Alfred Wegener Institute for Polar and Marine Research
Electronic Publication Information CenterNot a member yet
52828 research outputs found
Sort by
Calving front monitoring at a subseasonal resolution: a deep learning application for Greenland glaciers
Get PDFThe mass balance of the Greenland Ice Sheet is strongly influenced by the dynamics of its outlet glaciers. Therefore, it is of paramount importance to accurately and continuously monitor these glaciers, especially the variation in their frontal positions. A temporally comprehensive parameterization of glacier calving is essential for understanding dynamic changes and constraining ice sheet modeling. However, many current calving front records are limited in terms of temporal resolution as they rely on manual delineation, which is laborious and not appropriate considering the increasing amount of satellite imagery available. In this contribution, we address this problem by applying an automated method to extract calving fronts from optical satellite imagery. The core of this workflow builds on recent advances in the field of deep learning while taking full advantage of multispectral input information. The performance of the method is evaluated using three independent test datasets. For the three datasets, we calculate mean delineation errors of 61.2, 73.7, and 73.5 m, respectively. Eventually, we apply the technique to Landsat-8 imagery. We generate 9243 calving front positions across 23 outlet glaciers in Greenland for the period 2013-2021. Resulting time series not only resolve long-term and seasonal signals but also resolve subseasonal patterns. We discuss the implications for glaciological studies and present a first application for analyzing the effect of bedrock topography on calving front variations. Our method and derived results represent an important step towards the development of intelligent processing strategies for glacier monitoring, opening up new possibilities for studying and modeling the dynamics of Greenland's outlet glaciers
Using ancient sedimentary DNA to forecast ecosystem trajectories under climate change
Get PDFEcosystem response to climate change is complex. In order to forecast ecosystem dynamics, we need high-quality data on changes in past species abundance that can inform process-based models. Sedimentary ancient DNA (sedaDNA) has revolutionised our ability to document past ecosystems’ dynamics. It provides time series of increased taxonomic resolution compared to microfossils (pollen, spores), and can often give species-level information, especially for past vascular plant and mammal abundances. Time series are much richer in information than contemporary spatial distribution information, which have been traditionally used to train models for predicting biodiversity and ecosystem responses to climate change. Here, we outline the potential contribution of sedaDNA to forecast ecosystem changes. We showcase how species-level time series may allow quantification of the effect of biotic interactions in ecosystem dynamics, and be used to estimate dispersal rates when a dense network of sites is available. By combining palaeo-time series, process-based models, and inverse modelling, we can recover the biotic and abiotic processes underlying ecosystem dynamics, which are traditionally very challenging to characterise. Dynamic models informed by sedaDNA can further be used to extrapolate beyond current dynamics and provide robust forecasts of ecosystem responses to future climate change. This article is part of the theme issue ‘Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere’
Diurnal Temperature Range Trends Differ Below and Above the Melting Point
Get PDFThe globally averaged diurnal temperature range (DTR) has shrunk since the mid-20th century, and climate models project further shrinking. Observations indicate a slowdown or reversal of this trend in recent decades. Here, we show that DTR has a minimum for average temperatures close to 0°C. Observed DTR shrinks strongly at colder temperature, where warming shifts the average temperature toward the DTR minimum, and expands at warmer temperature, where warming shifts the average temperature away from the DTR minimum. Most, but not all climate models reproduce the minimum DTR close to average temperatures of 0°C and a stronger DTR shrinking at colder temperature. In models that reproduce the DTR minimum, DTR shrinking slows down significantly in recent decades. Models project that the global-mean DTR will shrink over the 21st century, and models with a DTR minimum close to 0°C project slower shrinking than other models
Storylines of summer Arctic climate change constrained by Barents–Kara seas and Arctic tropospheric warming for climate risk assessment
Get PDFWhile climate models broadly agree on the changes expected to occur over the Arctic with global warming on a pan-Arctic scale (i.e. polar amplification, sea ice loss, and increased precipitation), the magnitude and patterns of these changes at regional and local scales remain uncertain. This limits the usability of climate model projections for risk assessments and their impact on human activities or ecosystems (e.g. fires and permafrost thawing). Whereas any single or ensemble mean projection may be of limited use to stakeholders, recent studies have shown the value of the storyline approach in providing a comprehensive and tractable set of climate projections that can be used to evaluate changes in environmental or societal risks associated with global warming. Here, we apply the storyline approach to a large ensemble of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models with the aim of distilling the wide spread in model predictions into four physically plausible outcomes of Arctic summertime climate change. This is made possible by leveraging strong covariability in the climate system associated with well-known but poorly constrained teleconnections and local processes; specifically, we find that differences in Barents-Kara sea warming and lower-tropospheric warming over polar regions among CMIP6 models explain most of the inter-model variability in pan-Arctic surface summer climate response to global warming. Based on this novel finding, we compare regional disparities in climate change across the four storylines. Our storyline analysis highlights the fact that for a given amount of global warming, certain climate risks can be intensified, while others may be lessened, relative to a "middle-of-the-road"ensemble mean projection. We find this to be particularly relevant when comparing climate change over terrestrial and marine areas of the Arctic which can show substantial differences in their sensitivity to global warming. We conclude by discussing the potential implications of our findings for modelling climate change impacts on ecosystems and human activities
From practitioners’ knowledge to climate modelling and back: – Using climate model projections to provide relevant climate information to Arctic reindeer herding communities
Get PDFHeidrun Matthes1, Sirpa Rasmus2, Roza Laptander3, Teresa Komu2, Kirll Istomin4, Joachim Otto Habeck5, Tim Horstkotte6, Bruce C. Forbes2, Jussi T. Eronen7 and Hans A Tømmervik
Visualizing data on permafrost degradation in a pan-arctic pilot service aiming at a non-scientific audience
Get PDFClimate change has led to an increase in permafrost warming and thaw at global scale. Land surface change associated with permafrost thaw include the acceleration of Arctic coastal erosion, increased thaw slumping in hillslope regions, the drainage and formation of lakes, as well as an intensification of disturbances on land, such as forest fires and droughts. Thermo-erosion threatens infrastructure and leads to gullying, slumping, and even landslides. Arctic communities living on frozen ground are strongly affected by these processes and are increasingly forced to adapt their livelihoods. In some areas, the relocation of settlements has become the last resort and is already actively planned for several communities in Alaska.
Remote sensing analyses can be applied to detect and map permafrost disturbances at high spatial resolution across large regions to quantify landscape change, hydrological dynamics, and permafrost vulnerability. In the ERC PETA-CARB, ESA CCI Permafrost, and NSF Permafrost Discovery Gateway projects, a pan-arctic time series covering twenty years was produced using Landsat TM, ETM+, and OLI imagery. Following good scientific practice, this data is published via a digital data library and also available through a cloud-based analysis platform to facilitate re-use by other scientists.
However, the data is not readily designed and presented to be interpreted by non-scientists and non-experts. In order to make the scientific findings more easily accessible, within the EU Arctic PASSION project we designed a tailored web-based portal specifically targeting non-scientific user communities, stakeholders, and rightsholders as part of the projects Permafrost Pilot Service. With the new portal, the Arctic Landscape EXplorer (ALEX), we provide interactive maps for recent information on land surface changes, hot spots of disturbances, and potential areas of active permafrost thaw and erosion. While focusing on the local to regional scale relevant for private users, as well as local, regional, and state-level decision makers, exploring the data up to the pan-arctic scale may open new avenues for understanding permafrost change for the general public.
Recent consultations with local representatives and stakeholders from Alaska aimed to ensure that their actual information needs are met. Having received positive feedback and strong interest in the tool encouraged us to continue our work
Influence of high-latitude blocking and the northern stratospheric polar vortex on cold-air outbreaks under Arctic amplification of global warming
Get PDFAbstract
It is widely accepted that Arctic amplification (AA)—enhanced Arctic warming relative to global warming—will increasingly moderate cold-air outbreaks (CAOs) to the midlatitudes. Yet, some recent studies also argue that AA over the last three decades to the rest of the present century may contribute to more frequent severe winter weather including disruptive cold spells. To prepare society for future extremes, it is necessary to resolve whether AA and severe midlatitude winter weather are coincidental or physically linked. Severe winter weather events in the northern continents are often related to a range of stratospheric polar vortex (SPV) configurations and atmospheric blocking, but these dynamical drivers are complex and still not fully understood. Here we review recent research advances and paradigms including a nonlinear theory of atmospheric blocking that helps to explain the location, timing and duration of AA/midlatitude weather connections, studies of the polar vortex’s zonal asymmetric and intra-seasonal variations, its southward migration over continents, and its surface impacts. We highlight novel understanding of SPV variability—polar vortex stretching and a stratosphere–troposphere oscillation—that have remained mostly hidden in the predominant research focus on sudden stratospheric warmings. A physical explanation of the two-way vertical coupling process between the polar vortex and blocking highs, taking into account local surface conditions, remains elusive. We conclude that evidence exists for tropical preconditioning of Arctic-midlatitude climate linkages. Recent research using very large-ensemble climate modelling provides an emerging opportunity to robustly quantify internal atmospheric variability when studying the potential response of midlatitude CAOs to AA and sea-ice loss.</jats:p
Exploring glioma heterogeneity through omics networks: from gene network discovery to causal insights and patient stratification
Get PDFGliomas are primary malignant brain tumors with a typically poor prognosis, exhibiting significant heterogeneity across different cancer types. Each glioma type possesses distinct molecular characteristics determining patient prognosis and therapeutic options. This study aims to explore the molecular complexity of gliomas at the transcriptome level, employing a comprehensive approach grounded in network discovery. The graphical lasso method was used to estimate a gene co-expression network for each glioma type from a transcriptomics dataset. Causality was subsequently inferred from correlation networks by estimating the Jacobian matrix. The networks were then analyzed for gene importance using centrality measures and modularity detection, leading to the selection of genes that might play an important role in the disease. Spectral clustering based on patient similarity networks was applied to stratify patients into groups with similar molecular characteristics and to assess whether the resulting clusters align with the diagnosed glioma type. The results presented highlight the ability of the proposed methodology to uncover relevant genes associated with glioma intertumoral heterogeneity. Further investigation might encompass biological validation of the putative biomarkers disclosed
Heterotrophy in marine animal forests in an era of climate change
Get PDFMarine animal forests (MAFs) are benthic ecosystems characterised by biogenic three-dimensional structures formed by suspension feeders such as corals, gorgonians, sponges and bivalves. They comprise highly diversified communities among the most productive in the world's oceans. However, MAFs are in decline due to global and local stressors that threaten the survival and growth of their foundational species and associated biodiversity. Innovative and scalable interventions are needed to address the degradation of MAFs and increase their resilience under global change. Surprisingly, few studies have considered trophic interactions and heterotrophic feeding of MAF suspension feeders as an integral component of MAF conservation. Yet, trophic interactions are important for nutrient cycling, energy flow within the food web, biodiversity, carbon sequestration, and MAF stability. This comprehensive review describes trophic interactions at all levels of ecological organisation in tropical, temperate, and cold-water MAFs. It examines the strengths and weaknesses of available tools for estimating the heterotrophic capacities of the foundational species in MAFs. It then discusses the threats that climate change poses to heterotrophic processes. Finally, it presents strategies for improving trophic interactions and heterotrophy, which can help to maintain the health and resilience of MAFs
Environmental changes in the Eastern Arctic during the Early Gelasian Age: Palynological Data from Lake El'gygytgyn
Get PDFThe 2.373-2.510 Ma BP (isotopic stages 92-99; Early Gelasian Age) interval of the palynological record from Lake El'gygytgyn, northern Chukotka, includes 9 pollen zones characterizing interglacial, interstadial, and glacial plant communities. The boundaries of pollen zones and isotope stages in some cases do not correspond, indicating that the age model developed for the El'gygytgyn core requires revision. Between 2.373 and 2.510 Ma, the warmest climate occurred during MIS93, when larch forests, which included dark coniferous species, spread across the region. Alnus hirsuta (Spach) Turcz. ex Rupr., Chosenia arbutifolia (Pall.) A. K. Skvortsov, and Populus suaveolens Fish. dominated the gallery forests of the river valleys. The development of grass-shrub tundra and larch forest-tundra is associated with periods of climatic cooling, with the coolest conditions occurring at the beginning of MIS97. The consistent presence of Larix pollen throughout the Early Gelasian indicates that even in harsher climatic conditions, larch forest-tundra persisted in the areas of the Anadyr Plateau and Lake El'gygytgyn.</jats:p