Alfred Wegener Institute for Polar and Marine Research
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Assessing Seasonal and Inter‐Annual Marine Sediment Climate Proxy Data
Get PDFThree recently published papers including Napier et al. (2022, https://doi.org/10.1029/2021PA004355) utilize novel microanalytical approaches with varved marine sediments to demonstrate the potential to reconstruct seasonal and inter-annual climate variability. Obtaining paleoclimate data at a resolution akin to the observational record is vitally important for improving our understanding of climate phenomena such as monsoons and modes of variability such as the El Niño Southern Oscillation, for which appraisals of past inter-annual variability is critical. The ability to generate seasonal and inter annual resolution sea surface temperature proxy time series spanning a thousand years or more is revolutionary and has the potential to fill gaps in our knowledge of climate variability. Although generally limited to sediments from regions with oxygen depleted bottom waters, there is great potential to integrate shorter seasonal resolution climate “snap shots” from other archives such as annually banded corals into composite time series. But as paleoceanographic data are used more by the observational and modeling fields, we make the case for conducting a thorough case-by-case assessment of the processes that influence the climate signal recovered from proxies, using careful replication to validate new approaches. Understanding or exploring the potential influence of processes which effectively filter the climate signal will lead to more quantitative paleoceanographic data that will better serve the broader climate science community
Evaluating the 11-year solar cycle and short-term 10Be deposition events with novel excess water samples from the East Greenland Ice-core Project (EGRIP)
Get PDF10Be is produced by the interaction between galactic cosmic rays (GCRs) and solar energetic particles (SEPs) with the Earth's atmospheric constituents. The flux of GCRs is modulated by the varying strength of the magnetic fields of the Earth and the Sun. Measurement of 10Be concentrations from polar ice cores is thus a valuable tool to reconstruct the variations in the geomagnetic field and solar activity levels. The interpretation of 10Be records is, however, complicated by non-production-related effects on the 10Be deposition rate caused by climate-or weather-induced variability. Furthermore, volcanic eruptions have been proposed to lead to short-Term 10Be deposition enhancements. In this study, we test the use of excess meltwater from continuous flow analysis (CFA) to measure 10Be, allowing less time-consuming and more cost-effective sample preparation. We compare two records obtained from CFA and discrete samples from the East Greenland Ice core Project (EGRIP) S6 firn core, reaching back to 1900gCE. We find that the two records agree well and that the 10Be record from CFA samples agrees as well as the discrete samples with other records from Greenland. Furthermore, by subtracting the theoretically expected GCR-induced signal, we investigate the high-frequency variability in the 10Be records from Greenland and Antarctica after 1951gCE, focusing on SEP events and volcanic eruptions. Finally, we use the 10Be records from Greenland and Antarctica to study the 11-year solar cycles, allowing us to assess the suitability of the CFA samples for the reconstruction of solar activity. This result opens new opportunities for the collection of continuous 10Be records with less time-consuming sample preparation, while saving an important portion of the ice cores for other measurements
Modern temperatures in central–north Greenland warmest in past millennium
Get PDFThe Greenland Ice Sheet has a central role in the global climate system owing to its size, radiative effects and freshwater storage, and as a potential tipping point1. Weather stations show that the coastal regions are warming2, but the imprint of global warming in the central part of the ice sheet is unclear, owing to missing long-term observations. Current ice-core-based temperature reconstructions3–5 are ambiguous with respect to isolating global warming signatures from natural variability, because they are too noisy and do not include the most recent decades. By systematically redrilling ice cores, we created a high-quality reconstruction of central and north Greenland temperatures from ad 1000 until 2011. Here we show that the warming in the recent reconstructed decade exceeds the range of the pre-industrial temperature variability in the past millennium with virtual certainty (P < 0.001) and is on average 1.5 ± 0.4 degrees Celsius (1 standard error) warmer than the twentieth century. Our findings suggest that these exceptional temperatures arise from the superposition of natural variability with a long-term warming trend, apparent since ad 1800. The disproportionate warming is accompanied by enhanced Greenland meltwater run-off, implying that anthropogenic influence has also arrived in central and north Greenland, which might further accelerate the overall Greenland mass loss
Future projections of wind energy potentials in the arctic for the 21st century under the RCP8.5 scenario from regional climate models (Arctic-CORDEX)
Get PDFThe Arctic has warmed more than twice the rate of the entire globe. To quantify possible climate change effects, we calculate wind energy potentials from a multi-model ensemble of Arctic-CORDEX. For this, we analyze future changes of wind power density (WPD) using an eleven-member multi-model ensemble. Impacts are estimated for two periods (2020–2049 and 2070–2099) of the 21st century under a high emission scenario (RCP8.5). The multi-model mean reveals an increase of seasonal WPD over the Arctic in the future decades. WPD variability across a range of temporal scales is projected to increase over the Arctic. The signal amplifies by the end of 21st century. Future changes in the frequency of wind speeds at 100 m not useable for wind energy production (wind speeds below 4 m/s or above 25 m/s) has been analyzed. The RCM ensemble simulates a more frequent occurrence of 100 m non-usable wind speeds for the wind-turbines over Scandinavia and selected land areas in Alaska, northern Russia and Canada. In contrast, non-usable wind speeds decrease over large parts of Eastern Siberia and in northern Alaska. Thus, our results indicate increased potential of the Arctic for the development and production of wind energy. Bias corrected and not corrected near-surface wind speed and WPD changes have been compared with each other. It has been found that both show the same sign of future change, but differ in magnitude of these changes. The role of sea-ice retreat and vegetation expansion in the Arctic in future on near-surface wind speed variability has been also assessed. Surface roughness through sea-ice and vegetation changes may significantly impact on WPD variability in the Arctic
Tundra conservation challenged by forest expansion in a complex mountainous treeline ecotone as revealed by spatially explicit tree aboveground biomass modeling
Get PDFThe subarctic forest tundra transition zone is one of the most vulnerable ecological regions worldwide and susceptible to climate change. Forest changes could lead to biodiversity losses when tundra areas become colonized. However, the impact of complex landscapes with barriers and channels for seed dispersal is highly understudied. Hence, we investigated potential tree aboveground biomass (AGB) change in mountainous central Chukotka (Siberia) with the individual-based spatially explicit vegetation model Larix vegetation simulator (LAVESI). In a climate sensitivity study, we simulate forest dynamics until 3000 CE for Representative Concentration Pathways (RCPs) with and without hypothetical cooling after 2300 CE to twentieth-century levels. The current state and spatiotemporal dynamics of tree AGB are validated against field and satellite-derived data. Our results suggest densification of existing tree stands and a lagged forest expansion depending on the distance to the current tree line (~39 percent of the total study area, RCP 8.5) under all considered climate scenarios. In scenarios with cooling after 2300 CE, forests stopped expanding and then gradually retreated to their pre-twenty-first-century position (~10 percent, RCP 8.5). However, forest remnants remain in the colonized area, leaving an imprint of forests in former tundra areas, which will likely have an adverse impact on tundra biodiversity
Microbial-enrichment method enables high-throughput metagenomic characterization from host-rich samples
Get PDFHost–microbe interactions have been linked to health and disease states through the use of microbial taxonomic profiling, mostly via 16S ribosomal RNA gene sequencing. However, many mechanistic insights remain elusive, in part because studying the genomes of microbes associated with mammalian tissue is difficult due to the high ratio of host to microbial DNA in such samples. Here we describe a microbial-enrichment method (MEM), which we demonstrate on a wide range of sample types, including saliva, stool, intestinal scrapings, and intestinal mucosal biopsies. MEM enabled high-throughput characterization of microbial metagenomes from human intestinal biopsies by reducing host DNA more than 1,000-fold with minimal microbial community changes (roughly 90% of taxa had no significant differences between MEM-treated and untreated control groups). Shotgun sequencing of MEM-treated human intestinal biopsies enabled characterization of both high- and low-abundance microbial taxa, pathways and genes longitudinally along the gastrointestinal tract. We report the construction of metagenome-assembled genomes directly from human intestinal biopsies for bacteria and archaea at relative abundances as low as 1%. Analysis of metagenome-assembled genomes reveals distinct subpopulation structures between the small and large intestine for some taxa. MEM opens a path for the microbiome field to acquire deeper insights into host–microbe interactions by enabling in-depth characterization of host-tissue-associated microbial communities
Microbes with higher metabolic independence are enriched in human gut microbiomes under stress
Get PDFA wide variety of human diseases are associated with loss of microbial diversity in the human gut, inspiring a great interest in the diagnostic or therapeutic potential of the microbiota. However, the ecological forces that drive diversity reduction in disease states remain unclear, rendering it difficult to ascertain the role of the microbiota in disease emergence or severity. One hypothesis to explain this phenomenon is that microbial diversity is diminished as disease states select for microbial populations that are more fit to survive environmental stress caused by inflammation or other host factors. Here, we tested this hypothesis on a large scale, by developing a software framework to quantify the enrichment of microbial metabolisms in complex metagenomes as a function of microbial diversity. We applied this framework to over 400 gut metagenomes from individuals who are healthy or diagnosed with inflammatory bowel disease (IBD). We found that high metabolic independence (HMI) is a distinguishing characteristic of microbial communities associated with individuals diagnosed with IBD. A classifier we trained using the normalized copy numbers of 33 HMI-associated metabolic modules not only distinguished states of health versus IBD, but also tracked the recovery of the gut microbiome following antibiotic treatment, suggesting that HMI is a hallmark of microbial communities in stressed gut environments
Recent European drying and its link to prevailing large-scale atmospheric patterns
Get PDFThe extreme 2018 and 2022 droughts pose as recent examples of a series of drought events that have hit Europe over the last decades with wide ranging social, environmental and economic impacts. Although the link between atmospheric circulation and meteorological drought is clear and often highlighted during major drought events, there is a lack of in-depth studies linking historical changes in meteorological drought indices and prevailing large-scale atmospheric patterns in Europe. To meet this shortfall, we investigated the relation between changes in large-scale atmospheric patterns and meteorological drought, as indicated by the geopotential height at 500mb (Z500) and the Standardised Precipitation-Evapotranspiration Index (SPEI), respectively. Calculations were done separately for four climate regions (North, West, Central-East and Mediterranean) over the growing season (March–September). Coherent patterns of significant changes towards higher pressure (increasing Z500) and drier conditions (decreasing SPEI) over 1979–2021 are found over West in spring and Central-East in summer. Z500 and SPEI are strongly linked, reflected by both significant (1979–2021) correlations and high co-occurrences (69-96%) between meteorological drought and high-pressure anomaly occurrences since 1900. North shows the most heterogeneous trend patterns and weakest links, but constitutes a hotspot of significantly increasing Z500 in September. Finally, we performed an ensemble-based, European wide analysis of future Z500, based on CMIP6 low-end (SSP126) and high-end (SSP585) 21st century emission scenarios. According to the projected changes, anomalously high-pressure systems will be the new normal regardless of scenario, and well exceeding the 2018 and 2022 levels in the case of the high-end emission scenario. However, due to the limitations of the model ensemble to represent the spatial heterogeneity in historical Z500 variability and trends (1979–2014), projected changes in large-scale circulation, and associated meteorological droughts, are highly uncertain. This paper provides new insight into significant trends in atmospheric circulation over Europe, their strong links to the observed drying trends, and the inability of a CMIP6 ensemble to reproduce the spatial heterogeneity of the circulation changes
Hotspot movement of compound events on the Europe continent
Get PDFClimate indices are often used as a climate monitoring tool, allowing us to understand how the frequency, intensity, and duration of extreme weather events are changing over time. Here, based on complex statistical analysis we identify highly correlated significant pairs of compound events at the highest spatial resolution, on a monthly temporal scale across Europe. Continental-scale monthly analysis unleashes information on compound events such as high-risk zones, hotspots, monthly shifts of hotspots and trends, risk exposure to land cover and population, and identification of maximum increasing trends. While there are many studies on single or compound climate extremes there are only a few studies that addresses the relationship between pairs of hazards, the incorporation of bioclimatic indices, the determination of a grid best-fit copula approach, and the outlining relevance of this work of compound event risks with exposures. In this respect, here, using 27-bivariate and 10-trivariate copula models, we show that the different hazard pairs have high combined risks of indices related to radiation, temperature, evapotranspiration, bioclimatic-based indices, such as the universal thermal climate index, wind chill index, and heat index, mainly over the northern and eastern European countries. Furthermore, we show that over the last 7 decades, agricultural and coastal areas are highly exposed to the risks of defined hotspots of compound events. In some of the hotspots of compound events-identified by clusters, there is no monthly shifts of hotspots, leading to higher impacts when compounded. Future work needs to integrate the framework and process to identify other compound pairs
Towards an interoperable digital ecosystem in Earth System Science research
Get PDFEarth System Science (ESS) relies on the availability of data from varying resources and ranging over different disciplines. Hence, data sources are rich and diverse, including observatories, satellites, measuring campaigns, model simulations, case studies, laboratory experiments as well as citizen science etc. At the same time, practices of professional research data management (RDM) are differing significantly among various disciplines. There are many well-known challenges in enabling a free flow of data in the sense of the FAIR criteria. Such are data quality assurance, unique digital identifiers, access to and integration of data repositories, just to mention a few.
The Helmholtz DataHub Earth&Environment is addressing digitalization in ESS by developing a federated data infrastructure. Existing RDM practices at seven centers of the Helmholtz Association working together in a joint research program within the Research Field Earth and Environment (RF E&E) are harmonized and integrated in a comprehensive way. The vision is to establish a digital research ecosystem fostering digitalization in geosciences and environmental sciences. Hereby, issues of common metadata standards, digital object identifiers for samples, instruments and datasets, defined role models for data sharing certainly play a central role. The various data generating infrastructures are registered digitally in order to collect metadata as early as possible and enrich them along the flow of the research cycle.
Joint RDM bridging several institutions relies on professional practices of distributed software development. Apart from operating cross-center software development teams, the solutions rely on concepts of modular software design. For example, a generic framework has been developed to allow for quick development of tools for domain specific data exploration in a distributed manner. Other tools incorporate automated quality control in data streams. Software is being developed following guiding principles of open and reusable research software development.
A suite of views is being provided, allowing for varying user perspectives, monitoring data flows from sensor to archive, or publishing data in quality assured repositories. Furthermore, high-level data products are being provided for stakeholders and knowledge transfer (for examples see https://datahub.erde-und-umwelt.de). Furthermore, tools for integrated data analysis, e.g. using AI approaches for marine litter detection can be implemented on top of the existing software stack.
Of course, this initiative does not exist in isolation. It is part of a long-term strategy being embedded within national (e.g. NFDI) and international (e.g. EOSC, RDA) initiatives