cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.889727
title: Lake Ice Classification from Sentinel-1A 2015 - 2018

description: In the ESA DUE GlobPermafrost project lake ice classifications were produced to distinguish grounded ice and floating ice in lakes in Barrow (Arctic Alaska, US), Teshekpuk (Arctic Alaska, US), Mackenzie Delta (Beaufort Sea Region, CA), Kytalyk (Central Yakutia, RU), Lena Delta (Laptev and East Siberian Sea Region, RU) and Yamal (Western Siberia, RU).Classifications are based on Sentinel-1A synthetic aperture radar time-series with a resolution between 18 m and 26 m. Imagery provides a weekly to monthly resolution throughout April and May for the years 2015 to 2017. Three versions of the product are provided using three different algorithms: 1) image thresholding (THRESH), 2) unsupervised image segmentation using K-means classification (KMEANS), and 3) unsupervised image segmentation using the Iterative Region Growing with Semantics (IRGSEM) algorithm. All versions contain two classes: grounded ice (CLASS 1) and floating ice (CLASS 2). All data are provided in geotiff format.More information about image processing and classification can be found in the product guide.
description: This dataset will be updated in 2018, further data will be added. Update on 2019-01-28: The lake ice classification product was updated with additional datasets. The product has now more time steps including the year 2018. Also, two new sites were added, i.e. C12-1 Central Seward Peninsula and C12-2 Cape Espenberg Lowland.
DOI: 10.1594/pangaea.665592
title: Oceanography at CTD/bottle station IFREMER_2432
DOI: 10.1594/pangaea.735833
title: Meteorological synoptical observations from station Lindenberg (1996-10)
DOI: 10.1594/pangaea.693699
title: Yearly production of marine products and its process lines in Taltal, Chile, 1998
DOI: 10.1594/pangaea.819709
title: (Table 3) Quart/opal-CT ratios and quartz crystallinity for porcellanite-chert beds of DSDP Leg 62 Holes

description: Empty cells mean no data.
DOI: 10.1594/pangaea.819170
title: (Table 1) Stratigraphy, composition, and isotopes at DSDP Leg 63 Holes carbonates

description: Sediment depth is given in mbsf. #0 = indicates either no dolomite or calcite or only minor calcite present. Empty cells = no data available. # in d13C and d18O values indicates samples in which calcite was removed by repeated treatment with 0.1M acetic acid before measurement of isotopic composition. The isotopic values listed, therefore, refer only to the dolomite in the sample.
DOI: 10.1594/pangaea.898816
title: COAWST model output for 10 typical, maximum and minimum representative years for Madeira and Porto Santo Islands wind studies

description: COAWST model output for 10 typical, maximum and minimum representative years for Madeira and Porto Santo Islands wind studies. Variables included at @ 100m are wind velocity, wind direction, Weibull shape and form. This data represents the long-term, maximum and minimum climatology through a single year, constructed from a long-term period of 10 years measured data. Each climatology has twelve individual monthly simulations. The data has 1 km resolution, provided from COAWST. A coupled model with Weather Research and Forecasting (WRF), Regional Ocean Modelling System (ROMS) and WaveWatch III (WW3). Data in netcdf4 format. Note: Data visualization available at: https://oom.arditi.pt/index.php?page=produtos
DOI: 10.1594/pangaea.692354
title: Concentrations of chlorophyll-alpha in sea water from the euphotic zone at Station SEPT-94-GN3619940280300320 in the Aegean Sea

description: Samples from 2 l of sea water were filtered through polycarbonate Millipore. The filters were kept deep frozen and analyzed according to Holm-Hansen et al. (Holm-Hansen, O., Lorenzen, C.J., Holmes, R.W., Strickland, J.D.H. 1965. Fluorometric determination of chlorophyll. Journal du Conseil Permanent International Pour l'Exploration de la Mer 30, 3-15).
DOI: 10.1594/pangaea.757685
title: Concentrations of dissolved and particulate heavy metals in waters above the northwestern slope of the Paramushir Island (Sea of Okhotsk)

description: Distributions of Mn, Fe, Cu, Cd, Cr, Co and Ni in sea water are investigated (42 samples, dissolved and particulate forms) in the vicinity of the underwater gas vent field on the northwestern slope of the Paramushir Island. While regular background distributions of the elements occur in the shore zone, there is a column of elevated concentrations of particulate matter, particulate Mn, and dissolved Mn, Fe, Cu, Cd, Cr, Co and Ni that coincides with location of the gas plume. This column can be traced as high as 780 m above the bottom. High metal concentrations in water of the plume are attributable to physico-chemical concentration at the phase interface; the source of elevated mineral concentrations is obviously flux of dissolved minerals from interstitial waters, which extends to considerable distances in vertical direction.
description: Supplement to: Demina, Lyudmila L; Atnashev, Vitaly B (1989): Anomalous behavior of metals in the vicinity of an underwater gas vent off Paramushir Island, Sea of Okhotsk. Oceanology, 29(6), 708-714
DOI: 10.1594/pangaea.497377
title: Physical oceanography from BT during cruise U06X000200B_1942
DOI: 10.1594/pangaea.893404
title: CICE output from Navy Earth System Model (NESM) for 2018032612

description: INITIALIZATION: 2018032612FORECASTS:daily at 00Z out to 45 days (t1068)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.877559
title: Georeferenced photographs of benthic photoquadrats acquired along transects from Farquharson Reef in the Cairns to Cooktown region of the Great Barrier Reef (2017-01)
DOI: 10.1594/pangaea.898226
title: Snow density in snow pits around Weisssee snow research site (2014-2018)
DOI: 10.1594/pangaea.872142
title: Principal Component Analysis of TerraSAR-X backscatter and coherence stacks one year (2012-2013) in the Lena River Delta, links to GeoTIFFs

description: Principal Component Analysis (PCA) is a well-established technique in remote sensing for the visualization of multidimensional data. It reduces redundancy in multiband or multitemporal imagery, increases the signal-to-noise ratio and provides an opportunity to use multitemporal datasets for change detection. PCA transforms the axes of multidimensional data in such way that the new axes (the principal components) account for variances within the data, with the first PC accounting for the largest variance and the last PC accounting for the smallest variance. In our study PCA of TerraSAR-X time stacks of backscatter intensity and interferometric coherence provided a good spatial overview of the essential information contained within the multiple time slices. The PC1 for both stacks showed the most common features of the contributing images and represented the means of the temporal stacks. The PC1 of the coherence stack accounted for 29% of the variance (or unique information) and mapped (i) water bodies (lakes and river), (ii) rocky outcrops, and (iii) the remaining land surfaces. The PC1 of the backscatter stack accounted for 35% of the variance and was contaminated by such effects as the presence or absence of lake ice and shadow/layover in the rocky outcrops region. Anomalies in seasonal patterns were demonstrated by the higher PCs. The PC2 of the backscatter stack accounted for 22% of the variance and delineated water bodies. The PC3 of backscatter stack accounted for only 4% of the variance in the dataset and represented the spatial variance in river ice conditions during spring. The PC2 of coherence, which accounted for 9.5% of the variance in the coherence stack, represented the spatially variable snow conditions in spring (snowmelt to the south and stable snow cover to the north).
description: Input dataset includes 35 repeat-pass StripMap TerraSAR-X images acquired over the central Lena River Delta, Siberia, from 3 August 2012 to 14 September 2013 every 11 days with a few gaps. TerraSAR-X is a Synthetic Aperture Radar operating in X-band (wavelength 3.1 cm, frequency 9.6 GHz). The scene size measured approximately 18 × 56 km. The orbit was in descending pass and the radar was right-looking. The acquisition incidence angle was approximately 31° and the polarization channel was HH for all used images. Local time of acquisitions was 08:34 (UTC: 22:34).Based on this dataset, two stacks were created: (1) 35 backscatter intensity images and (2) 31 sequential 11-day interferometric coherence images. All images were geocoded to the WGS84 ellipsoid with a pixel size of 10 x 10 m in the Universal Transverse Mercator (UTM) projection Zone 52N. We applied PCA to the both stacks using the PCA tool in ArcGIS TM (ESRI). We provide here the first four PCs for each of the stacks as georeferenced rasters (.tif) as well as the text files with the covariance and correlation matrices, eigenvectors and eigenvalues.
DOI: 10.1594/pangaea.896817
title: LOI profile SHE IV, Lough Sheeauns, Connemara, Co. Galway

description: Pollen analyst: Sinéad Keane. Palaeoenvironmental Research Unit, NUI Galway, Galway, Ireland. Sampling density: variable; mainly 8 cm intervals. No. of spectra: 90. 442-402: continuous sampling. Lycopodium spore suspension of know concentration added; acetolysis, mounted in glycerine. Cereal-type pollen differentiated using Beug (1961) criteria (37 um taken as cutoff point; but only pollen grains 40 um and greater included in cereal-type). Pollen nomenclature generally follows Moore et al. 1991. &lt;1 = recorded outside the pollen counts (most samples searched for additional taxa). Distinction between Myrica and Corylus not made; combined counts given. Charcoal particles ≥37 µm counted during routine pollen counting
DOI: 10.1594/pangaea.874275
title: Photographs of benthic communities in the area The-sign, Comau Fjord at 2017-02-16

description: This dataset was generated in the frame of the co-operation between the Huinay Scientific Field Station (http://www.huinay.cl) and the Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research (http://www.awi.de).
DOI: 10.1594/pangaea.874231
title: Earth system model results by the MPI-ESM-LR of the MiKlip Decadal climate prediction experiment improved by ocean ensemble dispersion filtering, links to NetCDF files

description: Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two timescales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state towards the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering towards the ensemble mean.
description: The NetCDF data is organized in CMOR directory structure separated in ZIP archives containing one variable at a time. Decadal experiments from 1974 to 2012 consist of 5 ensemble member each forecasting 5 years ahead. A ensemble dispersion filter is applied every 3 months on ocean temperatures.
description: Supplement to: Kadow, Christopher; Illing, Sebastian; Kröner, Igor; Ulbrich, Uwe; Cubasch, Ulrich (2017): Decadal climate predictions improved by ocean ensemble dispersion filtering. Journal of Advances in Modeling Earth Systems
DOI: 10.1594/pangaea.893406
title: CICE output from Navy Earth System Model (NESM) for 2018033112

description: INITIALIZATION: 2018033112FORECASTS:daily at 00Z out to 45 days (t1068)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.881568
title: Matrix approach to land carbon cycle modeling: A case study with Community Land Model, link to input data in NetCDF format

description: The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial-temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective.
description: The input data (one zip file) for an demonstration global simulation for manuscript "Matrix approach to land carbon cycle modeling: A case study with Community Land Model". It contains one NetCDF file that provides required input variables for the matrix simulation and one mat file about soil depth information.
description: Supplement to: Huang, Yuanyuan; Lu, Xingjie; Shi, Zheng; Lawrence, David M; Koven, Charles D; Xia, Jianyang; Du, Zhenggang; Kluzek, Erik; Luo, Yiqi (2018): Matrix approach to land carbon cycle modeling: A case study with the Community Land Model. Global Change Biology, 24(3), 1394-1404
DOI: 10.1594/pangaea.893407
title: CICE output from Navy Earth System Model (NESM) for 2018040112

description: INITIALIZATION: 2018040112FORECASTS:daily at 00Z out to 45 days (t1068)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.898232
title: Snow depth (SPA) at Weisssee snow research site (2014-2018)
DOI: 10.1594/pangaea.893408
title: CICE output from Navy Earth System Model (NESM) for 2018040212

description: INITIALIZATION: 2018040212FORECASTS:daily at 00Z out to 45 days (t1068)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.701017
title: Monthly landings of marine products, Puerto Cisne, Chile, 2002
DOI: 10.1594/pangaea.897154
title: Plainfin midshipman (Porichthys notatus) dissection measures
DOI: 10.1594/pangaea.893409
title: CICE output from Navy Earth System Model (NESM) for 2018040312

description: INITIALIZATION: 2018040312FORECASTS:daily at 00Z out to 45 days (t1068)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.874396
title: Modeled and Measured salinity, oxygen and derived cod egg survival data for the Arkona Basin and the Bornholm Basin in the Baltic Sea

description: This data set contains several tables with modeled and measured data and also correlations coefficient data used in the publication.The model data are aggregations of areas in the Arkona Basin (AB) and Bornholm Basin (BB) from the Kiel Baltic Sea Ice and Ocean model (BSIOM) for the period 1971 to 2015. See the puplication for details about horizontal aggregation. Raw Data of the Model is not included in this data deposition, but are given by the authors upon request and when credited in any use of the data.Monthly Means of the AB and BB are used for detailed correlation analysis with time lags (raw data is given in the files "ModelData_O2_BornholmBasin_MM_ModelDepths.." and "ModelData_S_ArkonaBasin_MM_modelDepths.."). Resulting data of all combinations for depth layers in either Basin, and Monthly lags up to a full year, is given in the "ModelData_correlation_ABMM_vs_BBMM.txt" file.Monthly profiles of the Bornholm Basin were also used to produce monthly means of S,T,O2 and cod egg survival chances on certain levels of water density (1009, 1010, 1011, 1012 and 1013 kg/m^3) given in the file "ModelData_O2_BornholmBasin_MM_onDensLayers.txt"Model data for the Bornholm Basin were also used to produce a time series of daily resolution of the mean oxygen content below the halocline. Data is given in the file "ModelData_O2_BornholmBasin_DM_rough_layers.txt"Measured salinity at the 33m depth level in a daily resolution is taken from the Arkona Basin platform (permanent measuring buoy) operated by the Federal Maritime and Hydrography Agency, Hamburg, Germany. Given in file "Measured_S_ArkonaBasin_DM_33m_corrected.txt"
description: The research leading to these results has received funding from BONUS (INSPIRE and BIO-C3 projects), the joint Baltic Sea research and development programme (Art 185), funded jointly from the European Union's Seventh Programme for research, technological development and demonstration (Forschungszentrum Jülich Beteiligungsgesellschaft mbH (Germany) and BMBF (Grant No. 03F0682A). We also like to thank the DEMO project - "DEMOnstration exercise for Integrated Ecosystem Assessment and Advice of Baltic Sea fish stocks" financed by Granholms stiftelse and Baltic Eye at Stockholm University Baltic Sea Centre for support. None of the named funding sources were involved in study design; in collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.
description: Supplement to: von Dewitz, Burkhard; Tamm, Susanne; Höflich, Katharina; Voss, Rüdiger; Hinrichsen, Hans-Harald (2018): Use of existing hydrographic infrastructure to forecast the environmental spawning conditions for Eastern Baltic cod. PLoS ONE, 13(5), e0196477
DOI: 10.1594/pangaea.898235
title: Raw values of snow temperature at 10cm depth at Weisssee snow research site (2014-2018)

description: Only meaningful measurements if snow covered.
DOI: 10.1594/pangaea.874276
title: Photographs of benthic communities in the area X-Telele, Comau Fjord at 2017-02-17

description: This dataset was generated in the frame of the co-operation between the Huinay Scientific Field Station (http://www.huinay.cl) and the Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research (http://www.awi.de).
DOI: 10.1594/pangaea.898227
title: Raw values of snow density at 10cm depth at Weisssee snow research site (2014-2018)

description: Only meaningful measurements if snow covered.
DOI: 10.1594/pangaea.890335
title: CICE output from Navy Earth System Model (NESM) for 2018051512

description: INITIALIZATION: 2018051512FORECASTS:daily at 00Z out to 45 days (t1068)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;