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Institute
- Institut für Geowissenschaften (138) (remove)
The hydrological budget of a region is determined based on the horizontal and vertical water fluxes acting in both inward and outward directions. These integrated water fluxes vary, altering the total water storage and consequently the gravitational force of the region. The time-dependent gravitational field can be observed through the Gravity Recovery and Climate Experiment (GRACE) gravimetric satellite mission, provided that the mass variation is above the sensitivity of GRACE. This study evaluates mass changes in prominent reservoir regions through three independent approaches viz. fluxes, storages, and gravity, by combining remote sensing products, in-situ data and hydrological model outputs using WaterGAP Global Hydrological Model (WGHM) and Global Land Data Assimilation System (GLDAS). The results show that the dynamics revealed by the GRACE signal can be better explored by a hybrid method, which combines remote sensing-based reservoir volume estimates with hydrological model outputs, than by exclusive model-based storage estimates. For the given arid/ semi-arid regions, GLDAS based storage estimations perform better than WGHM.
Abstract. The aim of this study is to investigate the shallow thermal field differences for two differently aged passive continental margins by analyzing regional variations in geothermal gradient and exploring the controlling factors for these variations. Hence, we analyzed two previously published 3-D conductive and lithospheric-scale thermal models of the Southwest African and the Norwegian passive margins. These 3-D models differentiate various sedimentary, crustal, and mantle units and integrate different geophysical data such as seismic observations and the gravity field. We extracted the temperature–depth distributions in 1 km intervals down to 6 km below the upper thermal boundary condition. The geothermal gradient was then calculated for these intervals between the upper thermal boundary condition and the respective depth levels (1, 2, 3, 4, 5, and 6 km below the upper thermal boundary condition). According to our results, the geothermal gradient decreases with increasing depth and shows varying lateral trends and values for these two different margins. We compare the 3-D geological structural models and the geothermal gradient variations for both thermal models and show how radiogenic heat production, sediment insulating effect, and thermal lithosphere–asthenosphere boundary (LAB) depth influence the shallow thermal field pattern. The results indicate an ongoing process of oceanic mantle cooling at the young Norwegian margin compared with the old SW African passive margin that seems to be thermally equilibrated in the present day.
In this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12m TanDEM-X, 10m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000m of elevation. For the 30m DEMs, the ASTER datasets had the highest vertical standard deviation at > 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all < 3.5 m. Higher-resolution DEMs generally had lower uncertainty, with both the 12m TanDEM-X and 5m ALOSWorld 3D having < 2m vertical standard deviation. Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the low uncertainty across these attributes for SRTM-C (30 m), TanDEM-X (12–30 m), and ALOS World 3D (5–30 m). Single-CoSSC TerraSAR-X/TanDEM-X 10m DEMs and the 30m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on low vertical standard deviations and visual inspection alongside optical satellite data, we selected the 30m SRTM-C, 12–30m TanDEM-X, 10m single-CoSSC TerraSAR-X/TanDEM-X, and 5m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. Consistent m=n values were found using chi plot channel profile analysis, regardless of DEM type and spatial resolution. Slope, curvature, and drainage area were calculated and plotting schemes were used to assess basin-wide differences in the hillslope-to-valley transition related to the knickpoint. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5m ALOS World 3D DEM, which demonstrated high-frequency noise in 2–8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.
Many institutions struggle to tap into the potential of their large archives of radar reflectivity: these data are often affected by miscalibration, yet the bias is typically unknown and temporally volatile. Still, relative calibration techniques can be used to correct the measurements a posteriori. For that purpose, the usage of spaceborne reflectivity observations from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) platforms has become increasingly popular: the calibration bias of a ground radar (GR) is estimated from its average reflectivity difference to the spaceborne radar (SR). Recently, Crisologo et al. (2018) introduced a formal procedure to enhance the reliability of such estimates: each match between SR and GR observations is assigned a quality index, and the calibration bias is inferred as a quality-weighted average of the differences between SR and GR. The relevance of quality was exemplified for the Subic S-band radar in the Philippines, which is greatly affected by partial beam blockage.
The present study extends the concept of quality-weighted averaging by accounting for path-integrated attenuation (PIA) in addition to beam blockage. This extension becomes vital for radars that operate at the C or X band. Correspondingly, the study setup includes a C-band radar that substantially overlaps with the S-band radar. Based on the extended quality-weighting approach, we retrieve, for each of the two ground radars, a time series of calibration bias estimates from suitable SR overpasses. As a result of applying these estimates to correct the ground radar observations, the consistency between the ground radars in the region of overlap increased substantially. Furthermore, we investigated if the bias estimates can be interpolated in time, so that ground radar observations can be corrected even in the absence of prompt SR overpasses. We found that a moving average approach was most suitable for that purpose, although limited by the absence of explicit records of radar maintenance operations.
The interactions between atmosphere and steep topography in the eastern south–central Andes result in complex relations with inhomogenous rainfall distributions. The atmospheric conditions leading to deep convection and extreme rainfall and their spatial patterns—both at the valley and mountain-belt scales—are not well understood. In this study, we aim to identify the dominant atmospheric conditions and their spatial variability by analyzing the convective available potential energy (CAPE) and dew-point temperature (Td). We explain the crucial effect of temperature on extreme rainfall generation along the steep climatic and topographic gradients in the NW Argentine Andes stretching from the low-elevation eastern foreland to the high-elevation central Andean Plateau in the west. Our analysis relies on version 2.0 of the ECMWF’s (European Centre for Medium-RangeWeather Forecasts) Re-Analysis (ERA-interim) data and TRMM (Tropical Rainfall Measuring Mission) data. We make the following key observations: First, we observe distinctive gradients along and across strike of the Andes in dew-point temperature and CAPE that both control rainfall distributions. Second, we identify a nonlinear correlation between rainfall and a combination of dew-point temperature and CAPE through a multivariable regression analysis. The correlation changes in space along the climatic and topographic gradients and helps to explain controlling factors for extreme-rainfall generation. Third, we observe more contribution (or higher importance) of Td in the tropical low-elevation foreland and intermediate-elevation areas as compared to the high-elevation central Andean Plateau for 90th percentile rainfall. In contrast, we observe a higher contribution of CAPE in the intermediate-elevation area between low and high elevation, especially in the transition zone between the tropical and subtropical areas for the 90th percentile rainfall. Fourth, we find that the parameters of the multivariable regression using CAPE and Td can explain rainfall with higher statistical significance for the 90th percentile compared to lower rainfall percentiles. Based on our results, the spatial pattern of rainfall-extreme events during the past ∼16 years can be described by a combination of dew-point temperature and CAPE in the south–central Andes.
Marked along-strike changes in stratigraphy, mountain belt morphology, basement exhumation, and deformation styles characterize the Andean retroarc; these changes have previously been related to spatiotemporal variations in the subduction angle. We modeled new apatite fission track and apatite (U-Th-Sm)/He data from nine ranges located between 26 degrees S and 28 degrees S. Using new and previously published data, we constructed a Cretaceous to Pliocene paleogeographic model that delineates a four-stage tectonic evolution: extensional tectonics during the Cretaceous (120-75 Ma), the formation of a broken foreland basin between 55 and 30 Ma, reheating due to burial beneath sedimentary rocks (18-13 Ma), and deformation, exhumation, and surface uplift during the Late Miocene and the Pliocene (13-3 Ma). Our model highlights how preexisting upper plate structures control the deformation patterns of broken foreland basins. Because retroarc deformation predates flat-slab subduction, we propose that slab anchoring may have been the precursor of Eocene-Oligocene compression in the Andean retroarc. Our model challenges models which consider broken foreland basins and retroarc deformation in the NW Argentinian Andes to be directly related to Miocene flat subduction.
Himalayan water resources attract a rapidly growing number of hydroelectric power projects (HPP) to satisfy Asia's soaring energy demands. Yet HPP operating or planned in steep, glacier-fed mountain rivers face hazards of glacial lake outburst floods (GLOFs) that can damage hydropower infrastructure, alter water and sediment yields, and compromise livelihoods downstream. Detailed appraisals of such GLOF hazards are limited to case studies, however, and a more comprehensive, systematic analysis remains elusive. To this end we estimate the regional exposure of 257 Himalayan HPP to GLOFs, using a flood-wave propagation model fed by Monte Carlo-derived outburst volumes of >2300 glacial lakes. We interpret the spread of thus modeled peak discharges as a predictive uncertainty that arises mainly from outburst volumes and dam-breach rates that are difficult to assess before dams fail. With 66% of sampled HPP are on potential GLOF tracks, up to one third of these HPP could experience GLOF discharges well above local design floods, as hydropower development continues to seek higher sites closer to glacial lakes. We compute that this systematic push of HPP into headwaters effectively doubles the uncertainty about GLOF peak discharge in these locations. Peak discharges farther downstream, in contrast, are easier to predict because GLOF waves attenuate rapidly. Considering this systematic pattern of regional GLOF exposure might aid the site selection of future Himalayan HPP. Our method can augment, and help to regularly update, current hazard assessments, given that global warming is likely changing the number and size of Himalayan meltwater lakes.
The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b(899). The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part.
Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10-100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (similar to 60,000 km(2)) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999-2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.
Most hydrological studies rely on a model calibrated using discharge alone. However, judging the model reliability based on such calibration is problematic, as it does not guarantee the correct representation of internal hydrological processes. This study aims (a) to develop a comprehensive multi-objective calibration framework using remote sensing vegetation data and hydrological signatures (flow duration curve - FDC, and baseflow index) in addition to discharge, and (b) to apply this framework for calibration of the Soil and Water Assessment Tool (SWAT) in a typical Andean catchment. Overall, our calibration approach outperformed traditional discharge-based and FDC signature-based calibration strategies in terms of vegetation, streamflow, and flow partitioning simulation. New hydrological insights for the region are the following: baseflow is the main component of the streamflow sustaining the long dry-season flow, and pasture areas offer higher water yield and baseflow than other land-cover types. The proposed approach could be used in other data-scarce regions with complex topography.
Sediment archives in the terrestrial and marine realm are regularly analyzed to infer changes in climate, tectonic, or anthropogenic boundary conditions of the past. However, contradictory observations have been made regarding whether short period events are faithfully preserved in stratigraphic archives; for instance, in marine sediments offshore large river systems. On the one hand, short period events are hypothesized to be non-detectable in the signature of terrestrially derived sediments due to buffering during sediment transport along large river systems. On the other hand, several studies have detected signals of short period events in marine records offshore large river systems. We propose that this apparent discrepancy is related to the lack of a differentiation between different types of signals and the lack of distinction between river response times and signal propagation times. In this review, we (1) expand the definition of the term ‘signal’ and group signals in sub-categories related to hydraulic grain size characteristics, (2) clarify the different types of ‘times’ and suggest a precise and consistent terminology for future use, and (3) compile and discuss factors influencing the times of signal transfer along sediment routing systems and how those times vary with hydraulic grain size characteristics. Unraveling different types of signals and distinctive time periods related to signal propagation addresses the discrepancies mentioned above and allows a more comprehensive exploration of event preservation in stratigraphy – a prerequisite for reliable environmental reconstructions from terrestrially derived sedimentary records.
The Timpa delle Murge ophiolite in the North Calabrian Unit is part of the Liguride Complex (southern Apennines). The study is concentrated on the gabbroic part of the ophiolite of the Pollino area. They preserve the high-grade ocean floor metamorphic and locally developed flaser textures under ocean floor conditions. The primary magmatic assemblages are clinopyroxene, plagioclase, and opaques. Brown hornblende is a late magmatic phase. Green hornblende, actinolite, albite, chlorite and epidote display metamorphic recrystallization under lower amphibolite facies conditions, followed by greenschist facies.
The gabbros show subalkaline near to alkaline character with a tendency to a more calkalkaline trend. The normalization to primitive mantle and mid-ocean ridge basalt (N-MORB) compositions indicates a considerable depletion in Nb, P, Zr and Ti and an enrichment in Ba, Rb, K, Sr and Eu. This points to a mantle source, which is not compatible with a "normal" mid-ocean ridge situation. Rather, the gabbros are generated from a N-MORB-like melt with a strong crustal component, which was influenced by subduction related fluids and episodic melting during mid-ocean-ridge processes.
Plausible geodynamic settings of the Timpa delle Murge gabbros are oceanic back-arc positions with embryonic MORB-activities. Similar slab contaminated magmatism is also known from the early stage of island arc formation in supra-subduction zone environments like the Izu-Bonin-Mariana island arc.
Human development has far-reaching impacts on the surface of the globe. The transformation of natural land cover occurs in different forms, and urban growth is one of the most eminent transformative processes. We analyze global land cover data and extract cities as defined by maximally connected urban clusters. The analysis of the city size distribution for all cities on the globe confirms Zipf’s law. Moreover, by investigating the percolation properties of the clustering of urban areas we assess the closeness to criticality for various countries. At the critical thresholds, the urban land cover of the countries undergoes a transition from separated clusters to a gigantic component on the country scale. We study the Zipf-exponents as a function of the closeness to percolation and find a systematic dependence, which could be the reason for deviating exponents reported in the literature. Moreover, we investigate the average size of the clusters as a function of the proximity to percolation and find country specific behavior. By relating the standard deviation and the average of cluster sizes—analogous to Taylor’s law—we suggest an alternative way to identify the percolation transition. We calculate spatial correlations of the urban land cover and find long-range correlations. Finally, by relating the areas of cities with population figures we address the global aspect of the allometry of cities, finding an exponent δ ≈ 0.85, i.e., large cities have lower densities.
The origin of Asian monsoons
(2020)
The Cenozoic inception and development of the Asian monsoons remain unclear and have generated much debate, as several hypotheses regarding circulation patterns at work in Asia during the Eocene have been proposed in the few last decades. These include (a) the existence of modern-like monsoons since the early Eocene; (b) that of a weak South Asian monsoon (SAM) and little to no East Asian monsoon (EAM); or (c) a prevalence of the Intertropical Convergence Zone (ITCZ) migrations, also referred to as Indonesian-Australian monsoon (I-AM). As SAM and EAM are supposed to have been triggered or enhanced primarily by Asian palaeogeographic changes, their possible inception in the very dynamic Eocene palaeogeographic context remains an open question, both in the modelling and field-based communities. We investigate here Eocene Asian climate conditions using the IPSL-CM5A2 (Sepulchre et al., 2019) earth system model and revised palaeogeographies. Our Eocene climate simulation yields atmospheric circulation patterns in Asia substantially different from modern conditions. A large high-pressure area is simulated over the Tethys ocean, which generates intense low tropospheric winds blowing southward along the western flank of the proto-Himalayan-Tibetan plateau (HTP) system. This low-level wind system blocks, to latitudes lower than 10 degrees N, the migration of humid and warm air masses coming from the Indian Ocean. This strongly contrasts with the modern SAM, during which equatorial air masses reach a latitude of 20-25 degrees N over India and southeastern China. Another specific feature of our Eocene simulation is the widespread subsidence taking place over northern India in the midtroposphere (around 5000 m), preventing deep convective updraught that would transport water vapour up to the condensation level. Both processes lead to the onset of a broad arid region located over northern India and over the HTP. More humid regions of high seasonality in precipitation encircle this arid area, due to the prevalence of the Intertropical Convergence Zone (ITCZ) migrations (or Indonesian-Australian monsoon, I-AM) rather than monsoons. Although the existence of this central arid region may partly result from the specifics of our simulation (model dependence and palaeogeographic uncertainties) and has yet to be confirmed by proxy records, most of the observational evidence for Eocene monsoons are located in the highly seasonal transition zone between the arid area and the more humid surroundings. We thus suggest that a zonal arid climate prevailed over Asia before the initiation of monsoons that most likely occurred following Eocene palaeogeographic changes. Our results also show that precipitation seasonality should be used with caution to infer the presence of a monsoonal circulation and that the collection of new data in this arid area is of paramount importance to allow the debate to move forward.
In June 2013, widespread flooding and consequent damage and losses occurred in Central Europe, especially in Germany. This paper explores what data are available to investigate the adverse impacts of the event, what kind of information can be retrieved from these data and how well data and information fulfil requirements that were recently proposed for disaster reporting on the European and international levels. In accordance with the European Floods Directive (2007/60/EC), impacts on human health, economic activities (and assets), cultural heritage and the environment are described on the national and sub-national scale. Information from governmental reports is complemented by communications on traffic disruptions and surveys of flood-affected residents and companies.
Overall, the impacts of the flood event in 2013 were manifold. The study reveals that flood-affected residents suffered from a large range of impacts, among which mental health and supply problems were perceived more seriously than financial losses. The most frequent damage type among affected companies was business interruption. This demonstrates that the current scientific focus on direct (financial) damage is insufficient to describe the overall impacts and severity of flood events.
The case further demonstrates that procedures and standards for impact data collection in Germany are widely missing. Present impact data in Germany are fragmentary, heterogeneous, incomplete and difficult to access. In order to fulfil, for example, the monitoring and reporting requirements of the Sendai Framework for Disaster Risk Reduction 2015–2030 that was adopted in March 2015 in Sendai, Japan, more efforts on impact data collection are needed.
The first step towards assessing hazards in seismically active regions involves mapping capable faults and estimating their recurrence times. While the mapping of active faults is commonly based on distinct geologic and geomorphic features evident at the surface, mapping blind seismogenic faults is complicated by the absence of on-fault diagnostic features. Here we investigated the Pichilemu Fault in coastal Chile, unknown until it generated a Mw 7.0 earthquake in 2010. The lack of evident surface faulting suggests activity along a partly-hidden blind fault. We used off-fault deformed marine terraces to estimate a fault-slip rate of 0.52 ± 0.04 m/ka, which, when integrated with satellite geodesy suggests a 2.12 ± 0.2 ka recurrence time for Mw~7.0 normal-faulting earthquakes. We propose that extension in the Pichilemu region is associated with stress changes during megathrust earthquakes and accommodated by sporadic slip during upper-plate earthquakes, which has implications for assessing the seismic potential of cryptic faults along convergent margins and elsewhere.
Sedimentary ancient DNA has been proposed as a key methodology for reconstructing biodiversity over time. Yet, despite the concentration of Earth’s biodiversity in the tropics, this method has rarely been applied in this region. Moreover, the taphonomy of sedimentary DNA, especially in tropical environments, is poorly understood. This study elucidates challenges and opportunities of sedimentary ancient DNA approaches for reconstructing tropical biodiversity. We present shotgun-sequenced metagenomic profiles and DNA degradation patterns from multiple sediment cores from Mubwindi Swamp, located in Bwindi Impenetrable Forest (Uganda), one of the most diverse forests in Africa. We describe the taxonomic composition of the sediments covering the past 2200 years and compare the sedimentary DNA data with a comprehensive set of environmental and sedimentological parameters to unravel the conditions of DNA degradation. Consistent with the preservation of authentic ancient DNA in tropical swamp sediments, DNA concentration and mean fragment length declined exponentially with age and depth, while terminal deamination increased with age. DNA preservation patterns cannot be explained by any environmental parameter alone, but age seems to be the primary driver of DNA degradation in the swamp. Besides degradation, the presence of living microbial communities in the sediment also affects DNA quantity. Critically, 92.3% of our metagenomic data of a total 81.8 million unique, merged reads cannot be taxonomically identified due to the absence of genomic references in public databases. Of the remaining 7.7%, most of the data (93.0%) derive from Bacteria and Archaea, whereas only 0–5.8% are from Metazoa and 0–6.9% from Viridiplantae, in part due to unbalanced taxa representation in the reference data. The plant DNA record at ordinal level agrees well with local pollen data but resolves less diversity. Our animal DNA record reveals the presence of 41 native taxa (16 orders) including Afrotheria, Carnivora, and Ruminantia at Bwindi during the past 2200 years. Overall, we observe no decline in taxonomic richness with increasing age suggesting that several-thousand-year-old information on past biodiversity can be retrieved from tropical sediments. However, comprehensive genomic surveys of tropical biota need prioritization for sedimentary DNA to be a viable methodology for future tropical biodiversity studies.
The Arctic is greatly impacted by climate change. The increase in air temperature drives the thawing of permafrost and an increase in coastal erosion and river discharge. This leads to a greater input of sediment and organic matter into coastal waters, which substantially impacts the ecosystems by reducing light transmission through the water column and altering the biogeochemistry, but also the subsistence economy of local people, and changes in climate because of the transformation of organic matter into greenhouse gases. Yet, the quantification of suspended sediment in Arctic coastal and nearshore waters remains unsatisfactory due to the absence of dedicated algorithms to resolve the high loads occurring in the close vicinity of the shoreline. In this study we present the Arctic Nearshore Turbidity Algorithm (ANTA), the first reflectance-turbidity relationship specifically targeted towards Arctic nearshore waters that is tuned with in-situ measurements from the nearshore waters of Herschel Island Qikiqtaruk in the western Canadian Arctic. A semi-empirical model was calibrated for several relevant sensors in ocean color remote sensing, including MODIS, Sentinel 3 (OLCI), Landsat 8 (OLI), and Sentinel 2 (MSI), as well as the older Landsat sensors TM and ETM+. The ANTA performed better with Landsat 8 than with Sentinel 2 and Sentinel 3. The application of the ANTA to Sentinel 2 imagery that matches in-situ turbidity samples taken in Adventfjorden, Svalbard, shows transferability to nearshore areas beyond Herschel Island Qikiqtaruk.
Holocene temperature proxy records are commonly used in quantitative synthesis and model-data comparisons. However, comparing correlations between time series from records collected in proximity to one another with the expected correlations based on climate model simulations indicates either regional or noisy climate signals in Holocene temperature proxy records. In this study, we evaluate the consistency of spatial correlations present in Holocene proxy records with those found in data from the Last Glacial Maximum (LGM). Specifically, we predict correlations expected in LGM proxy records if the only difference to Holocene correlations would be due to more time uncertainty and more climate variability in the LGM. We compare this simple prediction to the actual correlation structure in the LGM proxy records. We found that time series data of ice-core stable isotope records and planktonic foraminifera Mg/Ca ratios were consistent between the Holocene and LGM periods, while time series of Uk'37 proxy records were not as we found no correlation between nearby LGM records. Our results support the finding of highly regional or noisy marine proxy records in the compilation analysed here and suggest the need for further studies on the role of climate proxies and the processes of climate signal recording and preservation.
In this study, we analyze interactions in lake and lake catchment systems of a continuous permafrost area. We assessed colored dissolved organic matter (CDOM) absorption at 440 nm (a(440)(CDOM)) and absorption slope (S300-500) in lakes using field sampling and optical remote sensing data for an area of 350 km(2) in Central Yamal, Siberia. Applying a CDOM algorithm (ratio of green and red band reflectance) for two high spatial resolution multispectral GeoEye-1 and Worldview-2 satellite images, we were able to extrapolate the a()(CDOM) data from 18 lakes sampled in the field to 356 lakes in the study area (model R-2 = 0.79). Values of a(440)(CDOM) in 356 lakes varied from 0.48 to 8.35 m(-1) with a median of 1.43 m(-1). This a()(CDOM) dataset was used to relate lake CDOM to 17 lake and lake catchment parameters derived from optical and radar remote sensing data and from digital elevation model analysis in order to establish the parameters controlling CDOM in lakes on the Yamal Peninsula. Regression tree model and boosted regression tree analysis showed that the activity of cryogenic processes (thermocirques) in the lake shores and lake water level were the two most important controls, explaining 48.4% and 28.4% of lake CDOM, respectively (R-2 = 0.61). Activation of thermocirques led to a large input of terrestrial organic matter and sediments from catchments and thawed permafrost to lakes (n = 15, mean a(440)(CDOM) = 5.3 m(-1)). Large lakes on the floodplain with a connection to Mordy-Yakha River received more CDOM (n = 7, mean a(440)(CDOM) = 3.8 m(-1)) compared to lakes located on higher terraces.
Changes in species' distributions are classically projected based on their climate envelopes. For Siberian forests, which have a tremendous significance for vegetation-climate feedbacks, this implies future shifts of each of the forest-forming larch (Larix) species to the north-east. However, in addition to abiotic factors, reliable projections must assess the role of historical biogeography and biotic interactions. Here, we use sedimentary ancient DNA and individual-based modelling to investigate the distribution of larch species and mitochondrial haplotypes through space and time across the treeline ecotone on the southern Taymyr peninsula, which at the same time presents a boundary area of two larch species. We find spatial and temporal patterns, which suggest that forest density is the most influential driver determining the precise distribution of species and mitochondrial haplotypes. This suggests a strong influence of competition on the species' range shifts. These findings imply possible climate change outcomes that are directly opposed to projections based purely on climate envelopes. Investigations of such fine-scale processes of biodiversity change through time are possible using paleoenvironmental DNA, which is available much more readily than visible fossils and can provide information at a level of resolution that is not reached in classical palaeoecology.
Glaciated high-alpine areas are fundamentally altered by climate change, with well-known implications for hydrology, e.g., due to glacier retreat, longer snow-free periods, and more frequent and intense summer rainstorms. While knowledge on how these hydrological changes will propagate to suspended sediment dynamics is still scarce, it is needed to inform mitigation and adaptation strategies. To understand the processes and source areas most relevant to sediment dynamics, we analyzed discharge and sediment dynamics in high temporal resolution as well as their patterns on several spatial scales, which to date few studies have done.
We used a nested catchment setup in the Upper Ötztal in Tyrol, Austria, where high-resolution (15 min) time series of discharge and suspended sediment concentrations are available for up to 15 years (2006–2020). The catchments of the gauges in Vent, Sölden and Tumpen range from 100 to almost 800 km2 with 10 % to 30 % glacier cover and span an elevation range of 930 to 3772 m a.s.l. We analyzed discharge and suspended sediment yields (SSY), their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. We complemented our analysis by linking the observations to satellite-based snow cover maps, glacier inventories, mass balances and precipitation data.
Our results indicate that the areas above 2500 m a.s.l., characterized by glacier tongues and the most recently deglaciated areas, are crucial for sediment generation in all sub-catchments. This notion is supported by the synchronous spring onset of sediment export at the three gauges, which coincides with snowmelt above 2500 m but lags behind spring discharge onsets. This points at a limitation of suspended sediment supply as long as the areas above 2500 m are snow-covered. The positive correlation of annual SSY with glacier cover (among catchments) and glacier mass balances (within a catchment) further supports the importance of the glacier-dominated areas. The analysis of short-term events showed that summer precipitation events were associated with peak sediment concentrations and yields but on average accounted for only 21 % of the annual SSY in the headwaters. These results indicate that under current conditions, thermally induced sediment export (through snow and glacier melt) is dominant in the study area.
Our results extend the scientific knowledge on current hydro-sedimentological conditions in glaciated high-alpine areas and provide a baseline for studies on projected future changes in hydro-sedimentological system dynamics.
Graphite forms the endpoint for organic carbon metamorphism; it is extremely resilient to physical, biological and chemical degradation. Carbonaceous materials (CM) contained within sediments, collected across Taiwan and from the Gaoping submarine canyon, were analyzed using Raman spectroscopy to determine the crystallinity. This allowed the erosional and orogenic movements of petrogenic organic carbon (OCpetro) during the Taiwanese orogeny to be deduced. After automatically fitting and classifying spectra, the distribution of four groups of CM within the sediments provides evidence that many forms of OCpetro have survived at least one previous cycle of erosion, transport and burial before forming rocks in the Western Foothills of the island. There is extensive detrital graphite present in rocks that have not experienced high-grade metamorphism, and graphite flakes are also found in recently deposited marine sediments off Taiwan. The tectonic and geological history of the island shows that these graphite flakes must have survived at least three episodes of recycling. Therefore, transformation to graphite during burial and orogeny is a mechanism for stabilizing organic carbon over geological time, removing biospheric carbon from the active carbon cycle and protecting it from oxidation during future erosion events.
Nearly 13,000 years ago, the warming trend into the Holocene was sharply interrupted by a reversal to near glacial conditions. Climatic causes and ecological consequences of the Younger Dryas (YD) have been extensively studied, however proxy archives from the Mediterranean basin capturing this period are scarce and do not provide annual resolution. Here, we report a hydroclimatic reconstruction from stable isotopes (delta O-18, delta C-13) in subfossil pines from southern France. Growing before and during the transition period into the YD (12 900-12 600 cal BP), the trees provide an annually resolved, continuous sequence of atmospheric change. Isotopic signature of tree sourcewater (delta O-18(sw)) and estimates of relative air humidity were reconstructed as a proxy for variations in air mass origin and precipitation regime. We find a distinct increase in inter-annual variability of sourcewater isotopes (delta O-18(sw)), with three major downturn phases of increasing magnitude beginning at 12 740 cal BP. The observed variation most likely results from an amplified intensity of North Atlantic (low delta O-18(sw)) versus Mediterranean (high delta O-18(sw)) precipitation. This marked pattern of climate variability is not seen in records from higher latitudes and is likely a consequence of atmospheric circulation oscillations at the margin of the southward moving polar front.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
Orthopyroxenes of a high temperature protomylonite of the Ivrea Zone, Northern Italy show twin like polysynthetic lamellae parallel to {210} of the hypersthene host. The transformation is caused by plastic deformation under high metamorphic conditions which has resulted in dynamic recrystallization of pyroxene and plagioclase. The lamellae consist of clinohypersthene. The twin plane and the lamellar clino-orthoinversion of hypersthene due to natural deformation have not been described hitherto.
Lake sediments are increasingly explored as reliable paleoflood archives. In addition to established flood proxies including detrital layer thickness, chemical composition, and grain size, we explore stable oxygen and carbon isotope data as paleoflood proxies for lakes in catchments with carbonate bedrock geology. In a case study from Lake Mondsee (Austria), we integrate high-resolution sediment trapping at a proximal and a distal location and stable isotope analyses of varved lake sediments to investigate flood-triggered detrital sediment flux. First, we demonstrate a relation between runoff, detrital sediment flux, and isotope values in the sediment trap record covering the period 2011-2013 CE including 22 events with daily (hourly) peak runoff ranging from 10 (24) m(3) s(-1) to 79 (110) m(3) s(-1). The three- to ten-fold lower flood-triggered detrital sediment deposition in the distal trap is well reflected by attenuated peaks in the stable isotope values of trapped sediments. Next, we show that all nine flood-triggered detrital layers deposited in a sediment record from 1988 to 2013 have elevated isotope values compared with endogenic calcite. In addition, even two runoff events that did not cause the deposition of visible detrital layers are distinguished by higher isotope values. Empirical thresholds in the isotope data allow estimation of magnitudes of the majority of floods, although in some cases flood magnitudes are overestimated because local effects can result in too-high isotope values. Hence we present a proof of concept for stable isotopes as reliable tool for reconstructing flood frequency and, although with some limitations, even for flood magnitudes.
High Mountain Asia (HMA) - encompassing the Tibetan Plateau and surrounding mountain ranges - is the primary water source for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications - such as agriculture, drinking-water generation, and hydropower - rely on consistent and predictable snowmelt runoff. Here, we examine passive microwave data across HMA with five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM) from 1987 to 2016 to track the timing of the snowmelt season - defined here as the time between maximum passive microwave signal separation and snow clearance. We validated our method against climate model surface temperatures, optical remote-sensing snow-cover data, and a manual control dataset (n = 2100, 3 variables at 25 locations over 28 years); our algorithm is generally accurate within 3-5 days. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29-year) time series, along with complex interannual snowfall variations, makes determining trends in snowmelt dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations. (1) The end of the snowmelt season is trending almost universally earlier in HMA (negative trends). Changes in the end of the snowmelt season are generally between 2 and 8 days decade 1 over the 29-year study period (5-25 days total). The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later peak signal separation (positive trends), but with generally smaller magnitudes than trends in snowmelt end. (2) Areas with long snowmelt periods, such as the Tibetan Plateau, show the strongest compression of the snowmelt season (negative trends). These trends are apparent regardless of the time period over which the regression is performed. (3) While trends averaged over 3 decades indicate generally earlier snowmelt seasons, data from the last 14 years (2002-2016) exhibit positive trends in many regions, such as parts of the Pamir and Kunlun Shan. Due to the short nature of the time series, it is not clear whether this change is a reversal of a long-term trend or simply interannual variability. (4) Some regions with stable or growing glaciers - such as the Karakoram and Kunlun Shan - see slightly later snowmelt seasons and longer snowmelt periods. It is likely that changes in the snowmelt regime of HMA account for some of the observed heterogeneity in glacier response to climate change. While the decadal increases in regional temperature have in general led to earlier and shortened melt seasons, changes in HMA's cryosphere have been spatially and temporally heterogeneous.
Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al., 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land–atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms.
Millennial-scale palaeoclimate variability has been documented in various terrestrial and marine palaeoclimate proxy records throughout the Northern Hemisphere for the last glacial cycle. Its clear expression and rapid shifts between different states of climate (Greenland Interstadials and Stadials) represents a correlation tool beyond the resolution of e.g. luminescence dating, especially relevant for terrestrial deposits. Usually, comparison of terrestrial proxy datasets and the Greenland ice cores indicates a complex expression of millennial-scale climate variability as recorded in terrestrial geoarchives including loess. Loess is the most widespread terrestrial geoarchive of the Quaternary and especially widespread over Eurasia. However, loess often records a smoothed representation of millennial-scale variability without all fidelity when compared to the Greenland data, this being a relevant limiting feature in integrating loess with other palaeoclimate records. To better understand the loess proxy-response to millennial-scale climate variability, we simulate a proxy signal smoothing by natural processes through application of low-pass filters of delta O-18 data from Greenland, a high-resolution palaeoclimate reference record, alongside speleothem isotope records from the Black Sea-Mediterranean region. We show that low-pass filters represent rather simple models for better constraining the expression of millennial-scale climate variability in low sedimentation environments, and in sediments where proxy-response signals are most likely affected by natural smoothing (by e.g. bioturbation). Interestingly, smoothed datasets from Greenland and the Black Sea-Mediterranean region are most similar in the last similar to 15 ka and between similar to 50-30 ka. Between similar to 30-15 ka, roughly corresponding to the Last Glacial Maximum and the deglaciation, the records show dissimilarities, challenging the construction of robust correlative time-scales in this age range. From our analysis it becomes apparent that patterns of palaeoclimate signals in loess-palaeosol sequences often might be better explained by smoothed Greenland reference data than the original high-resolution Greenland dataset, or other reference data. This opens the possibility to better assess the temporal resolution and palaeoclimate potential of loess-palaeosol sequences in recording supra-regional climate patterns, as well as to securely integrate loess with other chronologically better-resolved palaeoclimate records.
Near-surface geophysical imaging of alluvial fan settings is a challenging task but crucial for understating geological processes in such settings. The alluvial fan of Ghor Al-Haditha at the southeast shore of the Dead Sea is strongly affected by localized subsidence and destructive sinkhole collapses, with a significantly increasing sinkhole formation rate since ca. 1983. A similar increase is observed also on the western shore of the Dead Sea, in correlation with an ongoing decline in the Dead Sea level. Since different structural models of the upper 50 m of the alluvial fan and varying hypothetical sinkhole processes have been suggested for the Ghor Al-Haditha area in the past, this study aimed to clarify the subsurface characteristics responsible for sinkhole development.
For this purpose, high-frequency shear wave reflection vibratory seismic surveys were carried out in the Ghor Al-Haditha area along several crossing and parallel profiles with a total length of 1.8 and 2.1 km in 2013 and 2014, respectively. The sedimentary architecture of the alluvial fan at Ghor Al-Haditha is resolved down to a depth of nearly 200 m at a high resolution and is calibrated with the stratigraphic profiles of two boreholes located inside the survey area.
The most surprising result of the survey is the absence of evidence of a thick (> 2–10 m) compacted salt layer formerly suggested to lie at ca. 35–40 m depth. Instead, seismic reflection amplitudes and velocities image with good continuity a complex interlocking of alluvial fan deposits and lacustrine sediments of the Dead Sea between 0 and 200 m depth. Furthermore, the underground section of areas affected by sinkholes is characterized by highly scattering wave fields and reduced seismic interval velocities. We propose that the Dead Sea mud layers, which comprise distributed inclusions or lenses of evaporitic chloride, sulfate, and carbonate minerals as well as clay silicates, become increasingly exposed to unsaturated water as the sea level declines and are consequently destabilized and mobilized by both dissolution and physical erosion in the subsurface. This new interpretation of the underlying cause of sinkhole development is supported by surface observations in nearby channel systems. Overall, this study shows that shear wave seismic reflection technique is a promising method for enhanced near-surface imaging in such challenging alluvial fan settings.
Large rock slope failures play a pivotal role in long-term landscape evolution and are a major concern in land use planning and hazard aspects. While the failure phase and the time immediately prior to failure are increasingly well studied, the nature of the preparation phase remains enigmatic. This knowledge gap is due, to a large degree, to difficulties associated with instrumenting high mountain terrain and the local nature of classic monitoring methods, which does not allow integral observation of large rock volumes. Here, we analyse data from a small network of up to seven seismic sensors installed during July-October 2018 (with 43 days of data loss) at the summit of the Hochvogel, a 2592 m high Alpine peak. We develop proxy time series indicative of cyclic and progressive changes of the summit. Modal analysis, horizontal-to-vertical spectral ratio data and end-member modelling analysis reveal diurnal cycles of increasing and decreasing coupling stiffness of a 260,000 m(3) large, instable rock volume, due to thermal forcing. Relative seismic wave velocity changes also indicate diurnal accumulation and release of stress within the rock mass. At longer time scales, there is a systematic superimposed pattern of stress increased over multiple days and episodic stress release within a few days, expressed in an increased emission of short seismic pulses indicative of rock cracking. Our data provide essential first order information on the development of large-scale slope instabilities towards catastrophic failure. (c) 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd
The intensification of Northern Hemisphere glaciation (iNHG) and uplift of the Tibetan Plateau have been argued to be among the main drivers of climate change in midlatitude Central Asia during the Pliocene/Pleistocene. While most proxy records that support this hypothesis are from regions outside the Tibetan Plateau (such as from the Chinese Loess Plateau), detailed paleoclimatic information for the plateau itself during that time has yet remained elusive. Here we present a temporally highly resolved (similar to 500 years) sedimentological record from the Qaidam Basin situated on the northeastern Tibetan Plateau that shows pronounced glacial-interglacial climate variability during the interval from 2.7 to 2.1 Ma. Glacial (interglacial) intervals are generally characterized by coarser (finer) grain size, minima (maxima) in organic matter content, and maxima (minima) in carbonate content. Comparison of our results with Earth's orbital parameters and proxy records from the Chinese Loess Plateau suggests that the observed climate fluctuations were mainly driven by changes in the Siberian High/East Asian winter monsoon system as a response to the iNHG. They are further proposed to be enhanced by the topography of the Tibetan Plateau and its impact on the position and intensity of the westerlies.
Sediment Transit Time and Floodplain Storage Dynamics in Alluvial Rivers Revealed by Meteoric 10Be
(2020)
Quantifying the time scales of sediment transport and storage through river systems is fundamental for understanding weathering processes, biogeochemical cycling, and improving watershed management, but measuring sediment transit time is challenging. Here we provide the first systematic test of measuring cosmogenic meteoric Beryllium-10 (10Bem) in the sediment load of a large alluvial river to quantify sediment transit times. We take advantage of a natural experiment in the Rio Bermejo, a lowland alluvial river traversing the east Andean foreland basin in northern Argentina. This river has no tributaries along its trunk channel for nearly 1,300 km downstream from the mountain front. We sampled suspended sediment depth profiles along the channel and measured the concentrations of 10Bem in the chemically extracted grain coatings. We calculated depth-integrated 10Bem concentrations using sediment flux data and found that 10Bem concentrations increase 230% from upstream to downstream, indicating a mean total sediment transit time of 8.4 ± 2.2 kyr. Bulk sediment budget-based estimates of channel belt and fan storage times suggest that the 10Bem tracer records mixing of old and young sediment reservoirs. On a reach scale, 10Bem transit times are shorter where the channel is braided and superelevated above the floodplain, and longer where the channel is incised and meandering, suggesting that transit time is controlled by channel morphodynamics. This is the first systematic application of 10Bem as a sediment transit time tracer and highlights the method's potential for inferring sediment routing and storage dynamics in large river systems.
The semiarid northeast of Brazil is one of the most densely populated dryland regions in the world and recurrently affected by severe droughts. Thus, reliable seasonal forecasts of streamflow and reservoir storage are of high value for water managers. Such forecasts can be generated by applying either hydrological models representing underlying processes or statistical relationships exploiting correlations among meteorological and hydrological variables. This work evaluates and compares the performances of seasonal reservoir storage forecasts derived by a process-based hydrological model and a statistical approach.
Driven by observations, both models achieve similar simulation accuracies. In a hindcast experiment, however, the accuracy of estimating regional reservoir storages was considerably lower using the process-based hydrological model, whereas the resolution and reliability of drought event predictions were similar by both approaches. Further investigations regarding the deficiencies of the process-based model revealed a significant influence of antecedent wetness conditions and a higher sensitivity of model prediction performance to rainfall forecast quality.
Within the scope of this study, the statistical model proved to be the more straightforward approach for predictions of reservoir level and drought events at regionally and monthly aggregated scales. However, for forecasts at finer scales of space and time or for the investigation of underlying processes, the costly initialisation and application of a process-based model can be worthwhile. Furthermore, the application of innovative data products, such as remote sensing data, and operational model correction methods, like data assimilation, may allow for an enhanced exploitation of the advanced capabilities of process-based hydrological models.
Hydrometeorological hazards caused losses of approximately 110 billion U.S. Dollars in 2016 worldwide. Current damage estimations do not consider the uncertainties in a comprehensive way, and they are not consistent between spatial scales. Aggregated land use data are used at larger spatial scales, although detailed exposure data at the object level, such as openstreetmap.org, is becoming increasingly available across the globe.We present a probabilistic approach for object-based damage estimation which represents uncertainties and is fully scalable in space. The approach is applied and validated to company damage from the flood of 2013 in Germany. Damage estimates are more accurate compared to damage models using land use data, and the estimation works reliably at all spatial scales. Therefore, it can as well be used for pre-event analysis and risk assessments. This method takes hydrometeorological damage estimation and risk assessments to the next level, making damage estimates and their uncertainties fully scalable in space, from object to country level, and enabling the exploitation of new exposure data.
In this study, we investigated the scale sizes of equatorial plasma irregularities (EPIs) using measurements from the Swarm satellites during its early mission and final constellation phases. We found that with longitudinal separation between Swarm satellites larger than 0.4°, no significant correlation was found any more. This result suggests that EPI structures include plasma density scale sizes less than 44 km in the zonal direction. During the Swarm earlier mission phase, clearly better EPI correlations are obtained in the northern hemisphere, implying more fragmented irregularities in the southern hemisphere where the ambient magnetic field is low. The previously reported inverted-C shell structure of EPIs is generally confirmed by the Swarm observations in the northern hemisphere, but with various tilt angles. From the Swarm spacecrafts with zonal separations of about 150 km, we conclude that larger zonal scale sizes of irregularities exist during the early evening hours (around 1900 LT).
Widespread flooding in June 2013 caused damage costs of €6 to 8 billion in Germany, and awoke many memories of the floods in August 2002, which resulted in total damage of €11.6 billion and hence was the most expensive natural hazard event in Germany up to now. The event of 2002 does, however, also mark a reorientation toward an integrated flood risk management system in Germany. Therefore, the flood of 2013 offered the opportunity to review how the measures that politics, administration, and civil society have implemented since 2002 helped to cope with the flood and what still needs to be done to achieve effective and more integrated flood risk management. The review highlights considerable improvements on many levels, in particular (1) an increased consideration of flood hazards in spatial planning and urban development, (2) comprehensive property-level mitigation and preparedness measures, (3) more effective flood warnings and improved coordination of disaster response, and (4) a more targeted maintenance of flood defense systems. In 2013, this led to more effective flood management and to a reduction of damage. Nevertheless, important aspects remain unclear and need to be clarified. This particularly holds for balanced and coordinated strategies for reducing and overcoming the impacts of flooding in large catchments, cross-border and interdisciplinary cooperation, the role of the general public in the different phases of flood risk management, as well as a transparent risk transfer system. Recurring flood events reveal that flood risk management is a continuous task. Hence, risk drivers, such as climate change, land-use changes, economic developments, or demographic change and the resultant risks must be investigated at regular intervals, and risk reduction strategies and processes must be reassessed as well as adapted and implemented in a dialogue with all stakeholders.
The hyperthermal events of the Cenozoic, including the Paleocene-Eocene Thermal Maximum, provide an opportunity to investigate the potential effects of climate warming on marine ecosystems. Here, we examine the shallow benthic marine communities preserved in the late Cretaceous to Eocene strata on the Gulf Coastal Plain (United States). In stark contrast to the ecological shifts following the end-Cretaceous mass extinction, our data show that the early Cenozoic hyperthermals did not have a long-term impact on the generic diversity nor composition of the Gulf Coastal Plain molluscan communities. We propose that these communities were resilient to climate change because molluscs are better adapted to high temperatures than other taxa, as demonstrated by their physiology and evolutionary history. In terms of resilience, these communities differ from other shallow-water carbonate ecosystems, such as reef communities, which record significant changes during the early Cenozoic hyperthermals. These data highlight the strikingly different responses of community types, i.e., the almost imperceptible response of molluscs versus the marked turnover of foraminifera and reef faunas. The impact on molluscan communities may have been low because detrimental conditions did not devastate the entire Gulf Coastal Plain, allowing molluscs to rapidly recolonise vacated areas once harsh environmental conditions ameliorated.
Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.
Many widely used observational data sets are comprised of several overlapping instrument records. While data inter-calibration techniques often yield continuous and reliable data for trend analysis, less attention is generally paid to maintaining higher-order statistics such as variance and autocorrelation. A growing body of work uses these metrics to quantify the stability or resilience of a system under study and potentially to anticipate an approaching critical transition in the system. Exploring the degree to which changes in resilience indicators such as the variance or autocorrelation can be attributed to non-stationary characteristics of the measurement process – rather than actual changes in the dynamical properties of the system – is important in this context. In this work we use both synthetic and empirical data to explore how changes in the noise structure of a data set are propagated into the commonly used resilience metrics lag-one autocorrelation and variance. We focus on examples from remotely sensed vegetation indicators such as vegetation optical depth and the normalized difference vegetation index from different satellite sources. We find that time series resulting from mixing signals from sensors with varied uncertainties and covering overlapping time spans can lead to biases in inferred resilience changes. These biases are typically more pronounced when resilience metrics are aggregated (for example, by land-cover type or region), whereas estimates for individual time series remain reliable at reasonable sensor signal-to-noise ratios. Our work provides guidelines for the treatment and aggregation of multi-instrument data in studies of critical transitions and resilience.
Regional snow-avalanche detection using object-based image analysis of near-infrared aerial imagery
(2017)
Snow avalanches are destructive mass movements in mountain regions that continue to claim lives and cause infrastructural damage and traffic detours. Given that avalanches often occur in remote and poorly accessible steep terrain, their detection and mapping is extensive and time consuming. Nonetheless, systematic avalanche detection over large areas could help to generate more complete and up-to-date inventories (cadastres) necessary for validating avalanche forecasting and hazard mapping. In this study, we focused on automatically detecting avalanches and classifying them into release zones, tracks, and run-out zones based on 0.25 m near-infrared (NIR) ADS80-SH92 aerial imagery using an object-based image analysis (OBIA) approach. Our algorithm takes into account the brightness, the normalised difference vegetation index (NDVI), the normalised difference water index (NDWI), and its standard deviation (SDNDWI) to distinguish avalanches from other land-surface elements. Using normalised parameters allows applying this method across large areas. We trained the method by analysing the properties of snow avalanches at three 4 km−2 areas near Davos, Switzerland. We compared the results with manually mapped avalanche polygons and obtained a user's accuracy of > 0.9 and a Cohen's kappa of 0.79–0.85. Testing the method for a larger area of 226.3 km−2, we estimated producer's and user's accuracies of 0.61 and 0.78, respectively, with a Cohen's kappa of 0.67. Detected avalanches that overlapped with reference data by > 80 % occurred randomly throughout the testing area, showing that our method avoids overfitting. Our method has potential for large-scale avalanche mapping, although further investigations into other regions are desirable to verify the robustness of our selected thresholds and the transferability of the method.
The simulation of broad-band (0.1 to 10 + Hz) ground-shaking over deep and spatially extended sedimentary basins at regional scales is challenging. We evaluate the ground-shaking of a potential M 6.5 earthquake in the southern Lower Rhine Embayment, one of the most important areas of earthquake recurrence north of the Alps, close to the city of Cologne in Germany. In a first step, information from geological investigations, seismic experiments and boreholes is combined for deriving a harmonized 3D velocity and attenuation model of the sedimentary layers. Three alternative approaches are then applied and compared to evaluate the impact of the sedimentary cover on ground-motion amplification. The first approach builds on existing response spectra ground-motion models whose amplification factors empirically take into account the influence of the sedimentary layers through a standard parameterization. In the second approach, site-specific 1D amplification functions are computed from the 3D basin model. Using a random vibration theory approach, we adjust the empirical response spectra predicted for soft rock conditions by local site amplification factors: amplifications and associated ground-motions are predicted both in the Fourier and in the response spectra domain. In the third approach, hybrid physics-based ground-motion simulations are used to predict time histories for soft rock conditions which are subsequently modified using the 1D site-specific amplification functions computed in method 2. For large distances and at short periods, the differences between the three approaches become less notable due to the significant attenuation of the sedimentary layers. At intermediate and long periods, generic empirical ground-motion models provide lower levels of amplification from sedimentary soils compared to methods taking into account site-specific 1D amplification functions. In the near-source region, hybrid physics-based ground-motions models illustrate the potentially large variability of ground-motion due to finite source effects.
Temporal variation of natural light sources such as airglow limits the ability of night light sensors to detect changes in small sources of artificial light (such as villages). This study presents a method for correcting for this effect globally, using the satellite radiance detected from regions without artificial light emissions. We developed a routine to define an approximate grid of locations worldwide that do not have regular light emission. We apply this method with a 5 degree equally spaced global grid (total of 2016 individual locations), using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB). This code could easily be adapted for other future global sensors. The correction reduces the standard deviation of data in the Earth Observation Group monthly DNB composites by almost a factor of two. The code and datasets presented here are available under an open license by GFZ Data Services, and are implemented in the Radiance Light Trends web application.
Classification of clouds, cirrus, snow, shadows and clear sky areas is a crucial step in the pre-processing of optical remote sensing images and is a valuable input for their atmospheric correction. The Multi-Spectral Imager on board the Sentinel-2's of the Copernicus program offers optimized bands for this task and delivers unprecedented amounts of data regarding spatial sampling, global coverage, spectral coverage, and repetition rate. Efficient algorithms are needed to process, or possibly reprocess, those big amounts of data. Techniques based on top-of-atmosphere reflectance spectra for single-pixels without exploitation of external data or spatial context offer the largest potential for parallel data processing and highly optimized processing throughput. Such algorithms can be seen as a baseline for possible trade-offs in processing performance when the application of more sophisticated methods is discussed. We present several ready-to-use classification algorithms which are all based on a publicly available database of manually classified Sentinel-2A images. These algorithms are based on commonly used and newly developed machine learning techniques which drastically reduce the amount of time needed to update the algorithms when new images are added to the database. Several ready-to-use decision trees are presented which allow to correctly label about 91% of the spectra within a validation dataset. While decision trees are simple to implement and easy to understand, they offer only limited classification skill. It improves to 98% when the presented algorithm based on the classical Bayesian method is applied. This method has only recently been used for this task and shows excellent performance concerning classification skill and processing performance. A comparison of the presented algorithms with other commonly used techniques such as random forests, stochastic gradient descent, or support vector machines is also given. Especially random forests and support vector machines show similar classification skill as the classical Bayesian method.
RainNet v1.0
(2020)
In this study, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting. Its design was inspired by the U-Net and SegNet families of deep learning models, which were originally designed for binary segmentation tasks. RainNet was trained to predict continuous precipitation intensities at a lead time of 5min, using several years of quality-controlled weather radar composites provided by the German Weather Service (DWD). That data set covers Germany with a spatial domain of 900km × 900km and has a resolution of 1km in space and 5min in time. Independent verification experiments were carried out on 11 summer precipitation events from 2016 to 2017. In order to achieve a lead time of 1h, a recursive approach was implemented by using RainNet predictions at 5min lead times as model inputs for longer lead times. In the verification experiments, trivial Eulerian persistence and a conventional model based on optical flow served as benchmarks. The latter is available in the rainymotion library and had previously been shown to outperform DWD's operational nowcasting model for the same set of verification events.
RainNet significantly outperforms the benchmark models at all lead times up to 60min for the routine verification metrics mean absolute error (MAE) and the critical success index (CSI) at intensity thresholds of 0.125, 1, and 5mm h⁻¹. However, rainymotion turned out to be superior in predicting the exceedance of higher intensity thresholds (here 10 and 15mm h⁻¹). The limited ability of RainNet to predict heavy rainfall intensities is an undesirable property which we attribute to a high level of spatial smoothing introduced by the model. At a lead time of 5min, an analysis of power spectral density confirmed a significant loss of spectral power at length scales of 16km and below. Obviously, RainNet had learned an optimal level of smoothing to produce a nowcast at 5min lead time. In that sense, the loss of spectral power at small scales is informative, too, as it reflects the limits of predictability as a function of spatial scale. Beyond the lead time of 5min, however, the increasing level of smoothing is a mere artifact – an analogue to numerical diffusion – that is not a property of RainNet itself but of its recursive application. In the context of early warning, the smoothing is particularly unfavorable since pronounced features of intense precipitation tend to get lost over longer lead times. Hence, we propose several options to address this issue in prospective research, including an adjustment of the loss function for model training, model training for longer lead times, and the prediction of threshold exceedance in terms of a binary segmentation task. Furthermore, we suggest additional input data that could help to better identify situations with imminent precipitation dynamics. The model code, pretrained weights, and training data are provided in open repositories as an input for such future studies.
Quantifying rock weakening due to decreasing calcite mineral content by numerical simulations
(2018)
The quantification of changes in geomechanical properties due to chemical reactions is of paramount importance for geological subsurface utilisation, since mineral dissolution generally reduces rock stiffness. In the present study, the effective elastic moduli of two digital rock samples, the Fontainebleau and Bentheim sandstones, are numerically determined based on micro-CT images. Reduction in rock stiffness due to the dissolution of 10% calcite cement by volume out of the pore network is quantified for three synthetic spatial calcite distributions (coating, partial filling and random) using representative sub-cubes derived from the digital rock samples. Due to the reduced calcite content, bulk and shear moduli decrease by 34% and 38% in maximum, respectively. Total porosity is clearly the dominant parameter, while spatial calcite distribution has a minor impact, except for a randomly chosen cement distribution within the pore network. Moreover, applying an initial stiffness reduced by 47% for the calcite cement results only in a slightly weaker mechanical behaviour. Using the quantitative approach introduced here substantially improves the accuracy of predictions in elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in porosity and mineral distribution.
Climatic change alters the frequency and intensity of natural hazards. In order to assess potential future changes in flood seasonality in the Rhine River Basin, we analyse changes in streamflow, snowmelt, precipitation, and evapotranspiration at 1.5, 2.0 and 3.0 ◦C global warming levels. The mesoscale Hydrological Model (mHM) forced with an ensemble of climate projection scenarios (five general circulation models under three representative concentration pathways) is used to simulate the present and future climate conditions of both, pluvial and nival hydrological regimes. Our results indicate that the interplay between changes in snowmelt- and rainfall-driven runoff is crucial to understand changes in streamflow maxima in the Rhine River. Climate projections suggest that future changes in flood characteristics in the entire Rhine River are controlled by both, more intense precipitation events and diminishing snow packs. The nature of this interplay defines the type of change in runoff peaks. On the sub-basin level (the Moselle River), more intense rainfall during winter is mostly counterbalanced by reduced snowmelt contribution to the streamflow. In the High Rhine (gauge at Basel), the strongest increases in streamflow maxima show up during winter, when strong increases in liquid precipitation intensity encounter almost unchanged snowmelt-driven runoff. The analysis of snowmelt events suggests that at no point in time during the snowmelt season, a warming climate results in an increase in the risk of snowmelt-driven flooding. We do not find indications of a transient merging of pluvial and nival floods due to climate warming.
Initiation of subduction following the impingement of a hot buoyant mantle plume is one of the few scenarios that allow breaking the lithosphere and recycling a stagnant lid without requiring any preexisting weak zones. Here, we investigate factors controlling the number and shape of retreating subducting slabs formed by plume-lithosphere interaction. Using 3-D thermomechanical models we show that the deformation regime, which defines formation of single-slab or multi-slab subduction, depends on several parameters such as age of oceanic lithosphere, thickness of the crust and large-scale lithospheric extension rate. Our model results indicate that on present-day Earth multi-slab plume-induced subduction is initiated only if the oceanic lithosphere is relatively young (<30-40 Myr, but >10 Myr), and the crust has a typical thickness of 8 km. In turn, development of single-slab subduction is facilitated by older lithosphere and pre-imposed extensional stresses. In early Earth, plume-lithosphere interaction could have led to formation of either episodic short-lived circular subduction when the oceanic lithosphere was young or to multi-slab subduction when the lithosphere was old.