meters. The Delta is characterized by a network of several river arms, channels and a high number of lakes. Approximately 30% of the Delta is covered with water bodies.
The project purposes a multi-sensor approach in order to characterize the water vapour and energy fluxes on different spatial scales for the whole year with focus on the snowmelt and freeze-back processes. Different wavelength will differ in the penetration depth of the vegetation cover and the soil and thus provide various information. The project will integrate TSX data with field observations, micrometeorological measurements, multispectral optical imagery and multi-temporal ENVISAT ASAR WS, ALOS PALSAR FBD, and RADARSAT-2 data.
As optical satellite data is limited in the often cloudy environment and during polar night, SAR imagery will provide valuable information, especially of the seasonal variations of the environment, at a very high temporal and spatial resolution.
The project distinguishes between three scales: locale or point scale (<1m), meso scale (1m - 10 km) and regional scale (10 km - 100 km). Investigations on the meso scale close the gap between the understanding of local processes and regional phenomena. Ground measurements include long-term micrometeorological measurements, i.e. soil, surface, and air temperatures, soil moisture, humidity, wind speed and direction, snow height, and solar radiation. The active layer on top of the permafrost soil is instrumented with a variety of sensors measuring the thermal state of this layer, monitoring the thawing processes on ground. Evapotranspiration is measured via Eddy covariance. Frost tubes are installed to measure the active layer depth. An automatic camera with daily acquisitions monitors seasonal changes like snowmelt. Vegetation structure will be mapped to investigate surface roughness. These extensive ground measurements in conjunction with a multi-sensor remote sensing imagery will render a unique multi-scale and multi-temporal dataset of the Siberian high Arctic.
Data analysis will include the observation and interpretation of changes in the SAR backscatter in combination with changes in the seasonal local climate conditions. The significant changes of the conductivity of the soil with changes of water content and freezing/thawing will allow us to scale up from our investigation sites in the field to a larger spatial scale.
Results of the research will be made public by presentations at relevant scientific conferences and within at least one peer-reviewed paper publication.
The project is founded by the AWI within the Helmholtz EOS-Network program.
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