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Abstract: Not Available Category: geoscientificInformation Source: Not Available Supplemental Information: Not Availble Coverage: EVENT LABEL: (MSM76_22-1, MSM76_153-1) * LATITUDE START: 65.543370 * LONGITUDE START: -29.296630 * LATITUDE END: 65.541220 * LONGITUDE END: -29.309290 * DATE/TIME START: 2018-08-13T15:05:00 * DATE/TIME END: 2018-08-25T20:25:00 * ELEVATION START: -972.0 m * ELEVATION END: -970.0 m * LOCATION: North Atlantic * CAMPAIGN: MSM76 * BASIS: Maria S. Merian * METHOD|DEVICE: Mooring (short time)
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Abstract: Not Available Category: geoscientificInformation Source: Not Available Supplemental Information: Not Availble Coverage: EVENT LABEL: (PS107_23-1, PS114_43-1) * LATITUDE START: 78.831000 * LONGITUDE START: -2.792200 * LATITUDE END: 78.831000 * LONGITUDE END: -2.792200 * DATE/TIME START: 2017-08-04T14:00:00 * DATE/TIME END: 2018-07-26T12:00:00 * ELEVATION START: -2589.0 m * ELEVATION END: -2589.0 m * CAMPAIGN: PS107 * BASIS: Polarstern * METHOD|DEVICE: Mooring (long time)
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Abstract: Not Available Category: geoscientificInformation Source: Not Available Supplemental Information: Not Availble Coverage: EVENT LABEL: (PS107_38-7, MSM77_4-9) * LATITUDE START: 79.078000 * LONGITUDE START: 4.112300 * LATITUDE END: 79.078000 * LONGITUDE END: 4.112300 * DATE/TIME START: 2017-08-11T16:00:00 * DATE/TIME END: 2018-06-10T01:50:00 * ELEVATION START: -2493.0 m * ELEVATION END: -2493.0 m * CAMPAIGN: PS107 * BASIS: Polarstern * METHOD|DEVICE: Mooring (long time)
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Abstract: Not Available Category: geoscientificInformation Source: Not Available Supplemental Information: Not Availble Coverage: EVENT LABEL: (MSM76_12-1, MSM76_155-1) * LATITUDE START: 65.475620 * LONGITUDE START: -29.570080 * LATITUDE END: 65.480720 * LONGITUDE END: -29.609510 * DATE/TIME START: 2018-08-12T22:44:00 * DATE/TIME END: 2018-08-26T11:19:00 * ELEVATION: -930.0 m * LOCATION: North Atlantic * CAMPAIGN: MSM76 * BASIS: Maria S. Merian * METHOD|DEVICE: Mooring (short time)
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Abstract: Foraminifera are commonly used in paleoclimate reconstructions as they occur throughout the world's oceans and are often abundantly preserved in the sediments. Traditionally, foraminifera‐based proxies like δ18O and Mg/Ca are analyzed on pooled specimens of a single species. Analysis of single specimens of foraminifera allows reconstructing climate variability on timescales related to El Niño-Southern Oscillation or seasonality. However, quantitative calibrations between the statistics of individual foraminifera analyses (IFA) and climate variability are still missing. We performed Mg/Ca and δ18O measurements on single specimens from core top sediments from different settings to better understand the signal recorded by individual foraminifera. We used three species of planktic foraminifera (Globigerinoides ruber (s.s.), T. sacculifer, and N. dutertrei) from the Indo‐Pacific Warm Pool and one species (G. ruber (pink)) from the Gulf of Mexico. Mean values for the different species of Mg/Ca versus calculated δ18O temperatures agree with published calibration equations. IFA statistics (both mean and standard deviation) of Mg/Ca and δ18O between the different sites show a strong relationship indicating that both proxies are influenced by a common factor, most likely temperature variations during calcification. This strongly supports the use of IFA to reconstruct climate variability. However, our combined IFA data for the different species only show a weak relationship to seasonal and interannual temperature changes, especially when seasonal variability increases at a location. This suggests that the season and depth habitat of the foraminifera strongly affect IFA variability, such that ecology needs to be considered when reconstructing past climate variability. Category: geoscientificInformation Source: Supplement to: Groeneveld, Jeroen; Ho, Sze Ling; Mackensen, Andreas; Mohtadi, Mahyar; Laepple, Thomas (2019): Deciphering the variability in Mg/Ca and stable oxygen isotopes of individual foraminifera. Paleoceanography and Paleoclimatology, 34(5), 755-773, https://doi.org/10.1029/2018PA003533 Supplemental Information: Not Availble Coverage: Not Available
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Abstract: EnKF data assimilation outputs in support of Albright et al. (2009) in Geophysical Research Letters. Contains the modeled reservoir parameters, projected surface deformation, reservoir wall tensile stress, and host rock Mohr-Coulomb failure at each iteration of the assimilation for 4 different versions that vary input data and rock rheology. Category: geoscientificInformation Source: Supplement to: Albright, John A; Gregg, Patricia M; Lu, Zhong; Freymueller, Jeffrey T (2019): Hindcasting magma reservoir stability preceding the 2008 eruption of Okmok, Alaska. Geophysical Research Letters, https://doi.org/10.1029/2019GL083395 Supplemental Information: Not Availble Coverage: EVENT LABEL: * LATITUDE: 53.432000 * LONGITUDE: -168.130000 * METHOD|DEVICE: Multiple investigations
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Abstract: Marine phytoplankton are responsible for half of the global net primary production and perform multiple other ecological functions and services of the global ocean. These photosynthetic organisms comprise more than 4300 marine species, but their biogeographic patterns and the resulting species diversity are poorly known, mostly owing to severe data limitations. Here, we compile, synthesize, and harmonize marine phytoplankton occurrence data from the two largest biological occurrence archives (Ocean Biogeographic Information System; OBIS, and Global Biodiversity Information Facility; GBIF) and three recent data collections. The resulting PhytoBase data set contains over 1.36 million marine phytoplankton occurrence records (1.28 million at the level of species) for a total of 1717 species, spanning the principal groups of the Bacillariophyceae, Dinoflagellata, and Haptophyta as well as several other groups. This data compilation increases the amount of phytoplankton occurrence data available through the single largest contributing archive (OBIS) by 65%. Data span all ocean basins, latitudes and most seasons. Analyzing the oceanic inventory of sampled phytoplankton species richness at the broadest spatial scales possible, using a resampling procedure, we find that richness tends to saturate in the pantropics at ~93% of all species in our database, at ~64% in temperate waters, and at ~35% in the cold Northern Hemisphere, while the Southern Hemisphere remains underexplored. We provide metadata on the cruise, research institution, depth, and date for each occurrence record. Cell-counts for 195 339 records are also included. We strongly recommend consideration of global spatiotemporal biases in sampling intensity and varying taxonomic sampling scopes between research programs when analyzing the occurrence database. Including such information into statistical analysis tools, such as species distribution models, may serve to project the diversity, niches, and distribution of species in the contemporary and future ocean, opening the door for a quantification of macro-ecological phytoplankton patterns. Category: geoscientificInformation Source: Not Available Supplemental Information: Not Availble Coverage: Not Available
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Abstract: Optimum Multiparameter Model in Matlab code to solve the mixing of water masses in the North and South Atlantic ocean based on GOSHIP cruises with available Dissolved Organic Carbon (DOC) data. Data below 250 dbar and colder than 14ºC are considered. The scripts solve the mixing of central, intermediate, deep and bottom waters crossed by the GOSHIP lines (A22-2012, A20-2012, A13.5-2010, A16N-2013, A16S-2013). INPUT variables are the comprised within a matlab file (OMP_ATL_DOM.mat) containing hydrographic and biogeochemical data as provided in the OCADS repository for Repeat Hydrography. The OUTPUT is generated in the file OMP_RESULTS.xlsx containing self explaining names of the output variables. A detailed explanation of the OMP settings, constraints and results to analyse and check is given in the linked Global Biogeochemical Cycles manuscript. To inititate the OMP analysis just run "Megaprograma.m", the analysis will start and when ending the results will appear in the xlsx file. Category: geoscientificInformation Source: Supplement to: Romera-Castillo, Cristina; Álvarez, Marta; Pelegri, Jose L; Hansell, Dennis A; Alvarez-Salgado, Xose Anton (submitted): Net additions of recalcitrant dissolved organic carbon in the deep Atlantic Ocean. Global Biogeochemical Cycles Supplemental Information: Not Availble Coverage: Not Available
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Abstract: Here we present Late Miocene (~11-7 Ma) model boundary conditions used by Knorr et al. [2011] in two files (Paleogeography.nc and Surface_conditions.nc). These boundary conditions relate to Figure 1 in the corresponding study. The file Paleogeography.nc (0.5°x 0.5° resolution) contains the orography (positive values and zero) and bathymetry (negative values). The file Surface_conditions.nc contains land surface conditions. Besides the glacier mask these surface conditions (3.75°x 3.75° resolution) contain the vegetation distribution that is represented by specifying different land surface parameters including, surface albedo, surface roughness length, field capacity of soil, forest ratio, leaf area index, fractional vegetation cover, and soil data flags (Food and Agriculture Organization soil map) [cf. Hagemann et al., 1999]. For further details regarding the paleogeography reconstruction and proxy-based reconstruction of the Late Miocene vegetation we would like to refer to Micheels et al. [2007], Micheels et al. [2011] and the references therein. Category: geoscientificInformation Source: Supplement to: Knorr, Gregor; Butzin, Martin; Micheels, Arne; Lohmann, Gerrit (2011): A warm Miocene climate at low atmospheric CO2 levels. Geophysical Research Letters, 38(20), https://doi.org/10.1029/2011GL048873 Supplemental Information: Zip folder with two datasets: Paleogeography.nc and Surface_conditions.nc Coverage: Not Available
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Abstract: This dataset contains global lightning stroke density calculated from georeferenced stroke count data from the World Wide Lightning Location Network (WWLLN). The real-time raw stroke count data were reprocessed by WWLLN to remove artifacts and improve geolocation, which resulted in the "AE" georeferenced and timestamped stroke count data. These data were then gridded at 0.5 degree and hourly resolution, converted into density, and corrected for detection efficiency using the WWLLN global gridded detection efficiency maps. The corrected hourly grids were then aggregated into monthly totals and into a multi-year monthly mean climatology. The data cover the period 2010-2018 and will be updated in the coming years. The data are stored in a NetCDF (version 4) files and have the following attributes: - Spatial extent: Entire Earth - Spatial reference system (SRS): Unprojected (geographic, WGS84) - Spatial resolution: 30 arc-minutes (720 rows by 360 columns) - Temporal extent: 2010-2018 - Temporal resolution: One month (108 time steps for the monthly data; 12 for the climatology) - Variable: lightning: frequency of lightning flashes per unit area - Units: strokes per km2 Category: geoscientificInformation Source: Not Available Supplemental Information: Zip folder with two datasets: WWLLN_climatology.nc and WWLLN_monthly.nc Coverage: Not Available
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