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  • 1
    Research Dataset
    Research Dataset
    PANGAEA - Data Publisher for Earth & Environmental Science
    Language: English
    Keywords: Date/Time ; Uniform Resource Locator/Link To Image ; Uniform Resource Locator/Link To Thumbnail ; Digital Camera, Campbell Scientific
    Source: DataCite
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  • 2
    In: Global Change Biology, November 2010, Vol.16(11), pp.3096-3110
    Description: The carbon budgets of the atmosphere and terrestrial ecosystems are closely coupled by vertical gas exchange fluxes. Uncertainties remain with respect to high latitude ecosystems and the processes driving their temporally and spatially highly variable methane (CH) exchange. Problems associated with scaling plot measurements to larger areas in heterogeneous environments are addressed based on intensive field studies on two nested spatial scales in Northern Siberia. CH fluxes on the microsite scale (0.1–100 m) were measured in the Lena River Delta from July through September 2006 by closed chambers and were compared with simultaneous ecosystem scale (10–10 m) flux measurements by the eddy covariance (EC) method. Closed chamber measurements were conducted almost daily on 15 plots in four differently developed polygon centers and on a polygon rim. Controls on CH emission were identified by stepwise multiple regression. In contrast to relatively low ecosystem‐scale fluxes controlled mainly by near‐surface turbulence, fluxes on the microsite scale were almost an order of magnitude higher at the wet polygon centers and near zero at the drier polygon rim and high‐center polygon. Microsite scale CH fluxes varied strongly even within the same microsites. The only statistically significant control on chamber‐based fluxes was surface temperature calculated using the Stefan–Boltzmann equation in the wet polygon centers, whereas no significant control was found for the low emissions from the dry sites. The comparison with the EC measurements reveals differences in controls and the seasonal dynamics between the two measurement scales, which may have consequences for scaling and process‐based models. Despite those differences, closed chamber measurements from within the EC footprint could be scaled by an area‐weighting approach of landcover classes based on high‐resolution imagery to match the total ecosystem‐scale emission. Our nested sampling design allowed for checking scaling results against measurements and to identify potentially missed sources or sinks.
    Keywords: Arctic ; Closed Chambers ; Eddy Covariance ; Methane ; Permafrost ; Scaling ; Tundra
    ISSN: 1354-1013
    E-ISSN: 1365-2486
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  • 3
    In: Global Change Biology, April 2012, Vol.18(4), pp.1428-1440
    Description: Northern peatlands are a major natural source of methane () to the atmosphere. Permafrost conditions and spatial heterogeneity are two of the major challenges for estimating fluxes from the northern high latitudes. This study reports the development of a new model to upscale fluxes from plant communities to ecosystem scale in permafrost peatlands by integrating an existing biogeochemical model DeNitrification‐DeComposition () with a permafrost model Northern Ecosystem Soil Temperature (). A new ebullition module was developed to track the changes of bubble volumes in the soil profile based on the ideal gas law and enry's law. The integrated model was tested against observations of fluxes measured by closed chambers and eddy covariance () method in a polygonal permafrost area in the ena iver elta, ussia. Results from the tests showed that the simulated soil temperature, summer thaw depths and fluxes were in agreement with the measurements at the five chamber observation sites; and the modeled area‐weighted average fluxes were similar to the observations in seasonal patterns and annual totals although discrepancy existed in shorter time scales. This study indicates that the integrated model, –, is capable of upscaling fluxes from plant communities to larger spatial scales.
    Keywords: Dndc ; Methane Flux ; Model ; Nest ; Peatland ; Permafrost ; Upscale
    ISSN: 1354-1013
    E-ISSN: 1365-2486
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  • 4
    In: Journal of Geophysical Research: Atmospheres, 27 January 2003, Vol.108(D2), pp.ALT 4-1-ALT 4-11
    Description: We apply an energy balance model to the snow cover for snowpack accumulation and ablation at a continuous permafrost site on Spitsbergen for the snow‐covered periods from fall 1998 to winter 2000. The model includes net radiative, turbulent, ground, snow, and rain heat flux. The balance yields two distinct types of snow ablation: winter and spring ablation. Energy transferred by sensible heat and rain input reduces the snow cover during the winter, creating internal ice lenses and basal ice. The snowpack ablates during spring in two stages in both years. During the first stage, surface melt and subsequent internal freezing compact and reduce the snow cover, but no runoff is produced. This phase lasts more than twice as long as the second stage. During the second stage, which takes 14 days in both years, melt rates from the snowpack are represented well using the energy balance model. Ground heat fluxes are comparable during spring in both years, but the long persistence of the snow cover in 2000 delays the thawing of the ground. Due to the duration of the snow cover during spring snow melt of both years, the total energy supplied to the ground is significant, between 30 and 50% of the total energy supplied by net radiation.
    Keywords: Snow Cover ; Snow Melt ; Frozen Ground ; Energy Balance ; Spitsbergen
    ISSN: 0148-0227
    E-ISSN: 2156-2202
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  • 5
    Language: English
    In: Remote Sensing of Environment, March 15, 2012, Vol.118, p.162(6)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.rse.2011.10.025 Byline: Sebastian Westermann, Moritz Langer, Julia Boike Keywords: Land surface temperature; MODIS; Snow; Winter; Permafrost; Svalbard Abstract: Thermal remote sensing can quantify climate change in the Arctic, where ground-based measurements continue to be rare. The land surface temperature (LST) is accessible on the pan-arctic scale through a number of remote sensing platforms, such as the "Moderate Resolution Imaging Spectrometer" (MODIS). This study compares remotely sensed LST from MODIS to ground-based point measurements of the snow surface temperature on Svalbard for seven consecutive winters, thus covering more than half of the winter seasons in the operation period of MODIS Terra and Aqua. We find a systematic negative bias of the average winter surface temperature computed from single LST measurements between 1.5 and 6K, with a mean bias of 3K. The bias consistently occurs both for the MODIS L2 and for the daily and eight-day MODIS L3 products, which is explained by two reasons: i) During winter on Svalbard, cold surface temperatures are associated with clear-sky conditions, while warm surface temperatures typically occur during overcast periods. This leads to an overrepresentation of cold temperature in averages computed from remotely sensed LST measurements. ii) The MODIS cloud detection scheme fails to recognize some cloud-covered or partially cloud-covered situations, thus leading to admixing of colder cloud top temperatures. Both effects contribute equally to the total average bias accumulated over the winter season, with effect (i) dominating in some winters, while the observed bias can be fully explained by (ii) in other winters. Article History: Received 7 June 2011; Revised 24 October 2011; Accepted 29 October 2011
    Keywords: Global Temperature Changes ; Clouds (Meteorology)
    ISSN: 0034-4257
    Source: Cengage Learning, Inc.
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  • 6
    Language: English
    In: Journal of Geodesy, 2013, Vol.87(3), pp.287-299
    Description: Our study analyses satellite and land-based observations of the Yakutsk region centred at the Lena watershed, an area characterised mainly by continuous permafrost. Using monthly solutions of the Gravity Recovery And Climate Experiment satellite mission, we detect a mass increase over central Siberia from 2002 to 2007 which reverses into a mass decrease between 2007 and 2011. No significant mass trend is visible for the whole observation period. To further quantify this behaviour, different mass signal components are studied in detail: (1) inter-annual variation in the atmospheric mass, (2) a possible effect of glacial isostatic adjustment (GIA), and (3) hydrological mass variations. In standard processing the atmospheric mass signal is reduced based on the data from numerical weather prediction models. We use surface pressure observations in order to validate this atmospheric reduction. On inter-annual time scale the difference between the atmospheric mass signal from model prediction and from surface pressure observation is $$〈$$ 4 mm in equivalent water height. The effect of GIA on the mass signal over Siberia is calculated using a global ice model and a spherically symmetric, compressible, Maxwell-viscoelastic earth model. The calculation shows that for the investigated area any effect of GIA can be ruled out. Hence, the main part of the signal can be attributed to hydrological mass variations. We briefly discuss potential hydrological effects such as changes in precipitation, river discharge, surface and subsurface water storage.
    Keywords: GRACE ; Permafrost ; Mass transport ; Earth’s system ; Hydrology
    ISSN: 0949-7714
    E-ISSN: 1432-1394
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  • 7
    Language: English
    In: Remote Sensing of Environment, August, 2013, Vol.135, p.12(13)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.rse.2013.03.011 Byline: Moritz Langer, Sebastian Westermann, Max Heikenfeld, Wolfgang Dorn, Julia Boike Abstract: Remote sensing offers great potential for detecting changes of the thermal state of permafrost and active layer dynamics in the context of Arctic warming. This study presents a comprehensive feasibility analysis of satellite-based permafrost modeling for a typical lowland tundra landscape in the Lena River Delta, Siberia. We assessed the performance of a transient permafrost model which is forced by time series of land surface temperatures (LSTs) and snow water equivalents (SWEs) obtained from MODIS and GlobSnow products. Both the satellite products and the model output were evaluated on the basis of long-term field measurements from the Samoylov permafrost observatory. The model was found to successfully reproduce the evolution of the permafrost temperature and freeze-thaw dynamics when calibrated with ground measurements. Monte-Carlo simulations were performed in order to evaluate the impact of inaccuracies in the model forcing and uncertainties in the parameterization. The sensitivity analysis showed that a correct SWE forcing and parameterization of the snow's thermal properties are essential for reliable permafrost modeling. In the worst case, the bias in the modeled permafrost temperatures can amount to 5[degrees]C. For the thaw depth, a maximum uncertainty of about [+ or -]15cm is found due to possible uncertainties in the soil composition. Article History: Received 22 November 2012; Revised 19 March 2013; Accepted 20 March 2013
    Keywords: Monte Carlo Methods -- Analysis ; Tundra Ecology -- Analysis
    ISSN: 0034-4257
    Source: Cengage Learning, Inc.
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  • 8
    Language: English
    In: Global change biology, November 2014, Vol.20(11), pp.3439-56
    Description: In this study latent heat flux (λE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman-Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman-Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control λE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman-Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated λE of different ecosystem types under meteorological conditions at one site. Values of λE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that λE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of λE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling.
    Keywords: Eddy-Covariance ; Evapotranspiration ; Latent Heat ; Phenology ; Stomatal Resistance ; Ecosystem ; Hot Temperature ; Models, Theoretical
    ISSN: 13541013
    E-ISSN: 1365-2486
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  • 9
    Language: English
    In: Boreal Environment Research, 2010, Vol.15, pp.203-217
    Description: This study evaluates the climatic impact of possible future changes in high-latitude inland water surface (IWS) area. We carried out a set of climate-change experiments with an atmospheric general circulation model in which different scenarios of future changes of IWS extent were prescribed....
    Keywords: Sciences of the Universe ; Earth Sciences ; Glaciology ; Ecology
    ISSN: 1239-6095
    E-ISSN: 1797-2469
    Source: Hyper Article en Ligne (CCSd)
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  • 10
    Language: English
    In: Global and Planetary Change, April 2016, Vol.139, pp.116-127
    Description: The focus of this research has been on detecting changes in lake areas, vegetation, land surface temperatures, and the area covered by snow, 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), extending from east of Yakutsk to the central Siberian Plateau, and from the southern Lena River to north of the Vilyui River. Approximately 90% of the area is underlain by continuous permafrost. Remote sensing products were used to analyze changes in water bodies, land surface temperature (LST), and leaf area index (LAI), as well as the occurrence and extent of forest fires, and the area and duration of snow cover. The remote sensing analyses (for LST, snow cover, LAI, and fire) were based on MODIS–derived NASA products (250–1000 m) for 2000 to 2011. Changes in water bodies were calculated from two mosaics of (USGS) Landsat (30 m) satellite images from 2002 and 2009. Within the study area's 315,000 km the total area covered by lakes increased by 17.9% between 2002 and 2009, but this increase varied in different parts of the study area, ranging between 11% and 42%. The land surface temperatures showed a consistent warming trend, with an average increase of about 0.12 °C/year. The average rate of warming during the April–May transition period was 0.17 °C/year and 0.19 °C/year in the September–October period, but ranged up to 0.49 °C/year during September–October. Regional differences in the rates of land surface temperature change, and possible reasons for the temperature changes, are discussed with respect to changes in the land cover. Our analysis of a broad spectrum of variables over the study area suggests that the spring warming trend is very likely to be due to changes in the area covered by snow. The warming trend observed in fall does not, however, appear to be directly related to any changes in the area of snow cover, or to the atmospheric conditions, or to the proportion of the land surface that is covered by water (i.e., to wetting and drying). Supplementary data (original data, digitized version of the maps, metadata) are archived under PANGAEA ( ).
    Keywords: Permafrost ; Central Yakutia ; Lakes ; Land Cover ; Land Surface Warming ; Remote Sensing ; Geology
    ISSN: 0921-8181
    E-ISSN: 1872-6364
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