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DL-FRONT MERRA-2 vectorized weather fronts over North America, 1980-2018 (netCDF format)
<p>DL-FRONT is a Deep Learning Neural Network (DLNN) that was trained to detect weather fronts using spatial grids of near-surface atmospheric variables. The dataset is composed of <a href="http://www.unidata.ucar.edu/software/netcdf/docs/">netCDF-4</a> files. Each file contains one year of hourly geospatial data grids describing the locations of four types of weather fronts—cold front, warm front, stationary front, and occluded front, over the time span 1980-2018.</p> <p>This dataset is the product of processing data from the National Aeronautics and Space Administration (NASA) <a href="https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/">Modern-Era Retrospective analysis for Research and Applications, Version 2</a> (MERRA-2). DL-FRONT processed MERRA-2 hourly data grids of instantaneous measures of air pressure reduced to mean sea level, air temperature at 2 meters, specific humidity at 2 meters, and wind velocity at 10 meters over the time span 1980 - 2018 to produce this dataset. The original MERRA-2 data were resampled at 1 degree resolution over the spatial range 31W - 171W x 10N - 77N using bicubic interpolation.</p> <p>At each hourly time step the network produced a set of spatial grids with the same resolution and spatial range as the input, one for each of the five categories mentioned above. Each cell in a spatial grid for a given category records the network-assigned probability (from 0.0 to 1.0) that the cell is in a weather front boundary region of that category (or, for the "no front" category, the probability that the cell is not in any weather front boundary region).</p> <p>Each weather front probability map was then processed to obtain polyline skeletons of the weather front boundary regions found by DL-FRONT. These vector representations of the fronts were then written to JSON files—one file for each hour. These front polylines were then rasterized into geospatial data grids and stored by year into netCDF-4 files that conform to the <a href="http://cfconventions.org/">Climate and Forecast Metadata Conventions</a>. The front data in each file is stored in a netCDF variable with dimensions (time, front type, y, x), where x and y are geospatial dimensions. There is a 2D geospatial data grid for each time step for each of the 4 front types—cold, warm, stationary, and occluded.</p> <p>There are two large groupings of the netCDF files. One group uses a data grid based on the <a href="https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/north-american-regional-reanalysis-narr">North American Regional Reanalysis</a> (NARR) <a href="https://www.nco.ncep.noaa.gov/pmb/docs/on388/tableb.html#GRID221">grid</a>, which is a Lambert Conformal Conic projection coordinate reference system (CRS) centered over North America. The NARR grid is quite close the the spatial range of data displayed on the WPC workstations used to perform surface analysis and identify front locations. The native NARR grid has grid cells which are 32 km on each side. Our grid covers the same extents with cells that are 96 km on each side.</p> <p>The other group uses a 1° latitude/longitude data grid centered over North America with extents 171W – 31W / 10N – 77 N. The files in this group are identified by the name MERRA2, because they were used with data from the NASA MERRA-2 dataset, which uses a latitude/longitude data grid.</p> <p>There are a number of files within each group. The files all follow the naming convention merra2_[masked]_<grid>_<n>wide_<year>.nc, where [masked] indicates that the presence of the word <em>masked</em> is optional and <grid> is either <em>merra2-1deg</em> or <em>narr-96km</em>. The the sequence <n>wide indicates the width with which the fronts were drawn, and <year> is the year for the data stored in the file.</p> <p>The files marked as masked had a mask applied to the data grids that corresponded to the envelope of the geospatial region where there are, on average, 40 or more front crossing of any type per year, as determined using the <a href="https://dx.doi.org/10.5281/zenodo.2651361">Coded Surface Bulletin </a>dataset.</p> <p>The <n>wide portion of the file names takes two forms—<em>1wide</em> and <em>3wide</em>. The fronts in the <em>1wide</em> files were rasterized by drawing the front polylines with a width of one grid cell. The fronts in the <em>3wide</em> files were rasterized by drawing the front polylines with a width of 3 grid cells.</p> <p>Within each grid group, there are four subsets of files:</p> <ul> <li>merra2_masked_<grid>_1wide_<year>.nc</li> <li>merra2_masked_<grid>_3wide_<year>.nc</li> <li>merra2_<grid>_1wide_<year>.nc</li> <li>merra2_<grid>_3wide_<year>.nc</li> </ul>
FIG. 1 in A remarkable new genus and new species of Odonata, of the legion Podagrion, Selys, from north Queensland
FIG. 1. Wings of Chorismagrion risi (nat. length of h.-w. 22 mm.). 2. Wings of Chorismagrion risi, basal part more enlarged. 3. Apex of abdomen of Chorismagrion risi, from above. 4. Wings of Hemiphlebia mirabilis from Alexandra, Victoria (nat. length of h.-w. about 11 mm.).
Fig. 7 in A new species of Ampharete (Annelida: Ampharetidae) from the West Shetland shelf (NE Atlantic Ocean), with two updated keys to the species of the genus in North Atlantic waters
Fig. 7. Ampharete oculicirrata sp. nov., paratype MNCN 16.01/18482_spec. 5. A. Anterior end, ventral view. B. Buccal tentacle with pinnae. C. First four abdominal uncinigers, lateroventral view. D. Posterior end, from AU8 to pygidium, ventral view. Abbreviations: AU = abdominal unciniger; bl = buccal lip; br = branchia; bt = buccal tentacle; btp = buccal tentacle pinna; pal = paleae; plc = pygidial lateral cirrus; pp = pygidial papillae; SG = segment; vpo = ventral pharyngeal organ. Scale bars: A, C = 150 µm; B = 25 µm; D = 100 µm.
FIGS3, 4 in A Second Species Of Episynlestes Kennedy (Odonata: Chlorolestidae) From North Queensland
FIGS3, 4Anal appendages of male Episynlestes cristatus sp. n., paratype. Paluma: (3) dorsal view: (4) right lateral view.
FIGS1,2 in A Second Species Of Episynlestes Kennedy (Odonata: Chlorolestidae) From North Queensland
FIGS1,2- Venation of male Episynlestes cristatus sp. n.. paratypes, Paluma: (1) base of fore and hind wings; (2) region of pterustigma.
Fig. 6 in A new species of Ampharete (Annelida: Ampharetidae) from the West Shetland shelf (NE Atlantic Ocean), with two updated keys to the species of the genus in North Atlantic waters
Fig. 6. Ampharete oculicirrata sp. nov., paratype MNCN 16.01/18482_spec. 3. A. Abdominal unciniger 7, posterior view. B. Detail of abdominal uncini, frontal and lateral view. Scale bars: A =150 µm; B = 5 µm.
Fig. 4 in A new species of Ampharete (Annelida: Ampharetidae) from the West Shetland shelf (NE Atlantic Ocean), with two updated keys to the species of the genus in North Atlantic waters
Fig. 4. Ampharete oculicirrata sp. nov., paratype MNCN 16.01/18482_spec. 2. A. Incomplete specimen, dorsal view. B. Anterior end, dorsal view and detail of prostomium and nuchal organ; large arrow pointing to gap between groups of branchiae; framed enlarged areas: prostomium (bottom left) and branchial ciliation (bottom right). Abbreviations: br = branchia; nuo = nuchal organ; pal = paleae; pros(ml) = prostomium (median lobe). Scale bars = 200 µm.
Fig. 3 in A new species of Ampharete (Annelida: Ampharetidae) from the West Shetland shelf (NE Atlantic Ocean), with two updated keys to the species of the genus in North Atlantic waters
Fig. 3. Ampharete oculicirrata sp. nov., paratype MNCN 16.01/18482_spec. 1. A. First three abdominal uncinigers, lateral view. B. Thoracic unciniger 11. C. Abdominal unciniger 1. D. Abdominal unciniger 2. E. Abdominal unciniger 3. F. Posterior end, from AU7 to pygidium. Abbreviations: AU = abdominal unciniger; plc = pygidial lateral cirrus. Scale bars: A, F = 100 µm; B–D = 10 µm; E = 15 µm.
Fig. 1 in A new species of Ampharete (Annelida: Ampharetidae) from the West Shetland shelf (NE Atlantic Ocean), with two updated keys to the species of the genus in North Atlantic waters
Fig. 1. Ampharete oculicirrata sp. nov., holotype NMS.Z.2019.8.1 (A–B, D–E), paratype MNCN 16.01/18476 (C, F). A. Complete specimen, dorsolateral view, and detail of several thoracic and abdominal parapodia. B. Anterior end, lateral view. C. Anterior end, dorsal view. D–E. Posterior end, dorsal and ventral view. F. Posterior end, lateral view. Abbreviations: AU = abdominal unciniger; bl = buccal lip; br = branchia; brph = branchiophore; bt = buccal tentacle; btp = buccal tentacle pinna; eye(i) = pygidial eye; eye(p) = prostomial eye; pal = paleae; plc = pygidial lateral cirrus; pp = pygidial papillae; pros(ll) = prostomium (lateral lobe); pros(ml) = prostomium (median lobe); TN = thoracic notopodium; TU = thoracic unciniger. Scale bars: A = 1 mm; B–C = 200 µm; D–F = 100 µm.
Fig. 2 in A new species of Ampharete (Annelida: Ampharetidae) from the West Shetland shelf (NE Atlantic Ocean), with two updated keys to the species of the genus in North Atlantic waters
Fig. 2. Ampharete oculicirrata sp. nov., paratype MNCN 16.01/18482_spec. 1. A. Anterior end, lateral view. B. Paleae and first two thoracic chaetigers, lateral view. C. Thoracic notopodium and chaetae, anterior view. D. Uncini of second thoracic unciniger (thoracic chaetiger 4). Abbreviations: brph = branchiophore; nuo = nuchal organ; pal = paleae; pros(ml) = prostomium (median lobe); TN = thoracic notopodium; TU = thoracic unciniger. Scale bars: A = 200 µm; B = 100 µm; C = 20 µm; D = 15 µm.
Fig. 5 in A new species of Ampharete (Annelida: Ampharetidae) from the West Shetland shelf (NE Atlantic Ocean), with two updated keys to the species of the genus in North Atlantic waters
Fig. 5. Ampharete oculicirrata sp. nov., paratype MNCN 16.01/18482_spec. 3. A. Transitional area between thorax and abdomen, ventral view. B. Peristomium, ventral view. C. Paleae and first three thoracic chaetigers, ventral view. Abbreviations: AU = abdominal unciniger; bl = buccal lip; br = branchia; pal = paleae; per = peristomium; pros(ll) = prostomium (lateral lobe); pros(ml) = prostomium (median lobe); SG = segment; TC = thoracic chaetiger; TN = thoracic notopodium; TU = thoracic unciniger; vs = ventral shield. Scale bars: A = 200 µm; B–C = 100 µm.
North Atlantic circulation: a perspective from ocean reanalyses
<p>We provide data here from our paper "North Atlantic circulation: a perspective from ocean reanalyses". All files are netcdf or text files (or a tar of files).</p> <p>clim_MLD.tar.gz : time mean mixed layer depths (Fig 1)</p> <p>clim_AMOC.tar.gz : time mean AMOC streamfunctions (Fig 2)</p> <p>clim_gyre.tar.gz : time mean barotropic streamfunctions (Fig 3)</p> <p>clim_box_transports.csv : volume transports for the subtropical and subpolar regions split into upper, lower, boundary and interior (Fig 4)</p> <p>clim_transports.tar : heat and freshwater transports by latitude (Fig 5)</p> <p>clim_scatter_fig6-7.tar : time mean labrador sea densities, AMOC and subpolar gyre strengths, heat and freshwater transports (Fig 6+7)</p> <p> timeseries_TS.tar : timeseries of temperature and salinity anomalies in the upper 500m over region 25-45N and 45-65N. Also volumes of water> 10 degrees or 35.3PSU (Fig 8)</p> <p>timeseries_fig9.tar : timeseries of labrador sea density and mixed layer depth (Fig 9)</p> <p>dens_control_data.nc : the relationship between salinity and temperature control on density timeseries (Fig 10)</p> <p>timeseries_amoc.tar : timeseries of AMOC at 26.5N and 50N (Fig 11)</p> <p>rapid_corr.csv : correlations and standard deviations of components of AMOC at 26.5N compared to observations (Fig 12)</p> <p>timeseries_osnap.nc : timeseries of overturning across the OSNAP section (Fig 13)</p> <p>timeseries_gyres.tar : timeseries of subpolar and subtropical gyre strengths (Fig 14)</p> <p>Fig 15 uses data from Fig 9, 11,14</p> <p>timeseries_transports.tar : timeseries of heat and freshwater transports at 26.5N and 50N (Fig 16, 17)</p> <p>Fig 18 uses data from Fig 11, 16,17<br> </p>
Figs. 6-7. 6 in Odonata (Insecta) from Different States of North Eastern India
Figs. 6-7. 6, Megalestes lieftincki, sp. nov., ♂ holotype; 7, Neurothemls tullia tullia (Drury), isochrome ♀,
Figs. 1-4 in Odonata (Insecta) from Different States of North Eastern India
Figs. 1-4. Megalestes lieftincki, sp. nov. Holotype: 1-2, Anal appendages; 1, dorsal view; 2, right lateral view; 3-4, Penis: 3, lateral view; 4, apex, dorsal view; Fig. 5. Crocothemis servilia servilia (Drury) ♀ Synthorax, lateral view.
Cairn and Landscape Interaction: A Study of Human Ecodynamics in the North Atlantic
<p>Cairns are very versatile constructions, used for a variety of human activities. For this reason, this project focuses on the study of navigational and agricultural cairns as a way to further the study and understanding of human ecodynamics in the North Atlantic. The project was developed within the wider framework of DataARC, a ciberinfrastructure that interconnects and facilitates access to several North Atlantic datasets.</p> <p>The study uses a variety of interdisciplinary data, methodologies, tools, and approaches in its analysis. It is divided in two case studies. The first case study analyses the role of navigational cairns and their relationship with the roads and the general landscape while creating proposed routes between late medieval/early modern farm networks in Iceland. The results support the hypothesis that cairns were being used as road markers, and suggests a dependence between landscape features and cairn positioning, indicating landscape agency. The second case study focuses on analysing the position and effect of clearance cairns in the Scottish landscape. Archaeological and landscape data (i.e. soil quality, land compaction, erosion levels, and continued use in agricultural practices) were combined in a newly created dataset that was examined using statistical analysis. The results show a correlation between the presence of cairns and a high erosion risk while proposing three effects of clearance cairns on soils: so exhaustive they are no longer cultivable, they are cultivable but have a risk of erosion, and so non-exhaustive that they can still be cultivated.</p> <p>Overall, the project's findings highlight cairn's usefulness in the study of human ecodynamics. The datasets available here belong to both case studies. The first presents an Icelandic (Westfjords) navigational dataset with information from the routes the cairns are located in as well as their likelihood of being a route marker. The second offers a Scottish clearance cairn dataset which includes a variety of archaeological, historical, and geological data. There are two versions of this dataset: the raw version (ClearanceCairnDataset) and the processed version which offers an interactive table which classifies the cairns on the basis of soil type as well as a variety of other variables (InteractiveClearanceCairns). The code used to analyse this dataset and produce bar charts and pie charts has also been uploaded both in its original R file and a XPS version. Both datasets include metadata in PDF format. A CSV file with combinators created to connect these datasets to DataARC's concept map has also been included (CombinatorsForDataARC).</p>
Dataset for the article: "Weak genetic structure despite strong genomic signal in lesser sandeel in the North Sea"
<p>Dataset used for the article: "Weak genetic structure despite strong genomic signal in lesser sandeel in the North Sea".</p> <p>Dataset consists on a VCF file from 471 individuals of lesser sandeel, <em>Ammodytes marinus</em> (L.). This VCF is the end product of the bioinformatic analysis described in the paper Jimenez-Mena et al. (2019). Data was obtained from double-digest Restriction-site Associated DNA (ddRAD) sequencing. More information can be obtained in Methods of the article. The information of each of the individuals in the VCF is also included as a separate file, as well as the supplementary tables of the article.</p>
Fig. 613 in Review of Aphidiinae parasitoids (Hymenoptera: Braconidae) of the Middle East and North Africa: key to species and host associations
Fig. 613. Map of the Middle East and North Africa. A country is highlighted with green color indicates that there are available data on aphidiine parasitoids. A country highlighted with red color, indicates that there are no available data on aphidiine parasitoids
Figs 546–562 in Review of Aphidiinae parasitoids (Hymenoptera: Braconidae) of the Middle East and North Africa: key to species and host associations
Figs 546–562. Lateral aspect of ♀ genitalia: 546. Areopraon lepelleyi. 547. Betuloxys hortorum. 548. Binodoxys acalephae. 549. Binodoxys angelicae. 550. Binodoxys brevicornis. 551. Binodoxys centaureae. 552. Binodoxys heraclei. 553. Diaeretiella rapae. 554. Diaeretus leucopterus. 555. Ephedrus cerasicola. 556. Ephedrus chaitophori. 557. Ephedrus helleni. 558. Ephedrus lacertosus. 559. Ephedrus nacheri. 560. Ephedrus niger. 561. Ephedrus persicae. 562. Ephedrus plagiator.
Figs 581–598 in Review of Aphidiinae parasitoids (Hymenoptera: Braconidae) of the Middle East and North Africa: key to species and host associations
Figs 581–598. Lateral aspect of ♀ genitalia: 581. Pauesia silana. 582. Pauesia unilachni. 583. Praon abjectum. 584. Praon absinthii. 585. Praon athenaeum. 586. Praon barbatum. 587. Praon bicolor. 588. Praon exsoletum. 589. Praon flavinode. 590. Praon gallicum. 591. Praon longicorne. 592. Praon necans. 593. Praon nonveilleri. 594. Praon orpheusi. 595. Praon pubescens. 596. Praon rosaecola. 597. Praon unitum. 598. Praon uroleucon.
Figs 488–499 in Review of Aphidiinae parasitoids (Hymenoptera: Braconidae) of the Middle East and North Africa: key to species and host associations
Figs 488–499. Anterolateral aspect of petiole in Aphidius species (♀): 488. Aphidius platensis. 489. Aphidius popovi. 490. Aphidius rhopalosiphi. 491. Aphidius rosae. 492. Aphidius salicis. 493. Aphidius setiger. 494. Aphidius smithi. 495. Aphidius stigmaticus. 496. Aphidius transcaspicus. 497. Aphidius uroleuci. 498. Aphidius urticae. 499. Aphidius uzbekistanicus.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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