Circumpolar Active-Layer Permafrost System (CAPS): a global geocryological database on CD and Internet (poster)

p. 407-40

Northern Hemisphere permafrost map based on TTOP modelling for 2000-2016 at 1 km²scale

Permafrost is a key element of the cryosphere and an essential climate variable in the Global Climate Observing System. There is no remote-sensing method available to reliably monitor the permafrost thermal state. To estimate permafrost distribution at a hemispheric scale, we employ an equilibrium state model for the temperature at the top of the permafrost (TTOP model) for the 2000–2016 period, driven by remotely-sensed land surface temperatures, down-scaled ERA-Interim climate reanalysis data, tundra wetness classes and landcover map from the ESA Landcover Climate Change Initiative (CCI) project. Subgrid variability of ground temperatures due to snow and landcover variability is represented in the model using subpixel statistics. The results are validated against borehole measurements and reviewed regionally. The accuracy of the modelled mean annual ground temperature (MAGT) at the top of the permafrost is ±2 °C when compared to permafrost borehole data. The modelled permafrost area (MAGT 0) is around 21 × 106 km2 (22% of exposed land area), which is approximately 2 × 106 km2 less than estimated previously. Detailed comparisons at a regional scale show that the model performs well in sparsely vegetated tundra regions and mountains, but is less accurate in densely vegetated boreal spruce and larch forests

Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale

Permafrost is a key element of the cryosphere and an essential climate variable in the Global Climate Observing System. There is no remote-sensing method available to reliably monitor the permafrost thermal state. To estimate permafrost distribution at a hemispheric scale, we employ an equilibrium state model for the temperature at the top of the permafrost (TTOP model) for the 2000–2016 period, driven by remotely- sensed land surface temperatures, down-scaled ERA-Interim climate reanalysis data, tundra wetness classes and landcover map from the ESA Landcover Climate Change Initiative (CCI) project. Subgrid variability of ground temperatures due to snow and landcover variability is represented in the model using subpixel statistics. The results are validated against borehole measurements and reviewed regionally. The accuracy of the modelled mean annual ground temperature (MAGT) at the top of the permafrost is ±2 °C when compared to permafrost borehole data. The modelled permafrost area (MAGT 0) is around 21 × 106 km2 (22% of exposed land area), which is approximately 2 × 106 km2 less than estimated previously. Detailed comparisons at a regional scale show that the model performs well in sparsely vegetated tundra regions and mountains, but is less accurate in densely vegetated boreal spruce and larch forests

Landsurface feature classification of tundra regions with polarimetric TerraSAR-X data, links to GeoTIFF files

Permafrost is an essential element of the cryosphere, which will be strongly affected by global warming. Although permafrost cannot be measured directly with remote sensing, many permafrost features are observable. Polarimetric information can be used in this context. Polarimetric data of TerraSAR-X is the basis for a local landcover classification presented here, which reflects different scattering mechanisms. The resulting classification aims on the identification of process areas and periglacial features such as thaw slumps (bare wet surfaces) and thaw lakes as well as wetland areas. The following regions are covered in the dataset: Barrow (Alaska), Mackenzie Delta (Canada), Kytalyk (Russia), Lena Delta (Russia), Vaskiny Dachi (Russia), Herschel Island (Canada)

Mean TerraSAR-X backscatter and in-situ measurements of near surface soil moisture and temperature including vegetation survey in August 2015 on central Yamal (Vaskiny Dachi CALM site)

The active layer above the permafrost, which seasonally thaws during summer, is an important parameter for monitoring the state of permafrost. Its thickness is typically measured locally, but a range of methods which utilize information from satellite data exist. Mostly, the normalized difference vegetation index (NDVI) obtained from optical satellite data is used as a proxy. The applicability has been demonstrated mostly for shallow depths of active-layer thickness (ALT) below approximately 70 cm. Some permafrost areas including central Yamal are, however, characterized by larger ALT. Surface properties including vegetation structure are also represented by microwave backscatter intensity. So far, the potential of such data for estimating ALT has not been explored. We therefore investigated the relationship between ALT and X-band synthetic aperture radar (SAR) backscatter of TerraSAR-X (averages for 10 × 10 m window) in order to examine the possibility of delineating ALT with continuous and larger spatial coverage in this area and compare it to the already-established method of using NDVI from Landsat (30 m). Our results show that the mutual dependency of ALT and TerraSAR-X backscatter on land cover types suggests a connection of both parameters. A range of 5 dB can be observed for an ALT range of 100 cm (40-140 cm), and an R² of 0.66 has been determined over the calibration sites. An increase of ALT with increasing backscatter can be determined. The root mean square error (RMSE) over a comparably heterogeneous validation site with maximum ALT of > 150 cm is 20 cm. Deviations are larger for measurement locations with mixed vegetation types (especially partial coverage by cryptogam crust) with respect to the spatial resolution of the satellite data

NEW PERMAFROST FEATURE – DEP CRATER IN CENTRAL YAMAL (WEST SIBERIA, RUSIA) AS A RESPONSE TO LOCAL CLIMATE FLUCTUATIONS

This paper is based on field data obtained during short visits to a newly formed permafrost feature in a form of relatively narrow, deep crater. Excluding impossible and improbable versions of the crater’s development, the authors conclude that it originated from warmerground temperatures and an increase in unfrozen water content, leading to an increase in pressure from gas emissions from permafrost and ground ice. This conclusion is also supported by known processes in the palaeo-geography of Yamal lakes and recent studies of gas-hydrate behavior and subsea processes in gas-bearing provinces

Colored dissolved organic matter (cDOM) absorption measurements in the Vaskiny Dachi region, Central Yamal, Russia

The datasets present measurements of cDOM absorption of lakes located in Central Yamal regularly from the summer periods of 2011 on. The study region is in the central part of Yamal peninsula (Western Siberia, Russia) with the long-term research station Vaskiny Dachi. Vaskiny Dachi has been established in 1988 as permafrost monitoring site, since 1996 it is run by the Earth Cryosphere Institute (ECI), Siberian Branch of Russian Academy of Sciences and an established site for the international Global Terrestrial Network for Permafrost (GTN-P) program. Water samples were collected in calm weather conditions with bottle sampling from the upper 30 cm of water column close to the shore or in the center of lakes from boat. The coastal rim of several lakes on the high plains is affected by recent activation of thermocirques. The samples for CDOM were filtrated directly in the field after sampling. Filtrates for CDOM were prepared by filtrating through 0.7µm pore size glass fiber filters (Whatman) and were stored in cold and dark conditions to avoid the photodegradation of CDOM. CDOM filtrates have been measured after the expedition using the dual-beam Specord 200 laboratory spectrometer (Jena Analytik) at the Otto Schmidt Laboratory OSL, Arctic and Antarctic Research Institute, St. Petersburg, Russia. The OSL CDOM protocol (Heim and Roessler, 2016) prescribes 3 Absorbance (A) measurements per sample from UV to 750 nm against ultra-pure water. The absorption coefficient, a, is calculated by a = 2.303A/L, where L is the pathlength of the cuvette [m], and the factor 2.303 converts log10 to loge. The output of the calculation is a continuous spectrum of a. The CDOM a spectra are used to determine the exponential slope value for specific wavelength ranges, S by fitting the data between min and max wavelength to an exponential function. We provide CDOM absorption coefficients for the wavelengths 254, 260, 350, 375, 400, 412, 440, 443 nm [1/m] and Slope values for three different UV, VIS, wavelength ranges: 275 to 295 nm, 350 to 400 nm, 300 to 500 nm [1/nm]. All data sampling and processing were carried out by scientists from Earth Cryosphere Institute and Alfred Wegener Institute

Colored dissolved organic matter (cDOM) absorption measurements in the Vaskiny Dachi region in 2011

The datasets present measurements of cDOM absorption of lakes located in Central Yamal regularly from the summer periods of 2011 on. The study region is in the central part of Yamal peninsula (Western Siberia, Russia) with the long-term research station Vaskiny Dachi. Vaskiny Dachi has been established in 1988 as permafrost monitoring site, since 1996 it is run by the Earth Cryosphere Institute (ECI), Siberian Branch of Russian Academy of Sciences and an established site for the international Global Terrestrial Network for Permafrost (GTN-P) program. Water samples were collected in calm weather conditions with bottle sampling from the upper 30 cm of water column close to the shore or in the center of lakes from boat. The coastal rim of several lakes on the high plains is affected by recent activation of thermocirques. The samples for CDOM were filtrated directly in the field after sampling. Filtrates for CDOM were prepared by filtrating through 0.7µm pore size glass fiber filters (Whatman) and were stored in cold and dark conditions to avoid the photodegradation of CDOM. CDOM filtrates have been measured after the expedition using the dual-beam Specord 200 laboratory spectrometer (Jena Analytik) at the Otto Schmidt Laboratory OSL, Arctic and Antarctic Research Institute, St. Petersburg, Russia. The OSL CDOM protocol (Heim and Roessler, 2016) prescribes 3 Absorbance (A) measurements per sample from UV to 750 nm against ultra-pure water. The absorption coefficient, a, is calculated by a = 2.303A/L, where L is the pathlength of the cuvette [m], and the factor 2.303 converts log10 to loge. The output of the calculation is a continuous spectrum of a. The CDOM a spectra are used to determine the exponential slope value for specific wavelength ranges, S by fitting the data between min and max wavelength to an exponential function. We provide CDOM absorption coefficients for the wavelengths 254, 260, 350, 375, 400, 412, 440, 443 nm [1/m] and Slope values for three different UV, VIS, wavelength ranges: 275 to 295 nm, 350 to 400 nm, 300 to 500 nm [1/nm]. All data sampling and processing were carried out by scientists from Earth Cryosphere Institute and Alfred Wegener Institute