Geocryological characteristics of the upper permafrost in a tundra-forest transition of the Indigirka River Valley, Russia

Iwahana, Go; Takano, Shinya; Petrov, Roman E.; Tei, Shunsuke; Shingubara, Ryo; Maximov, Trofim C.; Fedorov, A.A.; Desyatkin, Alexey; Николаев, А. Н.; Desyatkin, Roman; Sugimoto, Akihiro

doi:10.1016/j.polar.2014.01.005

Cited by 44 publications

(43 citation statements)

References 46 publications

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“…The mean annual permafrost temperature at 15 m depth close to the site is −9.4 • C (Romanovsky et al, 2010). The study region in lowland tundra is underlain by very ice-rich permafrost (Iwahana et al, 2014), which makes it susceptible to rapid changes in case of warming (Jorgenson et al, 2006). A multi-year study by Parmentier et al (2011a) observed the snowmelt between 18 May and 10 June.…”

Section: Field Site Vegetation and Soilmentioning

confidence: 86%

Contrasting radiation and soil heat fluxes in Arctic shrub and wet sedge tundra

et al. 2016

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Abstract. Vegetation changes, such as shrub encroachment and wetland expansion, have been observed in many Arctic tundra regions. These changes feed back to permafrost and climate. Permafrost can be protected by soil shading through vegetation as it reduces the amount of solar energy available for thawing. Regional climate can be affected by a reduction in surface albedo as more energy is available for atmospheric and soil heating. Here, we compared the shortwave radiation budget of two common Arctic tundra vegetation types dominated by dwarf shrubs (Betula nana) and wet sedges (Eriophorum angustifolium) in North-East Siberia. We measured time series of the shortwave and longwave radiation budget above the canopy and transmitted radiation below the canopy. Additionally, we quantified soil temperature and heat flux as well as active layer thickness. The mean growing season albedo of dwarf shrubs was 0.15 ± 0.01, for sedges it was higher (0.17±0.02). Dwarf shrub transmittance was 0.36 ± 0.07 on average, and sedge transmittance was 0.28 ± 0.08. The standing dead leaves contributed strongly to the soil shading of wet sedges. Despite a lower albedo and less soil shading, the soil below dwarf shrubs conducted less heat resulting in a 17 cm shallower active layer as compared to sedges. This result was supported by additional, spatially distributed measurements of both vegetation types. Clouds were a major influencing factor for albedo and transmittance, particularly in sedge vegetation. Cloud cover reduced the albedo by 0.01 in dwarf shrubs and by 0.03 in sedges, while transmittance was increased by 0.08 and 0.10 in dwarf shrubs and sedges, respectively. Our results suggest that the observed deeper active layer below wet sedges is not primarily a result of the summer canopy radiation budget. Soil properties, such as soil albedo, moisture, and thermal conductivity, may be more influential, at least in our comparison between dwarf shrub vegetation on relatively dry patches and sedge vegetation with higher soil moisture.

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Section: Field Site Vegetation and Soilmentioning

confidence: 86%

Contrasting radiation and soil heat fluxes in Arctic shrub and wet sedge tundra

et al. 2016

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“…In permafrost regions, surface disturbance induces a relative increase in soil moisture at disturbed sites, as loss of vegetation causes a predominant effect on the decrease in evapotranspiration at the surface. For example, relatively higher soil moisture in the active layer was observed at an early stage after clear-cutting of a larch forest stand in a continuous permafrost zone in Eastern Siberia [34], and at a burned area from tundra fire in a discontinuous permafrost zone on the Seward Peninsula of Alaska [35]. In the case of ARF, soil moisture increase within the fire scar was probable and a certain magnitude of subsidence signal could have been offset.…”

Section: Effects Of Surface Changes Due To Wildfire On Insar Signalmentioning

confidence: 99%

“…Therefore, the rate of thaw settlement is small in the later thawing seasons, as the progress rate of the thawing front is low in the late season. For instance, thaw front progress in Arctic tundra was dulled in early August, and then gradually reached maximum thaw depth in mid-September (e.g., [34,39]). Thaw settlement is therefore active in the early thawing season, as the thaw front rapidly progresses, and becomes significantly slower later in the season when there is only a small change in thaw depth.…”

Section: Uncertainly In Our Insar Subsidence Detection Due To Active mentioning

confidence: 99%

InSAR Detection and Field Evidence for Thermokarst after a Tundra Wildfire, Using ALOS-PALSAR

et al. 2016

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Abstract:Thermokarst is the process of ground subsidence caused by either the thawing of ice-rich permafrost or the melting of massive ground ice. The consequences of permafrost degradation associated with thermokarst for surface ecology, landscape evolution, and hydrological processes have been of great scientific interest and social concern. Part of a tundra patch affected by wildfire in northern Alaska (27.5 km 2 ) was investigated here, using remote sensing and in situ surveys to quantify and understand permafrost thaw dynamics after surface disturbances. A two-pass differential InSAR technique using L-band ALOS-PALSAR has been shown capable of capturing thermokarst subsidence triggered by a tundra fire at a spatial resolution of tens of meters, with supporting evidence from field data and optical satellite images. We have introduced a calibration procedure, comparing burned and unburned areas for InSAR subsidence signals, to remove the noise due to seasonal surface movement. In the first year after the fire, an average subsidence rate of 6.2 cm/year (vertical) was measured. Subsidence in the burned area continued over the following two years, with decreased rates. The mean rate of subsidence observed in our interferograms (from 24 July 2008 to 14 September 2010) was 3.3 cm/year, a value comparable to that estimated from field surveys at two plots on average (2.2 cm/year) for the six years after the fire. These results suggest that this InSAR-measured ground subsidence is caused by the development of thermokarst, a thawing process supported by surface change observations from high-resolution optical images and in situ ground level surveys.

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“…1): Fairbanks in Alaska (Nakai et al, 2013), Tiksi (Kodama et al, 2007;Yabuki et al, 2011;Watanabe et al, 2000) and Chokurdakh (Iwahana et al, 2014) in northeast Siberia, Yakutsk in central east Siberia (Ohta et al, 2001(Ohta et al, , 2008(Ohta et al, , 2014Kotani et al, 2013;Lopez et al, 2007;Yabuki et al, 2011), Tura in central Siberia , and Kevo in northern Europe (Sato et al, 2001; precipitation and air pressure in Kevo are provided by Finnish Meteorological Institute). The longitudes and latitudes of the sites are summarized in Table 1, as well as the observational periods for data collection.…”

Section: Study Sites and Observational Periodsmentioning

confidence: 99%

“…tic conditions at those sites. It is very difficult, however, to create a complete data set for driving a model solely from observations, which are prone to data gaps due to instrument problems, human mistakes, or other reasons (Nakai et al, 2013;Kodama et al, 2007;Watanabe et al, 2000;Iwahana et al, 2014;Ohta et al, 2001Ohta et al, , 2008Ohta et al, , 2014Kotani et al, 2013;Lopez et al, 2007;Nakai et al, 2008;Sato et al, 2001). Despite efforts to maintain and improve our observational network, data gaps are unavoidable, as the availability of instrumentation is often limited by logistical or funding issues.…”

Section: Introductionmentioning

confidence: 99%

The GRENE-TEA model intercomparison project (GTMIP) Stage 1 forcing data set

Sueyoshi

Saitô

Miyazaki

et al. 2016

Earth Syst. Sci. Data

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Abstract. Here, the authors describe the construction of a forcing data set for land surface models (including both physical and biogeochemical models; LSMs) with eight meteorological variables for the 35-year period from 1979 to 2013. The data set is intended for use in a model intercomparison study, called GTMIP, which is a part of the Japanese-funded Arctic Climate Change Research Project. In order to prepare a set of site-fitted forcing data for LSMs with realistic yet continuous entries (i.e. without missing data), four observational sites across the pan-Arctic region (Fairbanks, Tiksi, Yakutsk, and Kevo) were selected to construct a blended data set using both global reanalysis and observational data. Marked improvements were found in the diurnal cycles of surface air temperature and humidity, wind speed, and precipitation. The data sets and participation in GTMIP are open to the scientific community

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Geocryological characteristics of the upper permafrost in a tundra-forest transition of the Indigirka River Valley, Russia

Cited by 44 publications

References 46 publications

Contrasting radiation and soil heat fluxes in Arctic shrub and wet sedge tundra

Contrasting radiation and soil heat fluxes in Arctic shrub and wet sedge tundra

InSAR Detection and Field Evidence for Thermokarst after a Tundra Wildfire, Using ALOS-PALSAR

The GRENE-TEA model intercomparison project (GTMIP) Stage 1 forcing data set

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