cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.bx5qmv
title: Occurrence Download

description: A dataset containing 1681 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "PublishingOrg is c3ad790a-d426-4ac1-8e32-da61f81f0117",
 "TaxonKey is Eichhornia crassipes",
 "Year 2010-2015"
 ]
}

 The dataset includes 1681 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012457-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18486493
title: Structural and dynamic embedding of the mouse functional connectome revealed  by functional ultrasound imaging (fUSI)

description: Functional ultrasound imaging (fUSI) is an emerging hemodynamic neuroimaging modality whose potential for connectome-scale network mapping remains largely untested. Here, we establish a non-invasive transcranial fUSI protocol and an fMRI-inspired preprocessing framework that enable robust resting-state functional connectomics in the mouse. We show that fUSI resolves canonical brain-wide cortical and subcortical networks with high spatial concordance to fMRI, including a default-mode (DMN) and a laterocortical network. Notably, fUSI networks are robustly embedded within the structural connectome, with structure-function coupling being parsimoniously described by four dominant axes that differentially relate functional systems to known anatomical substrates. We also show that, beyond static organization, fUSI reproduces hallmark resting state fMRI dynamics, including dominant anti-correlated coactivation patterns (CAPs) and a structuredtransition architecture that converges onto three stable attractor modes. Together, these results establish transcranial fUSI as a portable and scalable complement to fMRI for connectome-scale mapping of mouse brain networks.
DOI: 10.5281/zenodo.18486492
title: Structural and dynamic embedding of the mouse functional connectome revealed  by functional ultrasound imaging (fUSI)

description: Functional ultrasound imaging (fUSI) is an emerging hemodynamic neuroimaging modality whose potential for connectome-scale network mapping remains largely untested. Here, we establish a non-invasive transcranial fUSI protocol and an fMRI-inspired preprocessing framework that enable robust resting-state functional connectomics in the mouse. We show that fUSI resolves canonical brain-wide cortical and subcortical networks with high spatial concordance to fMRI, including a default-mode (DMN) and a laterocortical network. Notably, fUSI networks are robustly embedded within the structural connectome, with structure-function coupling being parsimoniously described by four dominant axes that differentially relate functional systems to known anatomical substrates. We also show that, beyond static organization, fUSI reproduces hallmark resting state fMRI dynamics, including dominant anti-correlated coactivation patterns (CAPs) and a structuredtransition architecture that converges onto three stable attractor modes. Together, these results establish transcranial fUSI as a portable and scalable complement to fMRI for connectome-scale mapping of mouse brain networks.
DOI: 10.5065/bc97-2h27
title: GPEP CONUS 0.02 degree multi-decadal ensemble daily precipitation and temperature dataset

description: Precipitation and temperature datasets are essential for diverse applications, yet existing high-resolution products often lack robust uncertainty quantification and transparent, reproducible station processing. This dataset resource contains a daily multi-decadal 0.02 ensemble of gridded surface precipitation and temperature for the Contiguous United States (CONUS). It currently spans 1950-2023 (74 years) and includes 10 ensemble members and statistics based on a larger 30-member ensemble. Links to software to generate additional ensemble members are provided in the documentation. The dataset was created using a framework combining meteorological station record reconstruction and spatial probabilistic estimation. The resulting serially-complete station record archive merges high-density observing networks (GHCN-D and MADIS) using a comprehensive set of gap-filling and reconstruction techniques -- quantile mapping, interpolation, machine learning, and multi-source merging -- yielding 25,887 precipitation and 20,998 temperature stations. Gridded Ensemble fields for daily precipitation total, mean temperature (Tmean), and daily temperature range (Trange) are generated using a probabilistic geospatial estimation approach that characterizes spatial variable uncertainty via cross-validation. This open-access ensemble -- together with its station archive and gridded deterministic and probabilistic components -- provides a critical resource for high-resolution hydrologic and climate research across CONUS.
DOI: 10.5065/gyff-5c40
title: Improving representation of stratospheric Polar Vortex in Southern Hemisphere with low-frequency frontal waves

description: Many global models tend to produce a stratospheric polar vortex in the Southern Hemisphere winter that is too strong and too cold - a common issue known as the "cold-pole bias". This bias can affect how models simulate important features like the ozone hole. In this study, we use a development version of the Community Atmosphere Model (CAM) at various horizontal resolutions. We find that higher-resolution simulations reduce the cold-pole bias and better capture the structure of the polar vortex. Motivated by this improvement, we introduce a new scheme to represent a source of frontal gravity waves that so far have been missing in the model. Including this new source representation leads to significant improvements in the model's ability to simulate the Southern Hemisphere stratospheric polar vortex, particularly in wind speeds and the vertical structure of the jet stream.
DOI: 10.5065/sjfq-1h62
title: Past2k: Transient simulation of the climate of the last 2000 years

description: This past2k simulation spanning the last 2 millennia, described in the reference paper [https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018GL079447], uses the fully coupled CESM1.1 at 1 degree resolution in the ocean and sea ice model model and 2 degree resolution in the atmosphere and land model, the same configuration used for the CESM Last Millennium Ensemble [https://doi.org/10.1175/BAMS-D-14-00233.1].The past2k simulation was forced using data compiled for PMIP4 [https://gmd.copernicus.org/articles/10/4005/2017/]. As there was no land-cover forcing available prior to 850 CE when the past2k simulation was started, a superposition of HYDE3.1 crop land changes onto the LME land cover for 850 CE was applied between 1 CE to 849 CE, followed by the land cover forcing from the Last Millennium Ensemble between 850 and 20005 CE. A volcanic aerosol forcing file for CESM1 for the last 2000 years was generated using PMIP4 Easy Volcanic Aerosol data [https://gmd.copernicus.org/articles/9/4049/2016/]. The land cover and volcanic forcing data used for past2k is published [https://openpolar.no/Record/ftzenodo:oai:zenodo.org:1304427].Monthly and daily outputs spanning the last 2000 years are saved and archived as single variable timeseries for the atmosphere, ocean, sea ice, and land model. (Note: In the daily ice data, the file trans1-850AD.cice.h1.FYarea_d.18000101-18991231.nc was corrupted and is not available.) Restart files from the transient simulation are available every 10 years for the first 1000 years and every five years for the second 1000 years of past2k.In addition to the transient past2k output, restart files from the 520 year long CE control simulation are available every 10 years. Note that the past2k simulation was started from year 203 of this control run. See the reference paper [https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018GL079447] for more details on the model spin-up.The past2k simulation was enabled by a Grant of Excellence (141573-053) from the Icelandic Research Center (RANNIS) and the National Science Foundation (ARC 1204096). The model simulation was conducted with high performance computing support from Yellowstone provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation.
DOI: 10.5065/wfzv-nx43
title: MPAS-A pseudo-global warming (PGW) experiment with convection-permitting resolution and regional configuration using the Model for Prediction Across Scales (MPAS) version 8.0.1

description: The dataset includes post-processed model outputs from regional configuration simulations (control and PGW) using the MPAS-A version 8.0.1. This is the first dataset publicly available that uses regional MPAS in combination with the PGW approach to study future climate in short time scales. The Limited-Area domain encompasses 30 degree South to 51 degree North and 3 km horizontal grid outputs, the post-processed outputs available here were interpolated to a 0.25-degree by 0.25-degree latitude-by-longitude grid and 27 isobaric levels (in the vertical). The namelist files to run the model, as well as a README file, are also included in this repository.More details of the data and analysis are published in the Geophysical Research Letters (GRL): Nunez Ocasio and Dougherty, 2024: https://doi.org/10.1029/2024GL112341
DOI: 10.5065/3nsd-qp06
title: Global Ocean Physics Reanalysis

description: From Copernicus Marine Services [https://data.marine.copernicus.eu/product/GLOBAL_MULTIYEAR_PHY_001_030/description] The GLORYS12V1 product is the CMEMS global ocean eddy-resolving (1/12 degree horizontal resolution, 50 vertical levels) reanalysis covering the altimetry (1993 onward). It is based largely on the current real-time global forecasting CMEMS system. The model component is the NEMO platform driven at surface by ECMWF ERA-Interim then ERA5 reanalyses for recent years. Observations are assimilated by means of a reduced-order Kalman filter. Along track altimeter data (Sea Level Anomaly), Satellite Sea Surface Temperature, Sea Ice Concentration and In situ Temperature and Salinity vertical Profiles are jointly assimilated. Moreover, a 3D-Var scheme provides a correction for the slowly-evolving large-scale biases in temperature and salinity. This product includes daily and monthly mean files for temperature, salinity, currents, sea level, mixed layer depth and ice parameters from the top to the bottom. The global ocean output files are displayed on a standard regular grid at 1/12 degree (approximately 8 km) and on 50 standard levels.
DOI: 10.15468/dl.czm5nn
title: Occurrence Download

description: A dataset containing 6682 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Angola",
 "GadmGid is AGO.5_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 1990-2026"
 ]
}

 The dataset includes 6682 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012460-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ry8e3f
title: Occurrence Download

description: A dataset containing 535 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Continent is North America",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Quercus crassipes",
 "Year 1980-2026"
 ]
}

 The dataset includes 535 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012459-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6b34au
title: Occurrence Download

description: A dataset containing 8876 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Continent is North America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rubus allegheniensis"
 ]
}

 The dataset includes 8876 records from 120 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012458-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.71819/airqcp
title: Coleção de Lepidoptera do MZUSP

description: Possui graduação em Ciências Biológicas pela Universidade do Estado do Rio de Janeiro (1996), mestrado em Ciências Biológicas (Entomologia) pela Universidade Federal do Paraná (1999) e doutorado em Ciências Biológicas (Entomologia) pela Universidade Federal do Paraná (2003). Atualmente é professor doutor (MS-3 – nível 2) do Museu de Zoologia da USP e pesquisador associado do National Museum of Natural History, Washington, DC, EUA. Tem experiência na área de Zoologia, com ênfase em Sistemática, Taxonomia e Biologia de Lepidoptera, atuando principalmente nos seguintes temas: Lepidoptera, sistemática, morfologia, taxonomia e Lycaenidae. É Editor de Área do Journal of Research on the Lepidoptera. Foi Vice-Presidente da Lepidopterists’ Society, Los Angeles, CA, EUA (2009-2010). Orienta pós-doutorandos, estudantes de Iniciação Científica, Mestrado e Doutorado. É bolsista do CNPq (Produtividade em Pesquisa – nível 2).
DOI: 10.25345/c50v89x00
title: MassIVE MSV000100717 - structure activtiy relationsip studies for 134thiadiazole based bacterial carbonic anhydrase inhibitors with invivo efficacy against drug resistant gonorrhoeae
title: Study is showing the rawdata for the manuscript JM-2026-000128
DOI: 10.5065/n81d-3e26
title: PERSIANN-CCS Hourly Accumulated Precipitation

description: The current operational PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) system uses neural network function classification/approximation procedures to compute an estimate of rainfall rate at each 0.25 degrees x 0.25 degrees pixel of the infrared brightness temperature image provided by geostationary satellites. An adaptive training feature facilitates updating of the network parameters whenever independent estimates of rainfall are available. The PERSIANN system was based on geostationary infrared imagery and later extended to include the use of both infrared and daytime visible imagery. The PERSIANN algorithm used here is based on the geostationary long wave infrared imagery to generate global rainfall. Rainfall product covers 60 degrees South to 60 degrees North globally.The system uses grid infrared images of global geosynchronous satellites (GOES-8, GOES-10, GMS-5, Metsat-6, and Metsat-7) provided by CPC, NOAA to generate 30-minute rain rates are aggregated to 6-hour accumulated rainfall. Model parameters are regularly updated using rainfall estimates from low-orbital satellites, including TRMM, NOAA-15, -16, -17, DMSP F13, F14, F15.Spectral Intervals and applicable satellites include the long wave infrared channel (10.2-11.2 micro-meters) from GOES-8, GOES-10, GMS-5, Meteosat-6, and Meteosat-7, and instantaneous rainfall estimates from TRMM, NOAA, and DMSP satellites.The PERSIANN Cloud Classification System (PERSIANN-CCS) is a real-time global high resolution (0.04 degrees x 0.04 degrees or 4km x 4km) satellite precipitation product developed by the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine (UCI). The PERSIANN-CCS system enables the categorization of cloud-patch features based on cloud height, areal extent, and variability of texture estimated from satellite imagery. At the center of PERSIANN-CCS is the variable threshold cloud segmentation algorithm. In contrast with the traditional constant threshold approach, the variable threshold enables the identification and separation of individual patches of clouds. The individual patches can then be classified based on texture, geometric properties, dynamic evolution, and cloud top height. These classifications help in assigning rainfall values to pixels within each cloud based on a specific curve describing the relationship between rain-rate and brightness temperature.
DOI: 10.5065/zyy0-y036
title: Four-kilometer long-term regional hydroclimate reanalysis over the conterminous United States (CONUS)

description: CONUS404 is a unique, high-resolution hydro-climate dataset appropriate for forcing hydrological models and conducting meteorological analysis over the conterminous United States. CONUS404, so named because it covers the CONterminous United States for over 40 years at 4 km resolution, was produced by the Weather Research and Forecasting (WRF) model simulations run by NCAR as part of a collaboration with the USGS Water Mission Area. The CONUS404 includes 42 years of data (water years 1980-2021) and the spatial domain [https://osdata.gdex.ucar.edu/web/datasets/d559000/docs/CONUS404_BAMS_fig01.png] extends beyond the CONUS into Canada and Mexico, thereby capturing transboundary river basins and covering all contributing areas for CONUS surface waters.The CONUS404 dataset, produced using WRF version 3.9.1.1, is the successor to the CONUS1 dataset in d612000 [https://gdex.ucar.edu/datasets/d612000/] (Liu, et al. 2017) with improved representation of weather and climate conditions in the central United States due to the addition of a shallow groundwater module and several other improvements in the NOAH Multi-parameterization land surface model. It also uses a more up-to-date and higher-resolution reanalysis dataset (ERA5) as input and covers a longer period than CONUS1.
DOI: 10.5065/d6th8jr2
title: Gridded Ensemble Precipitation and Temperature Estimates over the Contiguous United States Version 2.0

description: Gridded precipitation and temperature products are inherently uncertain due to myriad factors, including interpolation from a sparse observation network, measurement representativeness, and measurement errors. Generally uncertainty is not explicitly accounted for in gridded products of precipitation or temperature; if it is represented, it is often included in an ad-hoc manner. A lack of quantitative uncertainty estimates for hydrometeorological forcing fields limits the application of advanced data assimilation systems and other analysis tools in land-surface and hydrologic modeling. This study develops a gridded, observation-based ensemble of precipitation and temperature at a daily increment for the period 1980-2012. This allows for the estimation of precipitation and temperature uncertainty in hydrologic modeling and data assimilation through the use of the ensemble variance. Statistical verification of the ensemble indicates that it has generally good reliability and discrimination of events of various magnitudes, but has a slight wet bias for high threshold events (greater than 50 mm). The ensemble mean is similar to another widely used hydrometeorological dataset but with some important differences. The ensemble product produces more realistic occurrence of precipitation statistics (wet day fraction), which impacts the empirical derivation of other fields used in land-surface and hydrologic modeling. Elevation lapse rates for temperature are derived directly from the observations, resulting in higher winter temperatures at high elevations in the intermountain western US.
DOI: 10.5065/hsbv-b152
title: Ensemble Historical Gridded Daily Temperature and Bias Adjusted Precipitation for Alaska and the Yukon

description: Recently developed knowledge-based climatological interpolation and ensemble climatologically aided interpolation systems (Newman et al. 2019, 2020a) are used to develop gridded daily, 2 km grid spacing ensemble historical observations across Alaska and the Yukon territory. The ensemble files include daily unadjusted and adjusted precipitation (mm/day), daily mean temperature (degree C), diurnal temperature range (degree C), fraction of precipitation falling as snow, and the wetting loss and wind undercatch correction factors (Newman et al. 2020b). Currently there are only two deterministic daily gridded primarily in situ based observational datasets for this region. This dataset is the novel for the region because it is an ensemble and it contains ensemble estimates of gauge loss corrected precipitation. Additionally, there are limitations with any of the available observation based products, and having another comparison point is useful to the community.
DOI: 10.5065/jn2j-dn74
title: WACCM-X High-Resolution Nature Run

description: A new version of NSF NCAR CESM Whole Atmosphere Community Climate Model with thermosphere/ionosphere extension (WACCM-X) has been developed. The main feature of this version is the species-dependent spectral element (SE) dynamical core solved on a cubed sphere grid, eliminating the polar singularity and enabling simulations at high-resolutions. Molecular viscosity and diffusion in the horizontal direction are also included. The Conservative semi-Lagrangian Multi-Tracer Transport Scheme (CSLAM) is employed for the species transport. An efficient regridding scheme based on the Earth System Modeling Framework is used to map fields between the physics mesh and geomagnetic grid. The WACCM-X high-resolution (NE120) Nature Run refers to the simulation with ~25 km horizontal resolution and 0.1 scale height vertical resolution resolutions for a full year.
DOI: 10.5065/d65q4tsg
title: NCEP Global Forecast System (GFS) Analyses and Forecasts

description: This dataset is a collection of various NCEP GFS data used by NCAR's researchers. It consists of periods of GFS spectral coefficients (in binary format) and flux terms (in GRIB format), as well as their transformed, gridded NetCDF files of various spatial resolutions, T382, T254, T170 and T62. There is no attempt to recover, reconstruct missing data. All products are provided as is.
DOI: 10.5065/xvaq-2x07
title: MERRA2 Global Atmosphere Forcing Data

description: Atmospheric Forcing data, regridded from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) data and prepared as meteorological variables to run CESM and WRF simulations. The MERRA2 was introduced to replace the original MERRA dataset because of the advances made in the assimilation system that enable assimilation of modern spectral radiance and microwave observations, along with GPS Radio Occultation datasets. It also uses NASA's ozone profile observations that began in late 2004. Additional advances in both the GEOS model and the GSI assimilation system are included in MERRA2.