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61 results for “20th century”
Online Data for 'The role of wildfires in the interplay of forest carbon stocks and wood harvest in the contiguous United States during the 20th century'
<p>This data file (.xlsx) contains all data used to create table 1, figures 1a-d, figure 2, figure S1, S2, and S5 of the study "The role of wildfires in the interplay of forest carbon stocks and wood harvest in the contiguous United States during the 20th century". Main article is available under: https://doi.org/10.1029/2023GB007813</p>
PARESv3 : PArish REgistry Survey − Historical Census Table Dataset (19th, 20th centuries) − France
<h2>PARES Dataset v3</h2> <p>PARES (PArish REcord Survey) contains<strong> 535 images of handwritten census tables</strong> for years ranging from around <strong>1650 A.D. until 1850 A.D.</strong>.They come from two <strong>French cities</strong>, Vic-sur-Seille (French department of Moselle) and Echevronne (French department of Côte d'Or). While they mention very ancient times, the documents are handwritten transcriptions of even older documents and are quite recent, copied from original documents during the 1950's and 1960's for demographic studies led by the INED in France (<em>Institut National des études démographiques</em> − National Institute for Demographic Studies). These copies were made by only a few different writers.</p> <p>In this updated version of the dataset, each table row has been carefully annotated and transcribed. Please note that for each row transcription, we have specified the attribute to which each value corresponds.</p> <p>We published a paper, <a href="https://link.springer.com/article/10.1007/s10032-025-00531-z">The PARES Database: Information Extraction over Historical Parish Records,</a> in which we better describe the dataset and the tasks it's possible to run on it.</p> <p> </p>
Cultures of Suntanning in late-19th to mid-20th century Britain
<p>Data collected in the project "Cultures of Suntanning in late 19th to mid-20th century Britain", British Academy Mid-Career Fellowship award number MCFSS22\220038.</p><p>Archive Dataset lists identifying details for all archive resources that were consulted during the project, with a note as to whether data was collected from each source.</p><p>Literary dataset lists identifying details for all literary resources consulted during the project, including digital concordances where used, with a note as to whether data was collected from each source.</p><p>The raw data collected cannot be made open access due to archive/copyright restrictions. The identifying details provide enough supplementary information for researchers to locate these resources.</p>
Patch metrics and landscape patterns of forest disturbances at the beginning of the 20th Century
<h1>Summary:</h1> <p>The database consists of a compressed .CSV file containing structural information of forest disturbance patches identified between 2002 and 2014 using the Global Forest Change Tree Cover Loss Year dataset version 1.6 (Hansen et al, 2013) available at https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.6.html. Each row in the database represents a patch (249,149,911 in total). The columns (15) represent the structural metrics calculated for each patch, as well as the landscape patterns identified using kmeans cluster analysis. </p> <p>The methods used for building this database are published in the paper: Acil, N., Sadler, J.P., Senf, C. <em>et al.</em> Landscape patterns in stand-replacing disturbances across the world’s forests. <em>Nat Sustain</em> <strong>8</strong>, 86–98 (2025). <a href="https://doi.org/10.1038/s41893-024-01450-3">https://doi.org/10.1038/s41893-024-01450-3</a></p> <p>Aggregated global maps of the patch metrics can be visualised in <a href="https://ee-treemort-disturbances-nacil.projects.earthengine.app/view/patchmetrics2002-2014">Google Earth Engine</a> and accessed in the asset "http://projects/ee-treemort-disturbances-nacil/assets/PatchMetrics_Means_nonLU_2002-2014/". </p> <p>Some of the scripts associated with this project are hosted in <a href="https://github.com/N-Acil/GlobalForestDisturbances_PatchMetrics">GitHub</a> and <a href="https://code.earthengine.google.com/?accept_repo=users/NXA807/%20GlobalForestDisturbances_PatchMetrics">Google Earth Engine</a>.</p> <p>Additional scripts and data will be made available upon request.</p> <p> </p> <p> </p> <h1>Database structure: </h1> <h2>Patch metrics</h2> <h3>Occurrence: </h3> <p>Patch form and year were retrieved from the Global Forest Change tree cover loss year dataset version 1.6 (Hansen et al, 2013).</p> <table> <tbody> <tr> <td><strong>Column name</strong></td> <td><strong>Description</strong></td> <td><strong>Unit</strong></td> <td><strong>Format</strong></td> <td><strong>Valid values</strong></td> </tr> <tr> <td><strong>PID</strong></td> <td>Patch unique identifier in the format Tile_Year_PatchNumber (e.g. 01U_02_00000001).</td> <td> </td> <td>Characters</td> <td> </td> </tr> <tr> <td><strong>X_INT_deg</strong></td> <td>Longitude of the patch's internal centroid</td> <td>Degrees</td> <td>Float</td> <td>[-180-180]</td> </tr> <tr> <td><strong>Y_INT_deg</strong></td> <td>Latitude of the patch's internal centroid</td> <td>Degrees</td> <td>Float</td> <td>[-90-90]</td> </tr> <tr> <td><strong>YEAR_maj</strong></td> <td>Year of patch majority occurrence. </td> <td> </td> <td>Integer</td> <td>[2-14]</td> </tr> <tr> <td><strong>YEAR_n</strong></td> <td>Number of years over which the patch exhibited continuous growth.</td> <td> </td> <td>Integer</td> <td>>0</td> </tr> </tbody> </table> <h3>Metrics: </h3> <p>These patch and landscape metrics were calculated from the patch delineated.</p> <table> <tbody> <tr> <td><strong>Column name</strong></td> <td><strong>Description</strong></td> <td><strong>Unit</strong></td> <td><strong>Format</strong></td> <td><strong>Valid values</strong></td> </tr> <tr> <td><strong>AREA_G_ha</strong></td> <td>Patch geodesic area</td> <td>Hectares</td> <td>Float</td> <td>>0</td> </tr> <tr> <td><strong>PERIM_G_m</strong></td> <td>Patch geodesic perimeter</td> <td>Meters</td> <td>Float</td> <td>>0</td> </tr> <tr> <td><strong>PARA</strong></td> <td>Perimeter-area ratio</td> <td> </td> <td>Float</td> <td>>0</td> </tr> <tr> <td><strong>SHAPE</strong></td> <td>Shape index</td> <td> </td> <td>Float</td> <td>>=1</td> </tr> <tr> <td><strong>ELONG</strong></td> <td>Elongation index</td> <td> </td> <td>Float</td> <td>[0-1[</td> </tr> <tr> <td><strong>FRAC</strong></td> <td>Fractal dimension index</td> <td> </td> <td>Float</td> <td>[1-2]</td> </tr> <tr> <td><strong>NN5000_T0_n</strong></td> <td>Number of patches assigned the same year within 5 km radius.</td> <td> </td> <td>Integer</td> <td>>0</td> </tr> <tr> <td><strong>NN5000_AREA_T0_perc</strong><strong><br></strong></td> <td>Percent of the total area disturbed over the period 2001-2018 within 5 km radius from the focal patch centroid.</td> <td>%</td> <td>Float</td> <td>[0-100]</td> </tr> </tbody> </table> <h3>Clusters:</h3> <p>Cluster identification was performed using AREA_G_ha, YEAR_n, SHAPE, ELONG, NN5000_T0_n and NN5000_AREA_T0_perc. </p> <table> <tbody> <tr> <td><strong>Column name</strong></td> <td><strong>Description</strong></td> <td><strong>Unit</strong></td> <td><strong>Format</strong></td> <td><strong>Valid values</strong></td> </tr> <tr> <td><strong>CLUSTER_CODE</strong></td> <td>Code assigned to each cluster</td> <td> </td> <td>Integer</td> <td>[1-4]</td> </tr> <tr> <td><strong>CLUSTER_LABEL</strong></td> <td>Name given to the cluster identified. </td> <td> </td> <td>Character</td> <td> <ul> <li>Small-isolated</li> <li>Clustered</li> <li>Complex</li> <li>Large-multiyear</li> </ul> </td> </tr> </tbody> </table> <p> </p>
Food riots and food prices in the Eastern Mediterranean (Bilād al-Shām) in the 19th and 20th centuries: a data set
<p>This is an archival release to document the state of the data set for this research project before it got severely derailed by the Covid-19 pandemic and the explosion in Beirut on 4 August 2020. Please consult the readme for a detailed description of the contents and workflows.</p>
MaMo online Webinar Cycle "Materializing Modernity - Landscape, Architecture and Anthropology intersections in 20th-century rurality"
<p>A dataset (WP2-B_Materials_1) containing the video recordings of the MaMo Webinar Cycle titled “Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality” held on the ZOOM platform in April and May 2021. Activity developed under the Work Package 2 (WP2), Secondment period at Università degli Studi di Milano (UNIMI), Italy. All the events have been organized by Dr Federica Pompejano (MSCA-IF Fellow) in collaboration with the Laboratory of Ethnomusicology and Visual Anthropology (LEAV) of the Department of Cultural and Environmental Heritage (UNIMI) and the Institute of Cultural Anthropology and Art Studies (IAKSA) of the Akademia e Studimeve Albanologjike (ASA), Tirana, Albania.</p> <p>WP2-B_Materials_1 (PART 1) - Contents</p> <ul> <li>Programme of the MaMo Webinar Cycle "Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality" held in April-May 2021 on ZOOM online platform</li> <li>Banner of the MaMo Webinar Cycle "Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality" held in April-May 2021 on ZOOM online platform</li> <li>1st meeting - Introduction: MaMo - an introduction to Albanian Socialist and Post-Socialist rurality by Federica Pompejano, MSCA-IF Fellow, Department of Ethnology, Institute of Cultural Anthropology and Art Studies (IAKSA), Academy of Albanian Studies, Albania<br> Oral presentation: "The Albanian Village as an anthropological encounter of modernity" by Nebi Bardhoshi, Associate Professor and Director of the Institute of Cultural Anthropology and Art Studies (IAKSA), Academy of Albanian Studies, and Olsi Lelaj, Researcher, Department of Ethnology, IAKSA, Academy of Albanian Studies, Albania</li> <li>MaMo Webinar Cycle - 1st meeting banner</li> <li>MaMo Webinar Cycle - 1st meeting poster with oral presentation abstract</li> <li>MaMo Webinar Cycle - 1st meeting poster with oral presenters short bio</li> <li>MaMo Webinar Cycle - 1st meeting Instagram post</li> <li>2nd meeting - Oral presentation: "Exploring Rurality in Southern Italy: the experience of 'Sonic Ethnography'" by Nicola Scaldaferri, Associate Professor, Department of Cultural and Environmental Heritage, Università Statale di Milano, Italy, and Lorenzo Ferrarini, Lecturer in Social and Visual Anthropology, Granada Centre for Visual Anthropology, University of Manchester, United Kingdom</li> <li>MaMo Webinar Cycle - 2nd meeting banner</li> <li>MaMo Webinar Cycle - 2nd meeting poster with oral presentation abstract</li> <li>MaMo Webinar Cycle - 2nd meeting poster with oral presenters short bio</li> <li>MaMo Webinar Cycle - 2nd meeting Instagram post</li> </ul>
MaMo Webinar Cycle "Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality" - Part 2
<p>A dataset (WP2-B_Materials_2) containing the video recordings of the MaMo Webinar Cycle titled “Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality” held on the ZOOM platform in April and May 2021. Activity developed under the Work Package 2 (WP2), Secondment period at Università degli Studi di Milano (UNIMI), Italy. All the events have been organized by Dr Federica Pompejano (MSCA-IF Fellow) in collaboration with the Laboratory of Ethnomusicology and Visual Anthropology (LEAV) of the Department of Cultural and Environmental Heritage (UNIMI) and the Institute of Cultural Anthropology and Art Studies (IAKSA) of the Akademia e Studimeve Albanologjike (ASA), Tirana, Albania.</p> <p>WP2-B_Materials_2 (PART 2) - Contents</p> <ul> <li>3rd meeting - Oral presentation 1: "Embedding the Past into Modernist Rural Landscapes" by Cristina Pallini, Associate Professor, Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Italy - Oral presentation 2: "Figures in a landscape: notes for a history of rural planning and village design in the Eastern bloc" by Axel Fischer, Associate Professor p.t., Université libre de Bruxelles, School of Architecture La Cambre Horta, hortence lab for architectural history, theory and criticism, Belgium (WP2-B_Webinar_03W.mpeg)</li> <li>MaMo Webinar Cycle - 3rd meeting banner (WP2-B_Webinar-03W_Banner.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting poster with oral presentation abstract - 1 (WP2-B_Webinar_03W-Poster1.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting poster with oral presentation abstract - 2 (WP2-B_Webinar_03W-Poster2.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting poster with oral presenters short bio (WP2-B_Webinar_03W-Poster3.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting Instagram post - 1 (WP2-B_Webinar_03W_IG1.jpg)</li> <li>MaMo Webinar Cycle - 3rd meeting Instagram post - 2 (WP2-B_Webinar_03W_IG2.jpg)</li> </ul>
MaMo Webinar Cycle "Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality" - Part 3
<p>A dataset (WP2-B_Materials_3) containing the video recordings of the MaMo Webinar Cycle titled “Materializing Modernity: Landscape, Architecture and Anthropology intersections in 20th-century rurality” held on the ZOOM platform in April and May 2021. Activity developed under the Work Package 2 (WP2), Secondment period at Università degli Studi di Milano (UNIMI), Italy. All the events have been organized by Dr Federica Pompejano (MSCA-IF Fellow) in collaboration with the Laboratory of Ethnomusicology and Visual Anthropology (LEAV) of the Department of Cultural and Environmental Heritage (UNIMI) and the Institute of Cultural Anthropology and Art Studies (IAKSA) of the Akademia e Studimeve Albanologjike (ASA), Tirana, Albania.</p> <p>WP2-B_Materials_3 (PART 3) - Contents</p> <ul> <li>4th meeting - Oral presentation: "Concepts integrated conservation as inroads to sustainable management of cultural landscapes" by Bosse Lagerqvist, Associate Professor and Senior Lecturer, Department of Conservation, Göteborgs Universitet, Sweden (WP2-B_Webinar_04W.mpeg)</li> <li>MaMo Webinar Cycle - 4th meeting banner (WP2-B_Webinar_04W_Banner.jpg)</li> <li>MaMo Webinar Cycle - 4th meeting poster with oral presentation abstract (WP2-B_Webinar_04W_Poster1.jpg)</li> <li>MaMo Webinar Cycle - 4th meeting poster with oral presenter short bio (WP2-B_Webinar_04W_Poster2.jpg)</li> <li>MaMo Webinar Cycle - 4th meeting Instagram post (WP2-B_Webinar_04W_IG.jpg)</li> <li>5th meeting - Oral presentation: "Socialist Modernism in the former Eastern Bloc (1955-1991), The Socialist Modernism map at socialistmodernism.com" by Dumitru Rusu, President of B.A.C.U. Association - Birou pentru Art si Cercetare Urbană (Bureau for Art and Urban Research), Romania (WP2-B_Webinar_05W.mpeg)</li> <li>MaMo Webinar Cycle - 5th meeting banner (WP2-B_Webinar_05W_Banner.jpg)</li> <li>MaMo Webinar Cycle - 5th meeting poster with oral presentation abstract (WP2-B_Webinar_05W_Poster1.jpg)</li> <li>MaMo Webinar Cycle - 5th meeting poster with oral presenter short bio (WP2-B_Webinar_05W_Poster2.jpg)</li> <li>MaMo Webinar Cycle - 5th meeting Instagram post (WP2-B_Webinar_05W_IG.jpg)</li> </ul>
Particle tracking dataset for: Exceptional 20th century ocean circulation in the Northeast Atlantic
<p>Particle tracking data for: "Exceptional 20th century ocean circulation in the Northeast Atlantic" Peter T. Spooner, David J. R. Thornalley, Delia W. Oppo, Alan Fox, Svetlana Radionovskaya, Neil L. Rose, Robbie Mallett, Emma Cooper, J. Murray Roberts</p> <p>VIKING20 (is a 1/20th degree ocean model, forced by a hindcast simulation of the atmosphere: CORE2 (Griffies et al., 2009). The reverse tracks of 113200 particles per year for 50 years, (1959-2009) were simulated with the ARIANE software (Döös, 1995) modified to include independent vertical motion of particles. Particles were seeded at the seabed in 10 km x 10 km boxes centered on MC16-A/17-5P and RAPID-21-3K (representing the settling location). The reverse tracks 'rose' (sinking) at 100 m/day (Takahashi & Be, 1984) and were then allowed to drift freely within the upper 100 m of the water column for six months (i.e. spanning the reasonable lifespan for many species of planktic foraminifera).</p> <p>Track data for the full 50 years are stored in a single netcdf file (output of ncdump -h <filename> given below). The 3D particle positions are in variables traj_lon, traj_lat and traj_depth with the Viking20 model along-track temperature, salinity and density in traj_temp, temp_sal and traj_dens, respectively. The main complication is the obscure storage of time (see also ARIANE software documentation). Variable init_t gives particle start time, counting in 5-day periods from 12:00 pm on 29 December 1957. Viking20 uses a fixed 365 day year so the year can be found for track 'traj' according to:</p> <p> year = 1958 + ( (init_t(traj)-1) \ 73 ) where '\' represents integer division, discarding the remainder.</p> <p>All particle tracks 'begin' (actually the end of the track in time as these are tracked backwards) at the start of July (12:00 pm July 1 in model). Particles are ordered by release time, so trajectories 1-113200 are 1959; 113201-226400 are 1960; etc. Positions are stored every 5 days, counting backwards.</p> <p>Further details are available from the authors.</p> <p> </p> <p>References</p> <p>Döös, K. (1995). Interocean exchange of water masses. Journal of Geophysical Research, 100(C7), 13499. <a href="https://doi.org/10.1029/95JC00337">https://doi.org/10.1029/95JC00337</a></p> <p>Griffies, S. M., Biastoch, A., Böning, C., Bryan, F., Danabasoglu, G., Chassignet, E. P., et al. (2009). Coordinated Ocean-ice Reference Experiments (COREs). Ocean Modelling, 26(1–2), 1–46. <a href="https://doi.org/10.1016/J.OCEMOD.2008.08.007">https://doi.org/10.1016/J.OCEMOD.2008.08.007</a></p> <p>Takahashi, K., & Be, A. W. H. (1984). Planktonic foraminifera: factors controlling sinking speeds. Deep Sea Research Part A. Oceanographic Research Papers, 31(12), 1477–1500. <a href="https://doi.org/10.1016/0198-0149(84)90083-9">https://doi.org/10.1016/0198-0149(84)90083-9</a></p> <p> </p> <p>$ ncdump -h ariane_trajectories_qualitative.nc</p> <p>netcdf ariane_trajectories_qualitative {</p> <p>dimensions:</p> <p>ntraj = 5660000 ;</p> <p>nb_output = UNLIMITED ; // (74 currently)</p> <p>variables:</p> <p><strong>double init_x(ntraj) ;</strong></p> <p>init_x:title = "What is init_x ?" ;</p> <p>init_x:longname = "Initial position in i" ;</p> <p>init_x:units = "No dimension" ;</p> <p>init_x:missing_value = 1.e+20 ;</p> <p><strong>double init_y(ntraj) ;</strong></p> <p>init_y:title = "What is init_y ?" ;</p> <p>init_y:longname = "Initial position in j" ;</p> <p>init_y:units = "No dimension" ;</p> <p>init_y:missing_value = 1.e+20 ;</p> <p><strong>double init_z(ntraj) ;</strong></p> <p>init_z:title = "What is init_z ?" ;</p> <p>init_z:longname = "Initial position in k" ;</p> <p>init_z:units = "No dimension" ;</p> <p>init_z:missing_value = 1.e+20 ;</p> <p><strong>double init_t(ntraj) ;</strong></p> <p>init_t:title = "What is init_t ?" ;</p> <p>init_t:longname = "Initial position in l (time)" ;</p> <p>init_t:units = "See global attributes..." ;</p> <p>init_t:missing_value = 1.e+20 ;</p> <p><strong>double init_age(ntraj) ;</strong></p> <p>init_age:title = "What is init_age ?" ;</p> <p>init_age:longname = "Initial age (time)" ;</p> <p>init_age:units = "seconds" ;</p> <p>init_age:missing_value = 1.e+20 ;</p> <p><strong>double init_transp(ntraj) ;</strong></p> <p>init_transp:title = "What is init_transp ?" ;</p> <p>init_transp:longname = "Initial transport" ;</p> <p>init_transp:units = "m3/s" ;</p> <p>init_transp:missing_value = 1.e+20 ;</p> <p><strong>double l_matureage(ntraj) ;</strong></p> <p>l_matureage:title = "What is l_matureage ?" ;</p> <p>l_matureage:longname = "Larval age of maturity" ;</p> <p>l_matureage:units = "days" ;</p> <p>l_matureage:missing_value = 1.e+20 ;</p> <p><strong>double l_descendage(ntraj) ;</strong></p> <p>l_descendage:title = "What is l_descendage ?" ;</p> <p>l_descendage:longname = "Larval age of competency" ;</p> <p>l_descendage:units = "days" ;</p> <p>l_descendage:missing_value = 1.e+20 ;</p> <p><strong>double l_maxspeedup(ntraj) ;</strong></p> <p>l_maxspeedup:title = "What is l_maxspeedup ?" ;</p> <p>l_maxspeedup:longname = "Max upward larval swim speed" ;</p> <p>l_maxspeedup:units = "mm s-1" ;</p> <p>l_maxspeedup:missing_value = 1.e+20 ;</p> <p><strong>double l_maxspeeddown(ntraj) ;</strong></p> <p>l_maxspeeddown:title = "What is l_maxspeeddown ?" ;</p> <p>l_maxspeeddown:longname = "Max downward larval swim speed" ;</p> <p>l_maxspeeddown:units = "mm s-1" ;</p> <p>l_maxspeeddown:missing_value = 1.e+20 ;</p> <p><strong>int l_targetdepth(ntraj) ;</strong></p> <p>l_targetdepth:title = "What is l_targetdepth ?" ;</p> <p>l_targetdepth:longname = "Target shallow depth" ;</p> <p>l_targetdepth:units = "No dimension" ;</p> <p>l_targetdepth:missing_value = -1. ;</p> <p><strong>double final_x(ntraj) ;</strong></p> <p>final_x:title = "What is final_x ?" ;</p> <p>final_x:longname = "Final position in x (or i)" ;</p> <p>final_x:units = "No dimension" ;</p> <p>final_x:missing_value = 1.e+20 ;</p> <p><strong>double final_y(ntraj) ;</strong></p> <p>final_y:title = "What is final_y ?" ;</p> <p>final_y:longname = "Final position in y (or j)" ;</p> <p>final_y:units = "No dimension" ;</p> <p>final_y:missing_value = 1.e+20 ;</p> <p><strong>double final_z(ntraj) </strong>;</p> <p>final_z:title = "What is final_z ?" ;</p> <p>final_z:longname = "Final position in z (or k)" ;</p> <p>final_z:units = "No dimension" ;</p> <p>final_z:missing_value = 1.e+20 ;</p> <p><strong>double final_t(ntraj) ;</strong></p> <p>final_t:title = "What is final_t ?" ;</p> <p>final_t:longname = "Final position in t (time)" ;</p> <p>final_t:units = "See global attributes..." ;</p> <p>final_t:missing_value = 1.e+20 ;</p> <p><strong>double final_age(ntraj) ;</strong></p> <p>final_age:title = "What is fial_age ?" ;</p> <p>final_age:longname = "Final Age." ;</p> <p>final_age:units = "seconds" ;</p> <p>final_age:missing_value = 1.e+20 ;</p> <p><strong>double final_transp(ntraj) ;</strong></p> <p>final_transp:title = "What is final_transp ?" ;</p> <p>final_transp:longname = "Final transport" ;</p> <p>final_transp:units = "m3/s" ;</p> <p>final_transp:missing_value = 1.e+20 ;</p> <p><strong>float traj_lon(nb_output, ntraj) ;</strong></p> <p>traj_lon:title = "What is traj_lon ?" ;</p> <p>traj_lon:longname = "Trajectory: x positions" ;</p> <p>traj_lon:units = "No dimension" ;</p> <p>traj_lon:missing_value = 1.e+20 ;</p> <p><strong>float traj_lat(nb_output, ntraj) ;</strong></p> <p>traj_lat:title = "What is traj_lat ?" ;</p> <p>traj_lat:longname = "Trajectory: y positions" ;</p> <p>traj_lat:units = "No dimension" ;</p> <p>traj_lat:missing_value = 1.e+20 ;</p> <p><strong>float traj_depth(nb_output, ntraj) ;</strong></p> <p>traj_depth:title = "What is traj_depth ?" ;</p> <p>traj_depth:longname = "Trajectory: z positions" ;</p> <p>traj_depth:units = "No dimension" ;</p> <p>traj_depth:missing_value = 1.e+20 ;</p> <p><strong>float traj_time(nb_output, ntraj) ;</strong></p> <p>traj_time:title = "What is traj_time ?" ;</p> <p>traj_time:longname = "Trajectory: time positions" ;</p> <p>traj_time:units = "See global attributes" ;</p> <p>traj_time:missing_value = 1.e+20 ;</p> <p><strong>float traj_iU(nb_output, ntraj) ;</strong></p> <p>traj_iU:title = "ind i on grid U" ;</p> <p>traj_iU:longname = "Trajectory: i on grid U" ;</p> <p>traj_iU:units = "No dimension" ;</p> <p>traj_iU:missing_value = 1.e+20 ;</p> <p><strong>float traj_jV(nb_output, ntraj) ;</strong></p> <p>traj_jV:title = "ind j on grid V" ;</p> <p>traj_jV:longname = "Trajectory: j on grid V" ;</p> <p>traj_jV:units = "No dimension" ;</p> <p>traj_jV:missing_value = 1.e+20 ;</p> <p><strong>float traj_kW(nb_output, ntraj) ;</strong></p> <p>traj_kW:title = "ind k on grid W" ;</p> <p>traj_kW:longname = "Trajectory: k on grid W" ;</p> <p>traj_kW:units = "No dimension" ;</p> <p>traj_kW:missing_value = 1.e+20 ;</p> <p><strong>float traj_temp(nb_output, ntraj) ;</strong></p> <p>traj_temp:title = "What is traj_temp ?" ;</p> <p>traj_temp:longname = "Trajectory: temperatures" ;</p> <p>traj_temp:units = "degres" ;</p> <p>traj_temp:missing_value = 1.e+20 ;</p> <p><strong>float traj_salt(nb_output, ntraj) ;</strong></p> <p>traj_salt:title = "What is traj_salt ?" ;</p> <p>traj_salt:longname = "Trajectory: salinities" ;</p> <p>traj_salt:units = "psu" ;</p> <p>traj_salt:missing_value = 1.e+20 ;</p> <p><strong>float traj_dens(nb_output, ntraj) ;</strong></p> <p>traj_dens:title = "What is traj_dens ?" ;</p> <p>traj_dens:longname = "Trajectory: densities" ;</p> <p>traj_dens:units = "..." ;</p> <p>traj_dens:missing_value = 1.e+20 ;</p> <p> </p> <p>// global attributes:</p> <p>:key_roms = ".FALSE." ;</p> <p>:key_symphonie = ".FALSE." ;</p> <p>:key_B2C_grid = ".FALSE." ;</p> <p>:key_sequential = ".TRUE." ;</p> <p>:key_alltracers = ".TRUE." ;</p> <p>:key_ascii_outputs = ".FALSE." ;</p> <p>:key_iU_jV_kW = ".TRUE." ;</p> <p>:key_read_age = ".FALSE." ;</p> <p>:mode = "qualitative" ;</p> <p>:forback = "backward" ;</p> <p>:bin = "nobin" ;</p> <p>:init_final = "NONE" ;</p> <p>:nmax = 10000000 ;</p> <p>:tunit = 86400. ;</p> <p>:ntfic = 5 ;</p> <p>:tcyc = 1639872000. ;</p> <p>:key_approximatesigma = ".FALSE." ;</p> <p>:key_computesigma = ".TRUE." ;</p> <p>:zsigma = 1000. ;</p> <p>:memory_log = ".TRUE." ;</p> <p>:output_netcdf_large_file = ".FALSE." ;</p> <p>:key_interp_temporal = ".TRUE." ;</p> <p>:maxcycles = 50 ;</p> <p>:delta_t = 86400. ;</p> <p>:frequency = 5 ;</p> <p>:nb_output = 73 ;</p> <p>:mask = ".TRUE." ;</p> <p>:key_region = ".FALSE." ;</p> <p>:key_larvae = ".TRUE." ;</p> <p>:imt = 1784 ;</p> <p>:jmt = 1719 ;</p> <p>:kmt = 46 ;</p> <p>:lmt = 3796 ;</p> <p>:key_computew = ".TRUE." ;</p> <p>:w_surf_option = "" ;</p> <p>:key_partialsteps = ".TRUE." ;</p> <p>:key_jfold = ".FALSE." ;</p> <p>:pivot = "T" ;</p> <p>:key_periodic = ".FALSE." ;</p> <p>:dir_mesh = "./GRID" ;</p> <p>:fn_mesh = "1_mesh_mask.nc" ;</p> <p>:nc_var_xx_tt = "glamt" ;</p> <p>:nc_var_xx_uu = "glamu" ;</p> <p>:nc_var_zz_ww = "gdepw_0" ;</p> <p>:nc_var_e2u = "e2u" ;</p> <p>:nc_var_e1v = "e1v" ;</p> <p>:nc_var_e1t = "e1t" ;</p> <p>:nc_var_e2t = "e2t" ;</p> <p>:nc_var_e3t = "e3t" ;</p> <p>:nc_var_tmask = "tmask" ;</p> <p>:nc_mask_val = 0. ;</p> <p>:c_dir_zo = "./DATA" ;</p> <p>:c_prefix_zo = "V20_nest_5d_" ;</p> <p>:ind0_zo = 1958 ;</p> <p>:indn_zo = 2009 ;</p> <p>:maxsize_zo = 4 ;</p> <p>:c_suffix_zo = "_U.nc" ;</p> <p>:nc_var_zo = "vozocrtx" ;</p> <p>:nc_var_eivu = "NONE" ;</p> <p>:nc_att_mask_zo = "missing_value" ;</p> <p>:c_dir_me = "./DATA" ;</p> <p>:c_prefix_me = "V20_nest_5d_" ;</p> <p>:ind0_me = 1958 ;</p> <p>:indn_me = 2009 ;</p> <p>:maxsize_me = 4 ;</p> <p>:c_suffix_me = "_V.nc" ;</p> <p>:nc_var_me = "vomecrty" ;</p> <p>:nc_var_eivv = "NONE" ;</p> <p>:nc_att_mask_me = "missing_value" ;</p> <p>:c_dir_te = "./DATA" ;</p> <p>:c_prefix_te = "V20_nest_5d_" ;</p> <p>:ind0_te = 1958 ;</p> <p>:indn_te = 2009 ;</p> <p>:maxsize_te = 4 ;</p> <p>:c_suffix_te = "_T.nc" ;</p> <p>:nc_var_te = "votemper" ;</p> <p>:nc_att_mask_te = "missing_value" ;</p> <p>:c_dir_sa = "./DATA" ;</p> <p>:c_prefix_sa = "V20_nest_5d_" ;</p> <p>:ind0_sa = 1958 ;</p> <p>:indn_sa = 2009 ;</p> <p>:maxsize_sa = 4 ;</p> <p>:c_suffix_sa = "_T.nc" ;</p> <p>:nc_var_sa = "vosaline" ;</p> <p>:nc_att_mask_sa = "missing_value" ;</p> <p>}</p> <p> </p>
Macroseismic intensity data points for shallow 20th century earthquakes in the Hainaut coal area and the 1983 Liège earthquake (Belgium)
<p>This dataset contains macroseismic data points and source parameters for 28 shallow 20th-century earthquakes in the Hainaut area, as well as for the 1983-11-08 Liège earthquake, all in Belgium. For each earthquake, there is 1 CSV-file containing minimum and maximum evaluated macroseismic intensity, latitude, longitude, commune name, epicentral distance and azimuth. The source parameters (origin time, epicentral coordinates, hypocentral depth, magnitude, maximum intensity, macroseismic radius and number of observations) are listed in a XLSX file. The ID_EARTH column in this file corresponds to the first part of the CSV filenames.<br>The most significant difference with respect to the original dataset is an update of the coordinates of several Belgian localities that are used to locate the IDPs, resulting mainly in insignificant changes (<1 km difference for 96% of the IDPs used here), but a few outliers up to a difference of 22 km occur as well. This can result in significantly higher or lower epicentral distances for a few IDPs. Other adjustments to the data include the addition of intensity 1 values (not felt) and the removal, addition or modification of some IDPs (>20 IDPs in total). For the 1983 Liège earthquake (ID_EARTH=651), more significant changes were made to the IDP dataset as part of a major update of the ROB traditional macroseismic database, such as the addition of 297 new IDPs (~90% not felt), the modification of intensity values of 19 IDPs and the removal of 3 IDPs that were previously assigned to the wrong municipality.</p>
Word2Vec Models built from a Collection of French 20th-Century Novels
<p>The models were trained using the Gensim library for Python, developed by Radim Rehurek, in 2017. All models are based on the same collection of 20th century French novels that covers the period from 1900 to 2010, with a large range of authors and genres respresented. The collection contains approximately 1,200 novels and about 60 million tokens.</p> <p>The models were created using the SGNS (Skip-Gram with Negative Sampling) architecture, the context window was always of size of 6 + 6 around the target word, and the texts were lemmatised and POS-tagged beforehand. POS-Tags remain attached to each token (as in "souris_nom"). Other parameters vary by model: some have 200, some have 300 dimensional vectors; the minimum frequency of the words in the model varies with values of 50, 100 and 200, something which influences the size of the vocabulary and the size of the model. </p>
Data for: Repeatability of the 20th Century Earthquake Cluster in Mongolia: Paleoseismology along the Tsetserleg Fault (Mongolia)
<p>This dataset is associated to the article "Repeatability of the 20<sup>th</sup> Century Earthquake Cluster in Mongolia: Paleoseismology along the Tsetserleg Fault (Mongolia)" submitted to Journal of Geophysical Research: Solid Earth.</p> <p>It includes the following:</p> <ul> <li>Dataset S1 includes the output of the horizontal offset measurements performed with the LaDiCaOz Matlab GUI.</li> <li>Dataset S2 includes the drone DEMs.</li> </ul>
20th Century Press Archives JSON-LD dump for CdV 2018 Rhein-Main: persons and companies
<p>Folder metadata for all person and company folders of PM20, which have publicly accessible documents. Published for the "Coding da Vinci" Hackathon 2018.</p> <p>For a preview and further information, please see https://github.com/zbw/cdv2018-pressemappe20 (mostly in German)</p> <p> </p>
Southern Hemisphere winds, pressure, and temperature over the 20th century from proxy-data assimilation
<p>This archive contains four reconstructions of annually resolved zonal surface wind (us), sea level pressure (psl), and surface temperature (tas) anomalies in the Southern Hemisphere over the period 1900 to 2005 CE. The anomaly reference period is 1961-1990. </p> <p>The reconstructions are generated using the Last Millennium Reanalysis data assimilation framework (Hakim et al., 2016; Tardif et al., 2019). The proxies assimilated come from a global database comprising the PAGES2k database (PAGES2k Consortium, 2017), additional ice core accumulation records (Thomas et al., 2017), and additional coral records (Sanchez et al., 2021). We use four climate models to produce the four reconstructions:</p> <ol> <li>the iCESM Last Millennium Ensemble (“CESM LM”, Brady et al., 2019, Stevenson et al., 2019)</li> <li>the HadCM3 Last Millennium Ensemble (“HadCM3 LM”, Collins et al., 2001)</li> <li>the CESM1 Large Ensemble (“LENS”; Kay et al., 2015)</li> <li>the CESM1 Pacific Pacemaker Ensemble (“PACE”; Schneider and Deser, 2018).</li> </ol> <p>The four reconstructions are named after the prior that is used. The last millennium ensemble of simulations include natural forcings only and the LENS and PACE ensemble of simulations include historical external forcings. For each reconstruction, there are three netCDF files containing the ensemble mean (mean of 100 ensemble members) for each climate field. More details can be found in O'Connor et al. (2021).</p> <p>Please cite O'Connor et al. (2021) when using these datasets. <a href="https://doi.org/10.1029/2021GL095999">https://doi.org/10.1029/2021GL095999</a></p>
Animated E3SM V1 High Resolution Labrador Sea Ice Thickness and Concentration with mid-20th Century Atmospheric Constituents
<p>This animated GIF file visualizes daily grid-cell mean sea ice thickness and concentration for the Labrador Sea region from version 1 of the Energy Exascale Earth System Model (E3SM) using 25km Atmosphere/Land and 8-16km Sea Ice-Ocean resolutions as described in the manuscript "The DOE E3SM coupled model version 1: Description 1 and results at high resolution". River routing is resolved at 0.125˚. This fully coupled simulation was spun-up for 6 years, and then proceeded for 50 subsequent years using HighResMIP protocols for continuuous 1950s atmospheric constituents. This animation shows sea thickness evolution in each frame for five model years 46 to 50, inclusive, with rendered transparency determined from sea ice concentration to demonstrate the influence of ocean eddies around the southern tip of Greenland. The coastline is the true model boundary. The animation is best viewed using a web browser.</p>
Animated E3SM V1 High Resolution Full Coupled Sea Ice Thickness and Extent with mid-20th Century Atmospheric Constituents
<p>This animated GIF file visualizes daily grid-cell mean sea ice thickness from version 1 of the Energy Exascale Earth System Model (E3SM) using 25km Atmosphere/Land and 8-16km Sea Ice-Ocean resolutions as described in the manuscript "The DOE E3SM coupled mo del version 1: Description 1 and results at high resolution". River routing is resolved at 0.125˚. This fully coupled simulation was spun-up for 6 years, and then proceeded for 50 subsequent years using HighResMIP protocols for continuuous 1950s atmospheric constituents. The animation shows both pan-Arctic and Southern Ocean daily sea thickness evolution in each frame for model years 46 to 55, truncated at 15% sea ice concentration, and is best viewed from within a web browser.</p>
Animated E3SM V1 High Resolution Mertz Polynya Sea Ice Thickness and Concentration with mid-20th Century Atmospheric Constituents
<p>This animated GIF file visualizes daily grid-cell mean sea ice thickness and concentration for the Mertz Glacier Polynya region of the East Antarctic coast from version 1 of the Energy Exascale Earth System Model (E3SM) using 25km Atmosphere/Land and 8-16km Sea Ice-Ocean resolutions as described in the manuscript "The DOE E3SM coupled model version 1: Description 1 and results at high resolution". River routing is resolved at 0.125˚. This fully coupled simulation was spun-up for 6 years, and then proceeded for 50 subsequent years using HighResMIP protocols for continuuous 1950s atmospheric constituents. This animation shows sea thickness evolution in each frame for ten model years 46 to 55, inclusive, with shading transparency determined by sea ice concentration, and grid cell outlines dissappearing where there is less than 0.1% sea ice concentration. The coastline is the true model boundary. This animation is best viewed using a web browser.</p>
Dataset - "Ice core evidence for a 20th century increase in surface mass balance in coastal Dronning Maud Land, East Antarctica"
<p>We provide in this dataset the isotopic and ionic records from a 120 m-long ice core drilled at the summit of Derwael ice rise (70°14'44.88'' S, 26°20'5.64'' E) situated in coastal Dronning Maud Land, East Antarctica. Ions concentrations (Na<sup>+</sup>, MSA, Cl<sup>-</sup>, SO<sub>4</sub><sup>2-</sup> and NO<sub>3</sub><sup>-</sup>) and water stable isotopes (δ<sup>18</sup>O, δD and d-excess) are presented for the top 103 meters (corresponding to 1815 and the Tambora eruption) with a continuous record for the water stable isotopes and discontinuous sections for ions concentrations. A complementary database “Annual layer thicknesses and age-depth (oldest estimate) of Derwael Ice Rise (IC12), Dronning Maud Land, East Antarctica” with age model and annual layer thickness is available at https://doi.org/10.1594/PANGAEA.857574 and the companion paper is Philippe et al., 2016 (“Ice core evidence for a 20th century increase in surface mass balance in coastal Dronning Maud Land, East Antarctica”, https://doi.org/10.5194/tc-10-2501-2016).</p>
20th Century Atmospheric River Archive for Western North America and Europe
<p><strong>General Description</strong></p> <p>This datasets provides 6-hourly instantaneous atmospheric river absence-presence time series for 13 sub-regions along the coastlines of Western North America and Europe, as well the corresponding Integrated Water Vapor (IVT) values and exceeded climatological quantiles. These data were retrieved from 3 distinct reanalyses:</p> <p>1. ERA-20C, 1900-2010, 1.125 degrees resolution, here termed "era20c"</p> <p>2. NOAA-CIRES 20th Century Reanalysis version 2, 1900-2012, 2 degrees resolution, here termed "c20", ARs were retrieved from instantaneous ensemble-mean data.</p> <p>3. ECMWF ERA-Interim, 1979-2014, 0.75 degrees resolution, here termed "interim"</p> <p>The file structure is as in this example:</p> <p>ar_Brands_v0_interim_scalifornia_JFMAOND_1979_2014.nc</p> <p>translates to:</p> <p>ar_<algorithm name>_<version>_<underlying dataset>_<target region as illustrated in fig_studyregions.pdf>_<considered months>_<start year>_<end_year>.nc</p> <p>The 13 study regions are indicated in <fig_studyregions.pdf> attached below and described in Brands et al. (2017). The lat-lon coordinates of each region are provided in the netCDF files.</p> <p>For western North America and Europe the October-through-April and October-through-March season is covered, respectively. The compressed netCDF4 files offered here come with detailed metadata information. For generating the present dataset, the initial version of the AR detection and tracking algorithm developed in my PhD thesis was used (here referred to as version 0, see Brands et al. 2017 for a full description). Although newer algorithm versions have become available in the framework of the Atmospheric River Method Intercomparison Project (ARTMIP, see Rutz et al. 2019), the initial version 0 was specifically developed for detecting landfalling ARs along the coastlines of Western North America and Europe. The correct functioning was supervised by eye for hundreds, if not thousands of cases.</p> <p>The 9 distinct AR detection and tracking methods contained in each netCDF file (coined "method 0,1...8" in there) use distinct climatological percentile thresholds to 1) detect ARs along the coastline (the detection percentile, termed "prct_detect") and then "crawl" upwards the flow guided by the strongest IVT above the tracking percentile ("prct_track") and by the respective U and V components until a minimum length of 2000 km is reached. The results obtained from the 9 methods thus differ in AR intensity.</p> <p>The netCDF files of the present dataset have been recompiled from the non-standard .mat files generated in my PhD thesis during the years 2013-2017. For the target regions in Europe, the content of the present dataset partly overlaps with the non-standard dataset previously published at http://dx.doi.org/10.13140/RG.2.2.14711.32160. The target regions in western North America have been newly included and are only available from the present dataset.</p> <p>Contact: Swen Brands, brandssf@ifca.unican.es</p> <p> </p> <p><strong>References</strong></p> <p>Brands, S., Gutiérrez, J.M. & San-Martín, D. (2017). Twentieth-century atmospheric river activity along the west coasts of Europe and North America: algorithm formulation, reanalysis uncertainty and links to atmospheric circulation patterns. <em>Climate Dynamics</em> 48, 2771–2795. https://doi.org/10.1007/s00382-016-3095-6</p> <p>Compo, G.P., Whitaker, J.S., Sardeshmukh, P.D., Matsui, N., Allan, R.J., Yin, X., Gleason, B.E., Vose, R.S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R.I., Grant, A.N., Groisman, P.Y., Jones, P.D., Kruk, M.C., Kruger, A.C., Marshall, G.J., Maugeri, M., Mok, H.Y., Nordli, Ø., Ross, T.F., Trigo, R.M., Wang, X.L., Woodruff, S.D. and Worley, S.J. (2011), The Twentieth Century Reanalysis Project. <em>Q.J.R. Meteorol. Soc.</em>, 137: 1-28, https://doi.org/10.1002/qj.776</p> <p>Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S.B., Hersbach, H., Hólm, E.V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A.P., Monge-Sanz, B.M., Morcrette, J.-.-J., Park, B.-.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. <em>Q.J.R. Meteorol. Soc.</em>, 137: 553-597, https://doi.org/10.1002/qj.828</p> <p>Poli, P., and Coauthors, 2016: ERA-20C: An Atmospheric Reanalysis of the Twentieth Century. <em>J. Climate</em>, 29, 4083–4097, https://doi.org/10.1175/JCLI-D-15-0556.1</p> <p>Rutz, J. J., Shields, C. A., Lora, J. M., Payne, A. E., Guan, B., Ullrich, P., et al. (2019). The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying uncertainties in atmospheric river climatology. <em>Journal of Geophysical Research: Atmospheres</em>, 2019; 124: 13777– 13802. https://doi.org/10.1029/2019JD030936</p>
Assessing seasonal richness of active flowers throughout UC Reserve sites in the 20th Century
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