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1,117 results for “1980”
Santa Barbara Channel Marine BON: Nearshore kelp forest integrated benthic cover, 1980-ongoing
The Santa Barbara Channel Marine Biodiversity Observation Network (SBCMBON) tracks long-term patterns in species abundance and diversity. This dataset contains cover of kelp forest sessile invertebrates, understory macroalgae, and substrate types by integrating data from four contributing projects working in the kelp forests of the Santa Barbara Channel, USA. Divers collect data on using either uniform point contact (UPC) or random point contact (RPC) methods. The four contributing projects are two research projects: The Santa Barbara Coastal LTER (SBC LTER) and the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO), the kelp forest monitoring program of the Santa Barbara Channel National Park, and the San Nicolas Island monitoring program supported by USGS. Together, these projects have recorded data for more than 200 species at approximately 100 sites on both the mainland coast and on the Santa Barbara Channel Islands. Sampling began in 1982 and is ongoing. Data were collected by human observation (divers using SCUBA) during regular surveys. Percent cover is recorded for taxa where individuals cannot be counted. Cover can be calculated from the data here as the fraction of total points at which the taxon was present x 100. With UPC and RPC methods, multiple species can be recorded at any given point. The total percent cover of all species combined using this method can exceed 100%; however, the percent cover of any single species cannot exceed 100%. See Methods for information on integration and data processing. MBON is funded by National Aeronautics and Space Administration (NASA), Bureau of Ocean Energy Management (BOEM), and National Oceanic and Atmospheric Administration (NOAA). For users who are interested in using all or part of this integrated datasets, please contact data owners to discuss your research interests, data-related issues or any other questions. A recommended citation for the data package is available from the download page. In
Santa Barbara Channel Marine BON: Nearshore kelp forest integrated quad and swath survey, 1980-ongoing
The Santa Barbara Channel Marine Biodiversity Observation Network (SBCMBON) tracks long-term patterns in species abundance and diversity. This dataset contains counts of algae and invertebrates (both sessile and mobile) by integrating data from four contributing projects working in the kelp forests of the Santa Barbara Channel, USA. The four contributing projects are two research projects: The Santa Barbara Coastal LTER (SBC LTER) and the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO), the kelp forest monitoring program of the Santa Barbara Channel National Park, and the San Nicolas Island monitoring program supported by USGS. Together, these projects have recorded data for more than 200 species at approximately 100 sites on both the mainland coast and on the Santa Barbara Channel Islands. Sampling began in 1982 and is ongoing. Data were collected by human observation (divers using SCUBA) during regular surveys. The data table documents the number of organisms and the area over which that number was counted for calculation of areal abundance. Data were collected by human observation (divers using SCUBA) during regular surveys. The algae and invertebrate counts record the number of taxa found in each plot, including quad (small square plots such as 1 or 2 m2) and swath (large linear plots such as 60 m2). See Method and protocol for information on integration and data processing. MBON is funded by National Aeronautics and Space Administration (NASA), Bureau of Ocean Energy Management (BOEM), and National Oceanic and Atmospheric Administration (NOAA). For users who are interested in using all or part of this integrated datasets, please contact data owners to discuss your research interests, data-related issues or any other questions. A recommended citation for the data package is available from the download page. In addition, any manuscript generated using this dataset is expected to be sent to the data owners before publication so we can be sure t
Santa Barbara Channel Marine BON: Nearshore kelp forest integrated taxa, 1980-ongoing
The Santa Barbara Channel Marine Biodiversity Network (SBC MBON) tracks long-term patterns in species abundance and diversity. By integrating research and monitoring efforts (both existing and de novo data), we provide a comprehensive view of biodiversity in the region. This dataset is a combined species list from four datasets currently handled and integrated by SBC MBON, with identifiers from an appropriate taxonomic registry included for each taxon. Because this species list reflects the integration of multiple collections, it will be updated as SBC MBON integration efforts develop. Santa Barbara Channel Marine BON: Integrated kelp forest/reef: Fish https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=5&revision=newest Santa Barbara Channel Marine BON: Integrated kelp forest/reef: Quad and swath cover https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=6&revision=newest Santa Barbara Channel Marine BON: Integrated kelp forest/reef: Benthic cover https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=3&revision=newest As of 2018, this dataset contains approximately 400 taxa from combined observations beginning in 1980. Data include codes for the originating project and sampling method, plus basic taxonomic lineage. MBON is funded by National Aeronautics and Space Administration (NASA), Bureau of Ocean Energy Management (BOEM), and National Oceanic and Atmospheric Administration (NOAA). For users who are interested in using all or part of this integrated datasets, please contact data owners to discuss your research interests, data-related issues or any other questions. A recommended citation for the data package is available from the download page. In addition, any manuscript generated using this dataset is expected to be sent to the data owners before publication so we can be sure the data is used in the proper context and methods are reported accurately: Santa Barbara Coastal LTER (LTER): Dan Ree
Model simulated hydrological estimates for the North Slope drainage basin, Alaska, 1980-2010
Estimates of runoff, river discharge, snow water equivalent (SWE), subsurface runoff, and soil temperatures are drawn from the Permafrost Water Balance Model (PWBM). The simulation and derived data span the period 1980-2010. The model was forced with daily gridded meteorological data obtained from the Modern-Era Retrospective analysis for Research and Applications (MERRA) reanalysis (version 5.2.0). The estimates of total runoff (daily), soil temperature (daily), subsurface runoff (monthly), and SWE (monthly) are expressed on a spatial grid (N=312; 25x25 km EASE-Grid version 1, Northern Hemisphere) over the North Slope drainage basin, with the coastline extending from Utqiagvik (formerly Barrow) to just west of the Mackenzie River delta. River discharge, calculated as a volume flux of runoff at each grid cell, was routed through the river network defined on a simulated topological network (STN). Archived files contain discharge flux through the grid cell representing the outlet of each of forty-two basins defined across the region on the 25 km resolution EASE-Grid. Details of the PWBM, forcing variables, model validation and results of analysis are described in Rawlins et al. (2019).
Ecophysiology of Carnivorous Plants Worldwide 1980-2011
Identification of trade-offs among physiological and morphological traits and their use in cost-benefit models and ecological or evolutionary optimization arguments have been hallmarks of ecological analysis for at least 50 years. Carnivorous plants are model systems for studying a wide range of ecophysiological and ecological processes and the application of a cost-benefit model for the evolution of carnivory by plants has provided many novel insights into trait-based cost-benefit models. Central to the cost-benefit model for the evolution of botanical carnivory is the relationship between nutrients and photosynthesis; of primary interest is how carnivorous plants efficiently obtain scarce nutrients that are supplied primarily in organic form as prey, digest and mineralize them so that they can be readily used, and allocate them to immediate versus future needs. Most carnivorous plants are terrestrial - they are rooted in sandy or peaty wetland soils - and most studies of cost-benefit trade-offs in carnivorous plants are based on terrestrial carnivorous plants. However more than 10% of carnivorous plants are unrooted aquatic plants. By examining data published between 1980 and 2011, we ask whether the cost-benefit model applies equally well to aquatic carnivorous plants and what general insights into trade-off models are gained by this comparison. Nutrient limitation is more pronounced in terrestrial carnivorous plants, which also have much lower growth rates and much higher ratio of dark respiration to photosynthetic rates than aquatic carnivorous plants. Phylogenetic constraints on ecophysiological trade-offs among carnivorous plants remain unexplored. Despite differences in detail, the general cost-benefit framework continues to be of great utility in understanding the evolutionary ecology of carnivorous plants. We provide a research agenda that if implemented would further our understanding of ecophysiological trade-offs in carnivorous plants and also would pro
Digitised, searchable Holle List in Stokhof (1980)
<p>This repository contains the digitised Holle List in Stokhof (<a href="https://core.ac.uk/reader/159464813">1980</a>). Details and the interactive web version of the list can be accessed via <a title="Digitised, searchable Holle List" href="https://engganolang.github.io/digitised-holle-list/" target="_blank" rel="noopener">https://engganolang.github.io/digitised-holle-list/</a> (Rajeg 2023).</p> <p>The work in this repository is part of the <a href="https://gtr.ukri.org/projects?ref=AH%2FW007290%2F1">AHRC-funded research</a> on <a title="Lexical resources for Enggano" href="https://portal.sds.ox.ac.uk/Lexical_resources_for_Enggano" target="_blank" rel="noopener"><em>Lexical resources for Enggano, a threatened language of Indonesia</em></a> (central webpage of the Enggano project: <a title="Enggano research" href="https://enggano.ling-phil.ox.ac.uk/" target="_blank" rel="noopener">https://enggano.ling-phil.ox.ac.uk/</a>)</p> <h2>Updates in version 1.4.1</h2> <ul> <li>Adding the Transcription table (Stokhof 1980: 75-77, §6.2) on the interactive webpage version (see <a title="Transcription Symbols" href="https://engganolang.github.io/digitised-holle-list/#:~:text=Transcription%20Symbols" target="_blank" rel="noopener">Table 4 "Transcription Symbols"</a>)</li> <li>Adding an update on the potential for the list to be included in the <em>Concepticon</em> (cf. the note <a href="https://github.com/concepticon/concepticon-data/issues/1324">here</a>)</li> <li>Adding reference to <em>EnoLEX</em>, a diachronic lexical database for the Enggano language (cf. <a href="https://doi.org/10.25446/oxford.28282169">here</a>)</li> </ul> <h2>References</h2> <p>Forkel, Robert, Johann-Mattis List, Simon J. Greenhill, Christoph Rzymski, Sebastian Bank, Michael Cysouw, Harald Hammarström, Martin Haspelmath, Gereon A. Kaiping & Russell D. Gray. 2018. Cross-Linguistic Data Formats, advancing data sharing and re-use in comparative linguistics. Scientific Data. Nature Publishing Group 5(1). 180205. <a href="https://doi.org/10.1038/sdata.2018.205" target="_blank" rel="noopener">https://doi.org/10.1038/sdata.2018.205</a>.</p> <p>Krauße, Daniel; Rajeg, Gede Primahadi Wijaya; Pramartha, Cokorda Rai Adi; Zobel, Erik; Nothofer, Bernd; Hemmings, Charlotte; et al. (2024). EnoLEX: A diachronic lexical database for the Enggano language. University of Oxford. Online database. <a title="EnoLEX metadata record" href="https://doi.org/10.25446/oxford.28282169" target="_blank" rel="noopener">https://doi.org/10.25446/oxford.28282169</a>.</p> <p>Rajeg, Gede Primahadi Wijaya. 2023. Digitised, searchable Holle List in Stokhof (1980). Dataset. University of Oxford. <a href="https://doi.org/10.25446/oxford.23205173" target="_blank" rel="noopener">https://doi.org/10.25446/oxford.23205173</a></p> <p>Stokhof, W. A. L. (ed.). 1980. Holle lists, vocabularies in languages of Indonesia, vol. 1: Introductory volume. Vol. Materials in Languages of Indonesia. Canberra, A.C.T., Australia: Dept. of Linguistics, Research School of Pacific Studies, The Australian National University. <a title="Source Holle List in PDF" href="https://core.ac.uk/reader/159464813" target="_blank" rel="noopener">https://core.ac.uk/reader/159464813</a>.</p>
MEaSUREs Greenland Surface Melt Daily 25km EASE-Grid 2.0, Version 1.1.1 (JJA 1980-2022)
<p>This data set offers users a 25 km daily record of surface/near-surface melting on the Greenland Ice Sheet. The presence of melting is determined from brightness temperature data acquired by three satellite-borne microwave radiometers: the Scanning Multichannel Microwave Radiometer (SMMR), the Special Sensor Microwave/Imager (SSM/I), and the Special Sensor Microwave Imager/Sounder (SSMIS).</p> <p>Included in this archive are files for the June-July-August (JJA) summer months during 1980-2022, formatted as a separate file for each year.</p> <p>Version 1.1 includes data for 2021-2022 to supplement the original 1980-2020 dataset from version 1.</p> <p>Version 1.1.1 corrects the 2022 file to include data for 2022-08-24 that was missing in version 1.1.</p>
Wind Stress, Wind Stress Curl, and Upwelling Velocities in the Northwest Atlantic (80-45W, 30-45N) during 1980-2019
<p>This dataset contains three netcdf files that pertain to monthly, seasonal, and annual fields of surface wind stress, wind stress curl, and curl-derived upwelling velocities over the Northwest Atlantic (80-45W, 30-45N) covering a forty year period from 1980 to 2019. Six-hourly surface (10 m) wind speed components from the Japanese 55-year reanalysis (JRA-55; Kobayashi et al., 2015) were processed from 1980 to 2019 over a larger North Atlantic domain of 100W to 10E and 10N to 80N. Wind stress was computed using a modified step-wise formulation, originally based on (Gill, 1982) and a non-linear drag coefficient (Large and Pond, 1981), and later modified for low speeds (Trenberth et al., 1989). See Gifford (2023) for more details. </p> <p>After the six-hourly zonal and meridional wind stresses were calculated, the zonal change in meridional stress (curlx) and the negative meridional change in zonal stress (curly) were found using NumPy’s gradient function in Python (Harris et al., 2020) over the larger North Atlantic domain (100W-10E, 10-80N). The curl (curlx + curly) over the study domain (80-45W, 10-80N) is then extracted, which maintain a constant order of computational accuracy in the interior and along the boundaries for the smaller domain in a centered-difference gradient calculation. </p> <p>The monthly averages of the 6-hour daily stresses and curls were then computed using the command line suite climate data operators (CDO, Schulzweida, 2022) monmean function. The seasonal (3-month average) and annual averages (12-month average) were calculated in Python using the monthly fields with NumPy (NumPy, Harris et al., 2020). </p> <p>Corresponding upwelling velocities at different time-scales were obtained from the respective curl fields and zonal wind stress by using the Ekman pumping equation of the study by Risien and Chelton (2008; page 2393). Please see Gifford (2023) for more details. </p> <p>The files each contain nine variables that include longitude, latitude, time, zonal wind stress, meridional wind stress, zonal change in meridional wind stress (curlx), the negative meridional change in zonal wind stress (curly), total curl, and upwelling. Units of time begin in 1980 and are months, seasons (JFM etc.), and years to 2019. The longitude variable extends from 80W to 45W and latitude is 30N to 45N with uniform 1.25 degree resolution. </p> <p>Units of stress are in Pascals, units of curl are in Pascals per meter, and upwelling velocity is described by centimeters per day. The spatial grid is a 29 x 13 longitude x latitude array. </p> <p>Filenames: </p> <p><strong>monthly_windstress_wsc_upwelling.nc</strong>: 480 time steps from 80W to 45W and 30N to 45N.</p> <p><strong>seasonal_windstress_wsc_upwelling.nc</strong>: 160 time steps from 80W to 45W and 30N to 45N.</p> <p><strong>annual_windstress_wsc_upwelling.nc</strong>: 40 time steps from 80W to 45W and 30N to 45N.</p>
Monthly and Annual contour lines of the zero and the positive maximum of the Wind Stress Curl over Western North Atlantic during 1980-2019 and the Gulf Stream path during 1993-2019.
<p>This dataset includes multiple fields: (i) files for monthly and annual fields for the max curl line and the zero curl line at 0.1 degree longitudinal resolutions; (ii) files for monthly and annual GS path obtained from Altimetry and originally processed by Andres (2016) at 0.1 degree longitudinal resolution. The maximum curl line (MCL) and the zero curl line (ZCL) calculations are briefly described here and are based on the original wind data (at 1.25 x 1.25 degree) provided by the Japanese reanalysis (JRA-55; Kobayashi et al., 2015) and available at https://zenodo.org/record/8200832 (Gifford et al. 2023). For details see Gifford, 2023. </p> <p>The wind stress curl (WSC) fields used for the MCL and ZCL calculations extend from 80W to 45W and 30N to 45N at the 1.25 by 1.25-degree resolution. The MCL is defined as the maximum WSC values greater than zero within the domain per 1.25 degree longitude. As such, it is a function of longitude and is not a constant WSC value unlike the zero contour. High wind stress curl values that occurred near the coast were not included within this calculation. After MCL at the 1.25 resolution was obtained the line was smoothed with a gaussian smoothing and interpolated on to a 0.1 longitudinal resolution. The smoothed MCL lines at 0.1 degree resolution are provided in separate files for monthly and annual averages (2 files). Similarly, 2 other files (monthly and annual) are provided for the ZCL. </p> <p>Like the MCL, the ZCL is a line derived from 1.25 degree longitude throughout the domain under the condition that it's the line of zero WSC. The ZCL is constant at 0 and does not vary spatially like the MCL. If there are more than one location of zero curl for a given longitude the first location south of the MCL is selected. Similar to the MCL, the ZCL was smoothed with a gaussian smoothing and interpolated on to a 0.1 longitudinal resolution. </p> <p>The above files span the years from 1980 through 2019. So, the monthly files have 480 months starting January 1980, and the annual files have 40 years of data. The files are organized with each row being a new time step and each column being a different longitude. Therefore, the monthly MCL and ZCL files are each 480 x 351 for the 0.1 resolution data. Similarly, the annual files are 40 x 351 for the 0.1 degree resolution data. </p> <p><strong>Note that the monthly MCLs and ZCLs are obtained from the monthly wind-stress curl fields. The annual MCLs and ZCLs are obtained from the annual wind-stress curl fields.</strong></p> <p>Since the monthly curl fields preserves more atmospheric mesoscales than the annual curl fields, the 12-month average of the monthly MCLs and ZCLs will not match with the annual MCLs and ZCLs derived from the annual curl field. The annual MCLs and ZCLs provided here are obtained from the annual curl fields and representative metrics of the wind forcing on an annual time-scale. </p> <p>Furthermore, the monthly Gulf Stream axis path (25 cm isoheight from Altimeter, reprocessed by Andres (2016) technique) from 1993 through 2019 have been made available here. A total of 324 monthly paths of the Gulf Stream are tabulated. In addition, the annual GS paths for these 27 years (1993-2019) of altimetry era have been put together for ease of use. The monthly Gulf Stream paths have been resampled and reprocessed for uniqueness at every 0.1 degree longitude from 75W to 50W and smoothed with a 100 km (10 point) running average via matlab. The uniqueness has been achieved by using Consolidator algorithm (D’Errico, 2023). </p> <p>Each monthly or annual GS path has 251 points between 75W to 50W at 0.1 degree resolution. </p>
A Comprehensive Global Aquatic N2O Emission Database (GANED): Unravelling N2O Emission Patterns from Different Water Bodies, 1980-2023
The Global Aquatic Nitrous Oxide Emission Database (GANED) is a comprehensive synthesis of empirical observations of N2O concentration measurements and flux records, spanning the period 1980-2023. GANED advances N2O research by providing the first global systematic emission mechanisms among the different aquatic system types, including rivers, streams, estuaries, reservoirs, ponds, lakes, open seas and coastal areas. The N2O data in GANED is further interconnected with biogeochemical metadata on dissolved oxygen, dissolved organic carbon, ammonium, nitrate, nitrite, total nitrogen, water temperature, salinity and pH, along with site data (latitude, longitude, codes of channel type, depth, surface area, elevation). The dataset explains the discrepancy that emission of N2O in aquatic bodies is determined mainly by substrate availability, and not by climatic factors, and reveals the systematic biases of concentration-only measurements, which can result in an underestimation of fluxes in effluent water of dynamically changing aquatic waters. Consequently, GANED constitutes a crucial transition “where” emissions occur to understanding “why” they differ across systems, and thus enabling targeted mitigation interventions. GANED includes 5130 records of N2O concentration and 7386 flux measurements from 3,002 unique sites, most of which are resolved to the daily time scale.
Mass per tiller, nitrogen concentration, stable isotope ratios for carbon and nitrogen from the 1980-82 Eriophorum vaginatum reciprocal transplant experiment along a latitudinal gradient in interior Alaska collected in July, 2011
In 1980-1982, six transplant gardens were established along a latitudinal gradient in interior Alaska from Eagle Creek, AK in the south to Prudhoe Bay, AK in the north. Three sites, Toolik Lake (TL), Sagwon (SAG), and Prudhoe Bay (PB) are north of the continental divide and the remaining three, Eagle Creek (EC), No Name Creek (NN), and Coldfoot (CF), are south of the continental divide. Each garden consisted of 10 individual Eriophorum vaginatum tussocks transplanted back to their home-site, as well as 10 individuals from each of the other transplant sites. The gardens were harvested in 2011. Important variables are garden name, source population, mass per tiller, nitrogen concentration, and stable isotope ratios for Carbon and Nitrogen.
Light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration from the 1980-82 Eriophorum vaginatum reciprocal transplant plots from Eagle Creek to Prudhoe Bay, Alaska, 2010
In 1980-1982, six transplant gardens were established along a latitudinal gradient in interior Alaska from Eagle Creek, AK, in the south to Prudhoe Bay, AK, in the north (Shaver et al. 1986) .Three sites, Toolik Lake (TL), Sagwon (SAG), and Prudhoe Bay (PB) are north of the continental divide and the remaining three, Eagle Creek (EC), No Name Creek (NN), and Coldfoot (CF), are south of the continental divide. Each garden consisted of 10 individual tussocks transplanted back to their home-site, as well as 10 individuals from each of the other transplant sites. Data were collected in July 2010 for tussocks transplanted in 1980-82 in a reciprocal transplant experiment and then harvested in 2011. Important variables are garden name, source population, light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration.
Relative Humidity from Copernicus Essential Climate Variables for July months from 1980 to 2018
<p>This dataset can be used if you have issues with the Essential Climate Variables Galaxy Tool for the Training "Getting your hands-on climate data" in the section "Essential Climate Variables". You can then upload this dataset in your Galaxy history and skip the 1st step (<strong>Copernicus Essential Climate Variables</strong>) and directly start with 2. <strong>map plot gridded (lat/lon) netCDF data.</strong></p>
Water Cycle Atlas of India (WCAI) v1.0 [1980-2022, Daily, 0.1°]
<p>WCAI ( Water Cycle Atlas of India) is a long term land surface reanalysis of the Indian subcontinent from Jan 1980 to Dec 2022. It is produced using the Indian Land Data Assimillation System (ILDAS) at the Indian Institute of Technology Delhi, New Delhi India. It provides daily estimates of 16 variables at 0.1 degree resolution. The hydrologic and hydrodynamic model combination used is NoahMP3.6 and HYMAP2 forced with Indian Meteorological Department (IMD) gridded precipitation and MERRA2 reanalysis data. This dataset will be valuable for water balance assessments at continental scale for multiple applications such as water resources planning, soil conservation, urban planning, and natural disaster risk mitigation.</p> <p>Changelog</p> <p>------------------------------------</p> <p>v1.0 - Uncalibrated Model outputs</p> <p> </p> <p> </p>
A 30-year high resolution simulation of the ~1980-2010 climate over the Interior Western United States
<p>A high-resolution (4 km) regional climate simulation is conducted in the Interior Western United States (IWUS) using the Weather Research and Forecasting (WRF) model. The IWUS simulation is convection permitting and uses the NoahMP land surface model. The model integration is conducted over a 30-year period from 1 October 1981 through 30 September 2011.</p> <p>This repository contains a 30-year gridded dataset of daily precipitation, and daily minimum and maximum surface (2 m) temperature from the IWUS simulation. Anyone interested in the full dataset of the IWUS simulation is encouraged to contact the lead author at yongganga.wang@gmail.com.</p>
ERA5-derived daily temperature summary 1980-2018
<p>Hourly air temperature at surface data from the ERA5 reanalysis at 0.5˚grid resolution was summarised to produce daily mean, minimum, and maximum temperatures.</p>
Impact Areas and Dynamical Features associated with Mediterranean Cyclones (1980-2019)
<p>The dataset includes NetCDF files of Impact Areas and Dynamical Features associated with Mediterranean Cyclones (henceforth MedCyclones).</p> <p>MedCyclone tracks correspond to confidence-level 5 tracks from Flaounas et al. (2023), <a href="https://doi.org/10.5194/wcd-4-639-2023">https://doi.org/10.5194/wcd-4-639-2023</a>.</p> <p>Temporal frequency: 6h (00, 06, 12, 18 UTC)<br>Years: 1980 – 2019<br>Spatial resolution: 0.5 deg<br>Grid extension: 0-70N, 40W-65E</p> <p> </p> <h2>Dynamical Features</h2> <p>Files "dynfeats_bool_rmax2000_YYYY.nc" include the following list of variables, describing connected boolean objects:</p> <ul> <li><strong>r_500</strong>, <strong>r_1000</strong>: central areas of fixed 500 or 1000 km radius around MedCyclone centres;</li> <li><strong>WCB</strong>: warm conveyor belts related to MedCyclones (i.e., overlapping with r_500 in at least one grid point). Each <strong>WCB</strong> is eventually separated into inflow (<strong>WCBin</strong>, up to 800 hPa) and ascent (<strong>WCBout</strong>, between 800 and 400 hPa) regions. Ref. at <a href="https://doi.org/10.1175/JCLI-D-12-00720.1">https://doi.org/10.1175/JCLI-D-12-00720.1</a>, <a href="https://doi.org/10.5194/wcd-5-537-2024">https://doi.org/10.5194/wcd-5-537-2024</a>;</li> <li><strong>fronts</strong>: cold fronts related to MedCyclones (i.e., overlapping with r_500 in at least one grid point). Ref. at <a href="https://doi.org/10.5194/gmd-17-6137-2024">https://doi.org/10.5194/gmd-17-6137-2024</a>;</li> <li><strong>DI</strong>: dry instrusions related to MedCyclones (i.e., overlapping with r_1000 in at least one grid point). Ref. at <a href="https://doi.org/10.1175/JCLI-D-16-0782.1">https://doi.org/10.1175/JCLI-D-16-0782.1</a>;</li> <li><strong>r_1000_Nodynfeat</strong>: the central 1000 km area excluding regions of MedCyclone WCB, fronts and DI objects.</li> </ul> <p>The criteria for the identification of WCB, fronts and DI objects are described in Section 2.3 of Portal et al. (2024), <a href="https://doi.org/10.5194/wcd-5-1043-2024">https://doi.org/10.5194/wcd-5-1043-2024</a>.</p> <p>Additionally, we note that :<br>i. a weaker overlap constraint was used to associate DI objects to MedCyclones (r_1000 compared to r_500 for WCB and fronts objects) because of the relatively large distance of the DI airstream from the cyclone centre;<br>ii. in this dataset, all connected objects related to MedCyclones are cropped within a 2000 km area circle from the cyclone centre for two reasons. Firstly, the dynamical-feature related surface impacts usually weaken with the distance from the cyclone centre. Secondly, to cut connected objects composed by multiple overlapping features of the same kind - this often happens for fronts in summer because of their high detection density. Far from the cyclone centre, these objects are usually unrelated with the MedCyclone circulation.</p> <p> </p> <h2>Impact Areas</h2> <p>Files "IAs_bool_rmax2000_YYYY.nc" include boolean impact areas, combining a central area (r_1000 or r_500) and cyclone-related WCB, CF and DI objects. The three types of impact area are described in the following :</p> <ol> <li><strong>IA01</strong> is composed by a 1000 km radius circle around the cyclone centre (r_1000) extended by cyclone-related WCB, fronts and DI;</li> <li><strong>IA02</strong> is composed by a 500 km radius circle around the cyclone centre (r_500) extended by cyclone-related WCB, fronts and DI</li> <li><strong>IA03</strong> is composed by a 500 km radius circle around the cyclone centre (r_500) extended by cyclone-related WCB and fronts (DI is neglected).</li> </ol> <p>As discussed in Section 3.1 and Appendix A of Portal et al. (2024) (<a href="https://doi.org/10.5194/wcd-5-1043-2024">https://doi.org/10.5194/wcd-5-1043-2024</a>), IA01, composed by a central area of 1000 km, is adequate for intercepting long-range wind impacts associated with MedCyclones. IA02 and IA03, on the contrary, are better devised for detecting impacts expected at shorter distances from the cyclone centre, such as rainfall, thunderstorm and storm surges. In particular, IA03 neglects the DI region, which is normally of little interest for cyclone-related moist processes, involved in producing precipitation. Noetheless, DI remains relevant for the identification of strong cyclone-related winds.</p> <p> </p> <h3>Case Studies</h3> <p>A pdf file providing the visualisation and description of impact areas and dynamical features of all MedCyclones occurring in 1980 is available at the link <a href="https://boris.unibe.ch/192315/">https://boris.unibe.ch/192315/</a>. Note that in the examples the dynamical features are not cropped at 2000 km from the cyclone centres, as for the present dataset. </p> <p>Note that many of the "Annotations and Limitations" listed below derive from the attentive analysis of these study cases.</p> <h3>Annotations and limitations</h3> <ul> <li>In the case of more than one MedCyclone centre per timestep, the dasaset does not distinguish the impact areas / dynamical features associated with each centre.</li> <li>Because of the automated criteria for associating WCB, fronts and DI objects to MedCyclones, at times objects close to the centre but unrelated to the MedCyclone's circulation, are considered to be cyclone-related and included in the impact area.</li> <li>Elaborating on the point above, at times fronts responsible for Mediterranean cyclogenesis (and not produced by the cyclonic circulation itself) are included in the MedCyclone impact area.</li> <li>When computing statistics over a long time interval (e.g., climatology), the effects of erroneous associations of dynamical features to MedCyclone impact areas are attenuated by the aggregation of large quantity of data. </li> <li>Over a long time interval (e.g., climatology) the choice of a 1000 km fixed-radius impact area provides similar statistics to IA01, although in the first case it is not possible to isolate the role played by the different features composing the MedCyclones.</li> </ul>
RustMapper: White Pine Blister Rust Risk in the Western United States, 1980-2023
White pine blister rust (WPBR) is a highly destructive disease threatening high-elevation five-needle white pines across North America. To better understand risk patterns, we analyzed data from independent studies conducted across the western U.S. between 1995 and 2020. Using this data, we assessed WPBR risk for high-elevation five-needle pine species (High-5) from 1980 to 2023, integrating the results into the adaptive management tool "RustMapper." These projections estimate the annual probability of WPBR occurrence, providing valuable insights for monitoring and management. Risk ranges from 0 to 1, and values closer to 1 indicate a higher likelihood of disease occurrence based on conditions.
UC Davis Suisun Marsh Fish Study, CA,1980-2024
Suisun Marsh, at the geographic center of the northern San Francisco Estuary, provides important habitat for native and non-native fishes, as well as many valued and endangered plants, reptiles, mammals, and birds. The University of California, Davis, Suisun Marsh Fish Study, in partnership with the California Department of Water Resources (DWR), has systematically monitored the marsh's fish populations since January 1980 (O'Rear et al. 2023). The study’s main purpose has been to determine natural and human-caused factors affecting fish and invertebrate distribution and abundance. All sampling has occurred in Suisun Marsh, mostly in subtidal sloughs. Sampling began in 1979, but standardized methods and stations were not implemented until 1980. Sampling has occurred monthly from January 1980 to the present at geographically fixed stations. Fixed stations have been necessary because snags preclude uninterrupted trawls in many sections of smaller sloughs. Originally, 48 stations were selected haphazardly that could be easily and safely sampled by boat and covered the breadth of Suisun Marsh to ensure capture of all variability in fish populations. However, the emphasis has been on sampling smaller sloughs because they exhibit greater variability in a smaller space than the marsh's two big sloughs (Suisun and Montezuma), and because only the big sloughs are sampled by other long-term monitoring projects such as California Fish and Wildlife's Fall Midwater Trawl. The 48 stations were sampled in 1980 and 1981. Water quality and catches were then compared across these stations to locate redundancies and thereby improve logistical efficiency while maximizing capture of variation by eliminating uninformative stations (Brown et al. 1981). Seventeen stations were then chosen and were continuously sampled from 1980 through 1993. Geographic scope was reassessed in 1994, when sampling was reinitiated in the northeast marsh in Denverton and Nurse sloughs at four stations (DV2, DV3
Interagency Ecological Program: San Francisco Bay Study Survey for Fish and Mobile Crustaceans 1980-2024
The San Francisco Bay Study (Bay Study) was established in 1980 to determine the effects of freshwater outflow on the abundance and distribution of fish and mobile crustaceans (brachyuran crabs and caridean shrimp) in the San Francisco Estuary, mainly downstream of the Sacramento-San Joaquin Delta. The Bay Study survey currently samples 52 open-water stations monthly from a research vessel with two types of trawl gear: a midwater trawl to sample pelagic fishes, and an otter trawl to sample demersal fishes, crabs, and shrimp. Historically, the study also included plankton sampling (1980-1989) for larval fish and crustaceans. Fish collected by the otter and midwater trawl are identified to species, counted, and a representative subsample is measured. In addition, crabs from the otter trawl are identified, counted, sexed, and measured, and gelatinous zooplankton from the midwater trawl are identified and counted. Shrimp are retained from each otter trawl sample and returned to the laboratory for processing, which includes identification, counts, sex, and length. Additional data collected at each station includes water depth, Secchi, and a water column profile of temperature and conductivity. This data publication includes fish, crab, shrimp, gelatinous zooplankton (jellies), and water quality data. Metadata related to the plankton sampling will be included in the future when this data is published.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.