ALBERT

Description: Core and outcrop analysis from Lena mouth deposits have been used to reconstruct the Late Quaternary sedimentation history of the Lena Delta. Sediment properties (heavy mineral composition, grain size characteristics, organic carbon content) and age determinations (14C AMS and IR-OSL) are applied to discriminate the main sedimentary units of the three major geomorphic terraces, which form the delta. The development of the terraces is controlled by complex interactions among the following four factors: (1) Channel migration. According to the distribution of 14C and IR-OSL age determinations of Lena mouth sediments, the major river runoff direction shifted from the west during marine isotope stages 5-3 (third terrace deposits) towards the northwest during marine isotope stage 2 and transition to stage 1 (second terrace), to the northeast and east during the Holocene (first terrace deposits). (2) Eustasy. Sea level rise from Last Glacial lowstand to the modern sea level position, reached at 6-5 ka BP, resulted in back-filling and flooding of the palaeovalleys. (3) Neotectonics. The extension of the Arctic Mid-Ocean Ridge into the Laptev Sea shelf acted as a halfgraben, showing dilatation movements with different subsidence rates. From the continent side, differential neotectonics with uplift and transpression in the Siberian coast ridges are active. Both likely have influenced river behavior by providing sites for preservation, with uplift, in particular, allowing accumulation of deposits in the second terrace in the western sector. The actual delta setting comprises only the eastern sector of the Lena Delta. (4) Peat formation. Polygenetic formation of ice-rich peaty sand (''Ice Complex'') was most extensive (7-11 m in thickness) in the southern part of the delta area between 43 and 14 ka BP (third terrace deposits). In recent times, alluvial peat (5-6 m in thickness) is accumulated on top of the deltaic sequences in the eastern sector (first terrace).

Description: To project the future development of the soil organic carbon (SOC) storage in permafrost environments, the spatial and vertical distribution of key soil properties and their landscape controls needs to be understood. This article reports findings from the Arctic Lena River Delta where we sampled 50 soil pedons. These were classified according to the U.S.D.A. Soil Taxonomy and fall mostly into the Gelisol soil order used for permafrost-affected soils. Soil profiles have been sampled for the active layer (mean depth 58 ± 10 cm) and the upper permafrost to one meter depth. We analyze SOC stocks and key soil properties, i.e. C%, N%, C/N, bulk density, visible ice and water content. These are compared for different landscape groupings of pedons according to geomorphology, soil and land cover and for different vertical depth increments. High vertical resolution plots are used to understand soil development. These show that SOC storage can be highly variable with depth. We recommend the treatment of permafrost-affected soils according to subdivisions into: the surface organic layer, mineral subsoil in the active layer, organic enriched cryoturbated or buried horizons and the mineral subsoil in the permafrost. The major geomorphological units of a subregion of the Lena River Delta were mapped with a land form classification using a data-fusion approach of optical satellite imagery and digital elevation data to upscale SOC storage. Landscape mean SOC storage is estimated to 19.2 ± 2.0 kg C/m**2. Our results show that the geomorphological setting explains more soil variability than soil taxonomy classes or vegetation cover. The soils from the oldest, Pleistocene aged, unit of the delta store the highest amount of SOC per m2 followed by the Holocene river terrace. The Pleistocene terrace affected by thermal-degradation, the recent floodplain and bare alluvial sediments store considerably less SOC in descending order.

Description: This study presents evidence that Quaternary frontal arc calc-alkaline lavas from Central Mexican Volcanic Belt (CMVB) contain contributions from partial melts of the subducting garnet-bearing eclogitic oceanic crust and sediment, based on chemical and Hf-Nd isotope data. The CMVB includes both calc-alkaline lavas with arc-type trace element patterns such as aqueous fluid mobile element enrichments and high field strength element depletions; and "high-Nb" alkaline lavas with trace element patterns similar to ocean island basalts. The two types of lavas are closely related geographically and temporally. Distinct from the high-Nb lavas, the calc-alkaline lavas show trends toward higher 176Hf/177Hf and 143Nd/144Nd ratios coupled with lower Lu/Hf. The high Hf-Nd isotope ratios fingerprint contributions of subducted basaltic ocean crust, while the correlation with low Lu/Hf indicates melting in the presence of residual garnet, which reflects conversion of the subducted oceanic crust to eclogite. Isotopic and chemical mass balance considerations indicate that the slab melts are ~ 80% basaltic oceanic crust and ~ 20% subducted sediment. The calc-alkaline lavas have higher SiO2 at a given Mg# compared to the high-Nb alkaline lavas, also reflecting melt contributions from the subducted slab. A survey of global arc lavas shows that calc-alkaline lavas with low Lu/Hf ratios, reflecting melting in the presence of residual garnet and preferential mobilization of Hf over Lu from the subducted slab, are generally associated with hot slab conditions. These include arcs where young (〈 30 Ma old) ocean crust is subducted (e.g. Mexican Volcanic Belt, Cascades, Austral Andes, Luzon, Setouchi), where slab tearing occurred and hot asthenospheric mantle could upwell through the slab window (e.g., western Aleutians, Sunda, southern Scotia), and where oblique or slow subduction leads to higher slab temperatures (e.g. Lesser Antilles, western Aleutians). In some of these hot slab arcs, where low Lu/Hf ratios are coupled with high Nd-Hf isotope ratios, slab melt contributions are dominated by partial melts from the subducted oceanic basalt (e.g., Mexican Volcanic Belt, Aleutians and Cascades). In other hot slab arcs, low Lu/Hf ratios are coupled with low Nd-Hf isotope ratios, reflecting slab contributions dominated by sediment melts (e.g. Setouchi, Lesser Antilles, Luzon, Sunda, and southern Scotia). Arcs associated with colder subducted oceanic crust (e.g. Izu-Bonin-Marianas, Tonga-Kermadec, central and northern Scotia) erupt lavas with high Lu/Hf along with high Hf-Nd isotope ratios, similar to mid-ocean ridge basalts, thus they lack the signature of residual garnet as well as significant slab melt input.

Description: The Lena River Delta, which is the largest delta in the Arctic, extends over an area of 32 000 km**2 and likely holds more than half of the entire soil organic carbon (SOC) mass stored in the seven major deltas in the northern permafrost regions. The geomorphic units of the Lena River Delta which were formed by true deltaic sedimentation processes are a Holocene river terrace and the active floodplains. Their mean SOC stocks for the upper 1 m of soils were estimated at 29 kg/m**2 ± 10 kg/m**2 and at 14 kg/m**2 ± 7 kg/m**2, respectively. For the depth of 1 m, the total SOC pool of the Holocene river terrace was estimated at 121 Tg ± 43 Tg, and the SOC pool of the active floodplains was estimated at 120 Tg ± 66 Tg. The mass of SOC stored within the observed seasonally thawed active layer was estimated at about 127 Tg assuming an average maximum active layer depth of 50 cm. The SOC mass which is stored in the perennially frozen ground at the increment 50-100 cm soil depth, which is currently excluded from intense biogeochemical exchange with the atmosphere, was estimated at 113 Tg. The mean nitrogen (N) stocks for the upper 1 m of soils were estimated at 1.2 kg/m**2 ± 0.4 kg/m**2 for the Holocene river terrace and at 0.9 kg/m**2 ± 0.4 kg/m**2 for the active floodplain levels, respectively. For the depth of 1 m, the total N pool of the river terrace was estimated at 4.8 Tg ± 1.5 Tg, and the total N pool of the floodplains was estimated at 7.7 Tg ± 3.6 Tg. Considering the projections for deepening of the seasonally thawed active layer up to 120 cm in the Lena River Delta region within the 21st century, these large carbon and nitrogen stocks could become increasingly available for decomposition and mineralization processes.

Description: Ice rich Yedoma-dominated landscapes store considerable amounts of organic carbon (C) and nitrogen (N) and are vulnerable to degradation under climate warming. We investigate the C and N pools in two thermokarst-affected Yedoma landscapes - on Sobo-Sise Island and on Bykovsky Peninsula in the North of East Siberia. Soil cores up to three meters depth were collected along geomorphic gradients and analysed for organic C and N contents. A high vertical sampling density in the profiles allowed the calculation of C and N stocks for short soil column intervals and enhanced understanding of within-core parameter variability. Profile-level C and N stocks were scaled to the landscape level based on landform classifications from five-meter resolution, multispectral RapidEye satellite imagery. Mean landscape C and N storage in the first meter of soil for Sobo-Sise Island is estimated to be 20.2 kg C/m**-2 and 1.8 kg N/m**-2 and for Bykovsky Peninsula 25.9 kg C/m**-2 and 2.2 kg N/m**-2. Radiocarbon dating demonstrates the Holocene age of thermokarst basin deposits but also suggests the presence of thick Holocene aged cover layers which can reach up to two meters on top of intact Yedoma landforms. Reconstructed sedimentation rates of 0.10 mm/yr - 0.57 mm/yr suggest sustained mineral soil accumulation across all investigated landforms. Both Yedoma and thermokarst landforms are characterized by limited accumulation of organic soil layers (peat). We further estimate that an active layer deepening by about 100 cm will increase organic C availability in a seasonally thawed state in the two study areas by ~5.8 Tg (13.2 kg C/m**-2). Our study demonstrates the importance of increasing the number of C and N storage inventories in ice-rich Yedoma and thermokarst environments in order to account for high variability of permafrost and thermokarst environments in pan-permafrost soil C and N pool estimates.

Description: This data set describes the soil core and sample characteristics from the Ikpikpuk and Fish Creek river delta on the Arctic Coastal Plain in northern Alaska. The collection of the permafrost soil cores and the analysis of the samples are described in Fuchs et al. (2018). Sedimentary and geochemical characteristics of two small permafrost-dominated Arctic river deltas in northern Alaska. This data compilation consists of two data set. The first data set describes the properties of the collected permafrost soil cores from the Ikpikpuk river (IKP) and Fish Creek river (FCR) delta. This includes the coordinates of the nine coring locations, the field measurements of the active- and organic layer thickness at the coring locations, and the length of the collected permafrost core. In addition, soil organic carbon and soil nitrogen stocks and densities derived from the laboratory analyses for the reference depths 0-30 cm, 0-100 cm, 0-150 cm and 0-200 cm are presented in kg C m-2 and in kg C m-3. The second data set provides the raw laboratory data for all the samples of the nine collected permafrost cores in the Ikpikpuk and Fish Creek River Delta. All laboratory analyzes were carried out at the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam. The third data set presents the results from the radiocarbon dating of chosen samples from five different permafrost cores. This includes the AMS radiocarbon date and the calibrated age of a sample. In addition, the sediment and organic carbon accumulation rates for the dated samples are included. This data set allows to calculate the total carbon and nitrogen storage in two small Arctic river deltas (IKP and FCR) for the first two meter of soil and enlarges the available permafrost cores for Arctic river delta deposits.

Description: In 1974 the determination of zooplankton was added to the Helgoland Roads long-term data series. Zooplankton was sampled with an oblique haul using a 150µm hand net at the "Kabeltonne" site (54°11.3′N, 7°54.0′E). Live samples were counted with a stereomicroscope until 1981, since then samples are preserved in 4% formaldehyde (buffered with Borax) to allow for storage and later examination. Samples are counted depending on the density either as whole or subsamples. However, at least 60 individuals of each key species are counted per subsample to ensure counting of a representative part of the sample. This data collection includes mesozooplankton abundances since 1974 until present. Data of meso- and macrozooplankton abundances collected with a 500µm Calcofi net since 1975 are available in Renz et al. (2018).

Description: This is a compilation of all Concordia station datasets that were/are published in the frame of BSRN. The collection will be updated regularly with recent data. The data are subject to the data release guidelines of BSRN (https://bsrn.awi.de/data/conditions-of-data-release/).

Description: The data set represents an extensive collection of the sediment non-clay and clay mineral compositions, based on quantitative X-ray diffraction (qXRD) data. Mineral compositions are included from 90 bedrock or large ice-rafted clasts from around the Western North Atlantic. Sediment samples on the 〈 2mm sediment fraction were obtained using the whole pattern approach to mineral identification from the same area that include cores and sites collected on CCS Hudson and Marion Dufrense expeditons. Several cores include one or more detrital carbonate Hudson Strait Heinrich events.

Description: The scientific program of the Meteor M184 expedition was dedicated to studies on the intensity of water mass transformation, a synoptic view of the hydrography in the Labrador Sea and the Irminger Basin, as well as submesoscale resolving surveys of fronts. Measurements of the vertical structure of temperature, salinity, density, oxygen, optical properties, and the flow along selected sections have been surveyed during the M184 expedition. Close to the surface, permanent registrations are carried out with the thermosalinograph (temperature, salinity), meteorological data are continuously collected, flow measurements up to 1000 m depth are performed with the ships installed ADCP and surface currents by a X-band marine radar. Detailed surveys on submesoscale fronts were done with autonomous underwater gliders and ship mounted gear. Furthermore, 40 Hereon drifters were deployed to sample the surface flow. One drifter did not collect any data.

Description: Most of the world's permafrost is located in the Arctic, where its frozen organic carbon con-tent makes it a potentially important influence on the global climate system. The Arctic climate appears to be changing more rapidly than the lower latitudes, but observational data density in the region is low. Permafrost thaw and carbon release into the atmosphere is a positive feed-back mechanism that has the potential for climate warming. It is therefore particularly im-portant to understand the links between the energy balance, which can vary rapidly over hour-ly to annual time scales, and permafrost condition, which changes slowly on decadal to cen-tennial timescales. This requires long-term observational data such as that available from the Samoylov research site in northern Siberia, where meteorological parameters, energy balance, and subsurface observations have been recorded since 1998. This paper presents the temporal data set produced between 2002 and 2017, explaining the instrumentation, calibration, pro-cessing and data quality control. Additional data include a high-resolution digital terrain mod-el (DTM) obtained from terrestrial LiDAR laser scanning. Since the data provide observations of temporally variable parameters that influence energy fluxes between permafrost, active lay-er soils, and the atmosphere (such as snow depth and soil moisture content), they are suitable for calibrating and quantifying the dynamics of permafrost as a component in earth system models. The data also include soil properties beneath different microtopographic features (a polygon center, a rim, a slope, and a trough), yielding much-needed information on landscape heterogeneity for use in land surface modeling. For the record from 1998 to 2017, the average mean annual air temperature was -12.3°C, with mean monthly temperature of the warmest month (July) recorded as 9.5°C and for the coldest month (February) -32.7°C. The average annual rainfall was 169mm. The depth of zero annual amplitude niveau is at 20.8m, and has warmed from -9.1°C in 2006 to -7.7°C in 2017.

Description: The data presented herein originates from a mesocosm study conducted as part of the EU H2020 OceanNETs project, aimed at investigating the ecological ramifications of ocean alkalinity enhancement. Nine mesocosms were deployed in Taliarte Harbour, Gran Canaria, Spain, and systematically sampled using integrated water samplers over the period spanning from September 10th to October 25th, 2021. Alkalinity was employed in a gradient design, ranging from ambient (0 µeq kg-1 added alkalinity, OAE0) to elevated levels of 2400 µeq kg-1 additional alkalinity (OAE2400) in increments of 300 µeq kg-1. The dataset encompasses a spectrum of sediment trap particle flux data, water column biogeochemistry variables, including inorganic nutrients, carbonate chemistry parameters, and particulate matter, alongside chlorophyll a concentrations. The study and data set offer insights into impacts of alkalinity enhancement on marine ecosystems and their associated biogeochemistry.

Description: Ground-based electromagnetic induction (EM) measurements of land-fast sea ice and sub-ice platelet layer (SIPL) thickness distributions were carried out in McMurdo Sound, Antarctica in late spring (November 1-19) of 2018. Repeated west to east EM transects were carried out across McMurdo Sound along latitude 77.767°S. The EM data was acquired using a frequency-domain Geonics Ltd EM31-MK2 instrument mounted on a sledge and towed by skidoo. The thicknesses of consolidated ice (sea ice plus the snow layer) and the sub-ice platelet layer were simultaneously retrieved from the EM31 measured response using forward modelling and inversion methods of Irvin (2018). Variability in EM thicknesses detected significant growth of sub-ice platelet layer over the 18-day survey period (Brett et al., 2024).

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'Uz_profile_classic.dat' shows the streamwise velocity profile corresponding to the optimal classic perturbation. This file includes two columns: the first column 'r' indicates radial coordinate; the second column 'uz' indicates streamwise velocity.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'Uz_profile_helical.dat' shows the streamwise velocity profile corresponding to the optimal helical perturbation. This file includes two columns: the first column 'r' indicates radial coordinate; the second column 'uz' indicates streamwise velocity.

Description: Multibeam bathymetry raw data was recorded in the North Atlantic during cruise M80/3 that took place between 2009-12-29 and 2010-02-01. The data was collected using the ship's own Kongsberg EM 120. This data is part of the DAM (German Marine Research Alliance) underway research data project. Sound velocity profiles (SVP) were applied on the data for calibration. SVP data are part of this dataset publication.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'Fig2a_time_TG_all.dat' shows the maximum energy amplification over all perturbations at each time instant. This file includes three columns: the first column indicates dimensionless time; the second column indicates the time normalized by the pulsation period; the third column indicates the energy amplification at a time instant (first column).

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'TG_Re_Wo25.dat' shows the dependence of the maximum energy amplification on the Reynolds numbers at Womersley number of 25 and pulsation amplitude of 1. This file includes two columns: the first column indicates the Reynolds number; the second column indicates the maximum energy amplifiation.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'TG_Re_Wo15.dat' shows the dependence of the maximum energy amplification on the Reynolds numbers at Womersley number of 15 and pulsation amplitude of 1. This file includes two columns: the first column indicates the Reynolds number; the second column indicates the maximum energy amplifiation.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'wavenumber_Re_Wo15.dat' shows the dependence of the optimal wavenumber on the Reynolds numbers at Womersley number of 15 and pulsation amplitude of 1. This file includes three columns: the first column indicates the Reynolds number; the second column indicates the optimal axial wavenumber; the third column indicates the optimal azimuthal wavenumber.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'wavenumber_Re_Wo25.dat' shows the dependence of the optimal wavenumber on the Reynolds numbers at Womersley number of 25 and pulsation amplitude of 1. This file includes three columns: the first column indicates the Reynolds number; the second column indicates the optimal axial wavenumber; the third column indicates the optimal azimuthal wavenumber.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 't0_tf_A.dat' shows the variation of optimal time (corresponding to the maximum energy amplification) with the pulsation amplitude for the Reynolds number of 2000 and the Womersley number of 15. This file includes four columns: the first column indicates the pulsation amplitude; the second column indicates the initial time of perturbations normalized by pulsation period; the third column indicates the evolution time of the perturbation normalized by period; the fourth column indicates the final time normalized by the period.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'TG_A_Wo10.dat' shows the dependence of the maximum energy amplification on the pulsation amplitude for the Reynolds number of 2000 and the Womersley number of 10. This file includes two columns: the first column indicates the pulsation amplitude; the second column indicates the maximum energy amplification.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'wavenumber_A_Wo10.dat' shows the dependence of the optimal wavenumber on the pulsation amplitude. This file includes three columns: the first column indicates the pulsation amplitude; the second column indicates the optimal axial wavenumber; the third column indicates the optimal azimuthal wavenumber (corresponding to the maximum energy amplitude).

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'wavenumber_A_Wo15.dat' shows the dependence of the optimal wavenumber on the pulsation amplitude. This file includes three columns: the first column indicates the pulsation amplitude; the second column indicates the optimal axial wavenumber; the third column indicates the optimal azimuthal wavenumber (corresponding to the maximum energy amplitude).

Description: This is the measurement data from chemical analysis of archaeological Neolithic pottery using portable X-ray fluorescence analysis (p-XRF). The pottery came from the sites Wanna 1588, 1591, 1592, 1594 and 1603 (district of Cuxhaven, Lower Saxony, Germany) and belongs to the cultural group of the Funnel Beaker culture. The measurements are part of the research projects "Preserved in the bog - relics of prehistoric settlement landscapes in the Elbe-Weser triangle" funded by Niedersachsen Vorab and "Pottery traditions as a mirror of social structures of the 5th and 4th millennium BC in northern Central Europe" funded by the German Research Foundation (DFG project number 438036891). A handheld Niton XL3t XRF-Analyzer of the company analyticon was used. The device was held stationary in a stand. The measurements were taken on the edge of each sherd that have been previously cleaned and smoothed using abrasive paper. Each sherd was analysed in three different areas of the edge using the mode Mining and a small beam of 3 mm. The data consist of the average values of these measurements for each element. Each spot was analysed with four different filters. The total measuring time was 125 seconds.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'OptimalPerturbation_time_energy_classic.dat' shows the time series of the energy of the optimal classic perturbation. This file includes four columns: the first column indicates dimensionless time; the second column indicates the time normalized by period; the third column indicates the energy of the perturbation; the fourth column indicates the energy of the perturbation normalized by the energy at the initial perturbation time.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'OptimalPerturbation_time_StreamwiseVel_helical.dat' shows the streamwise velocity of the optimal helical perturbation in the streamwise-radial cross-section. This file includes three columns: the first two column 'x' and 'y' indicate Cartesian coordinates in the streamwise-radial cross-section; the third column 'uz' indicates streamwise velocity.

Description: Plant protection products in the environment are partly responsible for the progressive loss of biodiversity. The mostly insufficient ecological status of surface waters is often explained by habitat degradation and excessive nutrient input. But what role do plant protection products play in this context? The Kleingewässermonitoring (KgM) project provides a worldwide unique quantitative assessment of the impact of pesticides from diffuse agricultural sources on small and medium-sized streams. The dataset comprises 124 monitoring stream sections all over Germany covering a wide pollution gradient where consistent measurements were carried out in 2018 and 2019 during the major pesticide application period from April to July. These measurements include event-driven sampling to record surface rainfall-induced short-term peak concentrations in addition to regular grab sampling of pesticides and a wide range of other pollutants resulting in more than 1,000 water samples. All further relevant anthropogenic and environmental parameters reigning ecological stream quality were recorded comprehensively (morphological and stream bed structure, temperature, flow velocity, dissolved oxygen, pH, catchment land use, stream profile). The dataset also contains effect monitoring data featuring sampled invertebrate communities and bioassay analyses of water samples. The data enables an assessment of pesticide exposure and related effects as well as the analysis of complex causal relationships in streams.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'OptimalPerturbation_time_VortZ_classic.dat' shows the streamwise vorticity of the optimal classic perturbation in the radial-radial cross-section. This file includes three columns: the first two column 'x' and 'y' indicate Cartesian coordinates in the radial-radial cross-section; the third column 'VortZ' indicates streamwise vorticity.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'OptimalPerturbation_time_VortZ_helical.dat' shows the streamwise vorticity of the optimal helical perturbation in the radial-radial cross-section. This file includes three columns: the first two column 'x' and 'y' indicate Cartesian coordinates in the radial-radial cross-section; the third column 'VortZ' indicates streamwise vorticity.

Description: Snow-cores KF13, KF14, KF15, KF16, KF17, KF18, and KF20 continuously analyzed by Continuous Flow Analysis between April and October 2019 at the Alfred-Wegener-Institut Helmholtz-Zentrum für Polar-und Meeresforschung, in Bremerhaven, Germany. All cores were sampled along the trench T15-1 in 2014/15, correspond to depths 240-340cm and are 5 meters spaced (relative distance to the starting coordinate). Isotopic measurements were realized by CRDS (Cavity-Ring-Down Spectroscopy, L-2140-i, Picarro Inc.).

Description: Discrete samples at 22mm depth-resolution for snow-cores KF13, KF14, KF15, KF16, and 33mm depth-resolution for snow-core KF20, analyzed in 2019 at the Alfred-Wegener-Institut Helmholtz-Zentrum für Polar-und Meeresforschung, in Bremerhaven, Germany. All cores were sampled along the trench T15-1 in 2014/15, correspond to depths 240-340cm and are 5 meters spaced (relative distance to the starting coordinate). Isotopic measurements realized by CRDS (Cavity-Ring-Down Spectroscopy, L-2120-i and L-2140-i, Picarro Inc.).

Description: During RV MARIA S. MERIAN cruise MSM85 in the subpolar North Atlantic and the Greenland Sea (23 July - 13 August, 2019) conductivity, temperature, and depth (CTD) measurements were made using a SeaBird 9+ CTD equipped with sensors for temperature, conductivity, and oxygen, as well as a Seapoint turbidity sensor and a WET labs fluorometer. A total number of 160 CTD casts were carried out, while crossing the East Greenland Shelf and the East Greenland Current. The stations were organized into eight sections, which covered the Irminger, Iceland and Greenland Sea as well as the Denmark Strait. Three additional stations were made across the entrance of the Greenlandic fjord Scoresby Sound (Kangertittivaq).

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'time_TG_all.dat' shows the maximum energy amplification over all modes at each time instant. This file includes three columns: the first column indicates dimensionless time; the second column indicates the time normalized by the pulsation period; the third column indicates the energy amplification at a time instant (first column).

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'TG_A_Wo15.dat' shows the dependence of the maximum energy amplification on the pulsation amplitude for the Reynolds number of 2000 and the Womersley number of 15. This file includes two columns: the first column indicates the pulsation amplitude; the second column indicates the maximum energy amplification.

Description: The data are obtained via an in-house Matlab script (developed by Dr. Baofang Song) to compute the non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows. In this study, a Newtonian fluid driven by pulsatile and oscillatory flow rate flows in a straight pipe. In pulsatile flow, there are three governing parameters: steady Reynolds number (defined by the steady flow component), pulsation amplitude (ratio of oscillatory and steady flow component) and Womersley number (dimensionless pulsation and oscillation frequency). In oscillatory flow, due to vanishment of steady flow component, oscillatory Reynolds number (defined by the oscillation flow component) and Womersley number. The Reynolds number defined by the thickness of Stokes layer is alternatively used for the oscillatory Reynolds number. The study was carried out in a manner that one governing parameter varies while other governing parameters are fixed. The data file 'time_TG_A2.4.dat' shows the time series of the maximum energy amplification for the Reynolds number of 2000, the amplitude of 2.4 and the Womersley number of 15. This file includes three columns: the first column indicates the time; the second column indicates the time normalized by the pulsation period; the third column indicates maximum energy amplification.