@misc{ArboledaZapataAngelopoulosOverduinetal.2022,
  author    = {Arboleda-Zapata, Mauricio and Angelopoulos, Michael and Overduin, Pier Paul and Grosse, Guido and Jones, Benjamin M. and Tronicke, Jens},
  title     = {Exploring the capabilities of electrical resistivity tomography to study subsea permafrost},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1285},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-57123},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-571234},
  pages     = {4423 -- 4445},
  year      = {2022},
  abstract  = {Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.},
  language  = {en}
}
@misc{RungeGrosse2020,
  author    = {Runge, Alexandra and Grosse, Guido},
  title     = {Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1009},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-48031},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-480317},
  pages     = {25},
  year      = {2020},
  abstract  = {Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provides the means to detect, map, and quantify these changes homogeneously across large regions and time scales. Existing Landsat-based algorithms assess different types of disturbances with similar spatiotemporal requirements. However, Landsat-based analyses are restricted in northern high latitudes due to the long repeat interval and frequent clouds, in particular at Arctic coastal sites. We therefore propose to combine Landsat and Sentinel-2 data for enhanced data coverage and present a combined annual mosaic workflow, expanding currently available algorithms, such as LandTrendr, to achieve more reliable time series analysis. We exemplary test the workflow for twelve sites across the northern high latitudes in Siberia. We assessed the number of images and cloud-free pixels, the spatial mosaic coverage and the mosaic quality with spectral comparisons. The number of available images increased steadily from 1999 to 2019 but especially from 2016 onward with the addition of Sentinel-2 images. Consequently, we have an increased number of cloud-free pixels even under challenging environmental conditions, which then serve as the input to the mosaicking process. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas (99.9-100 \%), while Landsat-only mosaics contained data-gaps in the same years, only reaching coverage percentages of 27.2 \%, 58.1 \%, and 69.7 \% for Sobo Sise, East Taymyr, and Kurungnakh in 2017, respectively. The spectral comparison of Landsat image, Sentinel-2 image, and Landsat+Sentinel-2 mosaic showed high correlation between the input images and mosaic bands (e.g., for Kurungnakh 0.91-0.97 between Landsat and Landsat+Sentinel-2 mosaic and 0.92-0.98 between Sentinel-2 and Landsat+Sentinel-2 mosaic) across all twelve study sites, testifying good quality mosaic results. Our results show that especially the results for northern, coastal areas was substantially improved with the Landsat+Sentinel-2 mosaics. By combining Landsat and Sentinel-2 data we accomplished to create reliably high spatial resolution input mosaics for time series analyses. Our approach allows to apply a high temporal continuous time series analysis to northern high latitude permafrost regions for the first time, overcoming substantial data gaps, and assess permafrost disturbance dynamics on an annual scale across large regions with algorithms such as LandTrendr by deriving the location, timing and progression of permafrost thaw disturbances},
  language  = {en}
}
@misc{JonesArpGrosseetal.2020,
  author    = {Jones, Benjamin M. and Arp, Christopher D. and Grosse, Guido and Nitze, Ingmar and Lara, Mark J. and Whitman, Matthew S. and Farquharson, Louise M. and Kanevskiy, Mikhail and Parsekian, Andrew D. and Breen, Amy L. and Ohara, Nori and Rangel, Rodrigo Correa and Hinkel, Kenneth M.},
  title     = {Identifying historical and future potential lake drainage events on the western Arctic coastal plain of Alaska},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-61043},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-610435},
  pages     = {20},
  year      = {2020},
  abstract  = {Arctic lakes located in permafrost regions are susceptible to catastrophic drainage. In this study, we reconstructed historical lake drainage events on the western Arctic Coastal Plain of Alaska between 1955 and 2017 using USGS topographic maps, historical aerial photography (1955), and Landsat Imagery (ca. 1975, ca. 2000, and annually since 2000). We identified 98 lakes larger than 10 ha that partially (>25\% of area) or completely drained during the 62-year period. Decadal-scale lake drainage rates progressively declined from 2.0 lakes/yr (1955-1975), to 1.6 lakes/yr (1975-2000), and to 1.2 lakes/yr (2000-2017) in the ~30,000-km(2) study area. Detailed Landsat trend analysis between 2000 and 2017 identified two years, 2004 and 2006, with a cluster (five or more) of lake drainages probably associated with bank overtopping or headward erosion. To identify future potential lake drainages, we combined the historical lake drainage observations with a geospatial dataset describing lake elevation, hydrologic connectivity, and adjacent lake margin topographic gradients developed with a 5-m-resolution digital surface model. We identified ~1900 lakes likely to be prone to drainage in the future. Of the 20 lakes that drained in the most recent study period, 85\% were identified in this future lake drainage potential dataset. Our assessment of historical lake drainage magnitude, mechanisms and pathways, and identification of potential future lake drainages provides insights into how arctic lowland landscapes may change and evolve in the coming decades to centuries.},
  language  = {en}
}
@misc{RungeGrosse2019,
  author    = {Runge, Alexandra and Grosse, Guido},
  title     = {Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {767},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43866},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-438660},
  pages     = {29},
  year      = {2019},
  abstract  = {The Arctic-Boreal regions experience strong changes of air temperature and precipitation regimes, which affect the thermal state of the permafrost. This results in widespread permafrost-thaw disturbances, some unfolding slowly and over long periods, others occurring rapidly and abruptly. Despite optical remote sensing offering a variety of techniques to assess and monitor landscape changes, a persistent cloud cover decreases the amount of usable images considerably. However, combining data from multiple platforms promises to increase the number of images drastically. We therefore assess the comparability of Landsat-8 and Sentinel-2 imagery and the possibility to use both Landsat and Sentinel-2 images together in time series analyses, achieving a temporally-dense data coverage in Arctic-Boreal regions. We determined overlapping same-day acquisitions of Landsat-8 and Sentinel-2 images for three representative study sites in Eastern Siberia. We then compared the Landsat-8 and Sentinel-2 pixel-pairs, downscaled to 60 m, of corresponding bands and derived the ordinary least squares regression for every band combination. The acquired coefficients were used for spectral bandpass adjustment between the two sensors. The spectral band comparisons showed an overall good fit between Landsat-8 and Sentinel-2 images already. The ordinary least squares regression analyses underline the generally good spectral fit with intercept values between 0.0031 and 0.056 and slope values between 0.531 and 0.877. A spectral comparison after spectral bandpass adjustment of Sentinel-2 values to Landsat-8 shows a nearly perfect alignment between the same-day images. The spectral band adjustment succeeds in adjusting Sentinel-2 spectral values to Landsat-8 very well in Eastern Siberian Arctic-Boreal landscapes. After spectral adjustment, Landsat and Sentinel-2 data can be used to create temporally-dense time series and be applied to assess permafrost landscape changes in Eastern Siberia. Remaining differences between the sensors can be attributed to several factors including heterogeneous terrain, poor cloud and cloud shadow masking, and mixed pixels.},
  language  = {en}
}
@misc{NitzeGrosseJonesetal.2019,
  author    = {Nitze, Ingmar and Grosse, Guido and Jones, Benjamin M. and Romanovsky, Vladimir E. and Boike, Julia},
  title     = {Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {799},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-42617},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426171},
  pages     = {11},
  year      = {2019},
  abstract  = {Local observations indicate that climate change and shifting disturbance regimes are causing permafrost degradation. However, the occurrence and distribution of permafrost region disturbances (PRDs) remain poorly resolved across the Arctic and Subarctic. Here we quantify the abundance and distribution of three primary PRDs using time-series analysis of 30-m resolution Landsat imagery from 1999 to 2014. Our dataset spans four continental-scale transects in North America and Eurasia, covering ~10\% of the permafrost region. Lake area loss (-1.45\%) dominated the study domain with enhanced losses occurring at the boundary between discontinuous and continuous permafrost regions. Fires were the most extensive PRD across boreal regions (6.59\%), but in tundra regions (0.63\%) limited to Alaska. Retrogressive thaw slumps were abundant but highly localized (<10-5\%). Our analysis synergizes the global-scale importance of PRDs. The findings highlight the need to include PRDs in next-generation land surface models to project the permafrost carbon feedback.},
  language  = {en}
}
@misc{FuchsGrosseStraussetal.2018,
  author    = {Fuchs, Matthias and Grosse, Guido and Strauss, Jens and G{\"u}nther, Frank and Grigoriev, Mikhail N. and Maximov, Georgy M. and Hugelius, Gustaf},
  title     = {Carbon and nitrogen pools in thermokarst-affected permafrost landscapes in Arctic Siberia},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  volume    = {15},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {654},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41802},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418026},
  pages     = {19},
  year      = {2018},
  abstract  = {Ice-rich yedoma-dominated landscapes store con- siderable amounts of organic carbon (C) and nitrogen (N) and are vulnerable to degradation under climate warming. We investigate the C and N pools in two thermokarst-affected yedoma landscapes - on Sobo-Sise Island and on Bykovsky Peninsula in the north of eastern Siberia. Soil cores up to 3 m depth were collected along geomorphic gradients and anal- ysed for organic C and N contents. A high vertical sampling density in the profiles allowed the calculation of C and N stocks for short soil column intervals and enhanced under- standing of within-core parameter variability. Profile-level C and N stocks were scaled to the landscape level based on landform classifications from 5 m resolution, multispectral RapidEye satellite imagery. Mean landscape C and N storage in the first metre of soil for Sobo-Sise Island is estimated to be 20.2 kg C m -2 and 1.8 kg N m -2 and for Bykovsky Penin- sula 25.9 kg C m -2 and 2.2 kg N m -2 . Radiocarbon dating demonstrates the Holocene age of thermokarst basin de- posits but also suggests the presence of thick Holocene- age cover layers which can reach up to 2 m on top of in- tact yedoma landforms. Reconstructed sedimentation rates of 0.10-0.57 mm yr -1 suggest sustained mineral soil accu- mulation across all investigated landforms. Both yedoma and thermokarst landforms are characterized by limited accumu- lation of organic soil layers (peat). We further estimate that an active layer deepening of about 100 cm will increase organic C availability in a sea- sonally thawed state in the two study areas by ∼ 5.8 Tg (13.2 kg C m -2 ). Our study demonstrates the importance of increasing the number of C and N storage inventories in ice- rich yedoma and thermokarst environments in order to ac- count for high variability of permafrost and thermokarst en- vironments in pan-permafrost soil C and N pool estimates.},
  language  = {en}
}
@misc{ZwiebackKokeljGuentheretal.2018,
  author    = {Zwieback, Simon and Kokelj, Steven V. and G{\"u}nther, Frank and Boike, Julia and Grosse, Guido and Hajnsek, Irena},
  title     = {Sub-seasonal thaw slump mass wasting is not consistently energy limited at the landscape scale},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {926},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-44568},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-445688},
  pages     = {549 -- 564},
  year      = {2018},
  abstract  = {Predicting future thaw slump activity requires a sound understanding of the atmospheric drivers and geomorphic controls on mass wasting across a range of timescales. On sub-seasonal timescales, sparse measurements indicate that mass wasting at active slumps is often limited by the energy available for melting ground ice, but other factors such as rainfall or the formation of an insulating veneer may also be relevant. To study the sub-seasonal drivers, we derive topographic changes from single-pass radar interferometric data acquired by the TanDEM-X satellites. The estimated elevation changes at 12m resolution complement the commonly observed planimetric retreat rates by providing information on volume losses. Their high vertical precision (around 30 cm), frequent observations (11 days) and large coverage (5000 km(2)) allow us to track mass wasting as drivers such as the available energy change during the summer of 2015 in two study regions. We find that thaw slumps in the Tuktoyaktuk coastlands, Canada, are not energy limited in June, as they undergo limited mass wasting (height loss of around 0 cm day 1) despite the ample available energy, suggesting the widespread presence of early season insulating snow or debris veneer. Later in summer, height losses generally increase (around 3 cm day 1), but they do so in distinct ways. For many slumps, mass wasting tracks the available energy, a temporal pattern that is also observed at coastal yedoma cliffs on the Bykovsky Peninsula, Russia. However, the other two common temporal trajectories are asynchronous with the available energy, as they track strong precipitation events or show a sudden speed-up in late August respectively. The observed temporal patterns are poorly related to slump characteristics like the headwall height. The contrasting temporal behaviour of nearby thaw slumps highlights the importance of complex local and temporally varying controls on mass wasting.},
  language  = {en}
}
@misc{ChenGuentherGrosseetal.2018,
  author    = {Chen, Jie and G{\"u}nther, Frank and Grosse, Guido and Liu, Lin and Lin, Hui},
  title     = {Sentinel-1 InSAR Measurements of Elevation Changes over Yedoma Uplands on Sobo-Sise Island, Lena Delta},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {690},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-42680},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426807},
  pages     = {16},
  year      = {2018},
  abstract  = {Yedoma-extremely ice-rich permafrost with massive ice wedges formed during the Late Pleistocene-is vulnerable to thawing and degradation under climate warming. Thawing of ice-rich Yedoma results in lowering of surface elevations. Quantitative knowledge about surface elevation changes helps us to understand the freeze-thaw processes of the active layer and the potential degradation of Yedoma deposits. In this study, we use C-band Sentinel-1 InSAR measurements to map the elevation changes over ice-rich Yedoma uplands on Sobo-Sise Island, Lena Delta with frequent revisit observations (as short as six or 12 days). We observe significant seasonal thaw subsidence during summer months and heterogeneous inter-annual elevation changes from 2016-17. We also observe interesting patterns of stronger seasonal thaw subsidence on elevated flat Yedoma uplands by comparing to the surrounding Yedoma slopes. Inter-annual analyses from 2016-17 suggest that our observed positive surface elevation changes are likely caused by the delayed progression of the thaw season in 2017, associated with mean annual air temperature fluctuations.},
  language  = {en}
}
@misc{LaraNitzeGrosseetal.2018,
  author    = {Lara, Mark J. and Nitze, Ingmar and Grosse, Guido and Martin, Philip and McGuire, A. David},
  title     = {Reduced arctic tundra productivity linked with landform and climate change interactions},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {550},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-42313},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423132},
  pages     = {10},
  year      = {2018},
  abstract  = {Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (similar to 60,000 km(2)) using the Landsat archive (1999-2014), in combination with novel 30 m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected.},
  language  = {en}
}
@misc{JongejansStraussLenzetal.2018,
  author    = {Jongejans, Loeka Laura and Strauss, Jens and Lenz, Josefine and Peterse, Francien and Mangelsdorf, Kai and Fuchs, Matthias and Grosse, Guido},
  title     = {Organic matter characteristics in yedoma and thermokarst deposits on Baldwin Peninsula, west Alaska},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {20},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-44625},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-446250},
  pages     = {6033 -- 6048},
  year      = {2018},
  abstract  = {As Arctic warming continues and permafrost thaws, more soil and sedimentary organic matter (OM) will be decomposed in northern high latitudes. Still, uncertainties remain in the quality of the OM and the size of the organic carbon (OC) pools stored in different deposit types of permafrost landscapes. This study presents OM data from deep permafrost and lake deposits on the Baldwin Peninsula which is located in the southern portion of the continuous permafrost zone in west Alaska. Sediment samples from yedoma and drained thermokarst lake basin (DTLB) deposits as well as thermokarst lake sediments were analyzed for cryostratigraphical and biogeochemical parameters and their lipid biomarker composition to identify the below-ground OC pool size and OM quality of ice-rich permafrost on the Baldwin Peninsula. We provide the first detailed characterization of yedoma deposits on Baldwin Peninsula. We show that three-quarters of soil OC in the frozen deposits of the study region (total of 68 Mt) is stored in DTLB deposits (52 Mt) and one-quarter in the frozen yedoma deposits (16 Mt). The lake sediments contain a relatively small OC pool (4 Mt), but have the highest volumetric OC content (93 kgm(-3)) compared to the DTLB (35 kgm(-3)) and yedoma deposits (8 kgm(-3)), largely due to differences in the ground ice content. The biomarker analysis indicates that the OM in both yedoma and DTLB deposits is mainly of terrestrial origin. Nevertheless, the relatively high carbon preference index of plant leaf waxes in combination with a lack of a degradation trend with depth in the yedoma deposits indi-cates that OM stored in yedoma is less degraded than that stored in DTLB deposits. This suggests that OM in yedoma has a higher potential for decomposition upon thaw, despite the relatively small size of this pool. These findings show that the use of lipid biomarker analysis is valuable in the assessment of the potential future greenhouse gas emissions from thawing permafrost, especially because this area, close to the discontinuous permafrost boundary, is projected to thaw substantially within the 21st century.},
  language  = {en}
}