ALBERT

Beschreibung: The ESA DUE Permafrost project (2009-2011) is developing a suite of parameters indicative of the subsurface phenomenon permafrost using satellite remote sensing: Land Surface Temperature (LST), Surface Soil Moisture (SSM), Surface Frozen and Thawed State (Freeze/Thaw), Terrain, Land Cover (LC), and Surface Water (SW). Snow parameters (Snow Extent and Snow Water Equivalent) are being developed through the DUE GlobSnow project, Global Snow Monitoring for Climate Research (2008-2011). The final DUE Permafrost remote sensing products cover the years 2007 to 2011 with a circumpolar coverage that will soon be released (early 2012), and then be used to analyze the temporal dynamics and map the spatial patterns of indicators. Further information is available at www.ipf.tuwien.ac.at/ permafrost. Since the beginning, scientific stakeholders and the International Permafrost Association (IPA) have been involved in the science and implementation plan. Interactive international user workshops took place in 2010 at the Technical University of Vienna, Vienna (AT), and in 2011 at the International Arctic Research Center (IARC), Fairbanks, Alaska (US). This involvement and the ongoing evaluation of the indicators derived from remote sensing for the high-latitude permafrost regions make the DUE Permafrost products trustworthy for the permafrost and the climate research community. The adaption of the remote sensing products for the permafrost and climate modelling is experimental and highly dependent on the users’ involvement. For a few years already, the Geophysical Institute Permafrost Laboratory (GIPL), University of Alaska Fairbanks, US, (http://www.gi.alaska.edu/research/snowicepermafrost/Permafrost) has successfully demonstrated the value of using LST derived from remote sensing data for driving its permafrost models. Further experimental testing of the DUE Permafrost products for use by the modeling community (permafrost and climate) will range from (i) the evaluation of external data of the models, with modifying or providing new external data (e.g. tundra land cover, surface water ratio, soil distribution), to (ii) new drivers for regional models derived from remote sensing (e.g., LST), to (iii) the evaluation of the output data from the models (e.g. spatial patterns of moisture and temperature).

Beschreibung: The focus of this research has been on detecting changes in lakes vegetation, land surface temperatures, and snow cover, using data from remote sensing. The study area covers the main (central) part of the Lena River catchment in the Yakutia Region of Siberia (Russia) where continuous permafrost coverage’s is up to 90%. The remote sensing analyses are based on MODIS (NASA) and Landsat (USGS) satellite data. Time series of remote sensing products of MODIS land surface temperature were produced for the study region between 61°N and 65°N, and between 117.5°E and 131.5°E. The MODIS Land Surface Temperature level 3 product, MOD11C3 are configured on a 0.05° latitude/longitude MODIS Climate Model Grid (CMG) raster. The LST product is a monthly composited average and represents clear-sky LST values. The monthly land surface temperature were analyzed over the eleven year interval from May 2000 to April 2011. Linear trend calculations for the 11 year temperature measurement interval were performed separately for each two month interval, in each pixel, using the least squares method. Water bodies were extracted using the Landsat Short Wave Infrared SWIR band 5. Within the study region's 315,000 sq. km, the total area covered by lakes increased by 17.5% between 2002 and 2009. The amount of lake increase differs between 42-11% depending on the region. The overall trend in land surface temperature is around 0.15°C/year, but with seasonal warming trends in April-May of up to 0.45°C/year in some areas and cooling of -0.2 to -0.3°C/year in July-August in other areas. These regional differences and potential causes of the land surface temperature changes will be discussed with respect to land cover changes.