Find research datasets worth reusing

Enormously large tippers observed in southwest China. Can realistic 3-D EM modeling reproduce them?

This dataset contains the observed tipper data and 3-D EM modeling results associated to the manuscript: Enormously large tippers observed in southwest China. Can realistic 3-D EM modeling reproduce them?

Plume detection and estimate emissions for biomass burning plumes from TROPOMI Carbon monoxide observations using APE v1.1

This data is based on the paper: Plume detection and estimate emissions for biomass burning plumes from TROPOMI Carbon monoxide observations using APE 1.1 (unpublished).

opencc-by-4.0May 2021View details →

The role of teriflunomide in Multiple Sclerosis patient: an observational study

Teriflunomide is a drug with immunosuppressive and selective immunomodulatory action, characterized by anti-inflammatory and antiproliferative properties. Several clinical studies have demonstrated the efficacy and safety of this drug in Multiple Sclerosis, estimating a significant improvement in cognitive performance.The aim of our study is to evaluate the effects of teriflunomide by analysing the correlation between brain atrophy and the general cognitive profile and evaluating long-term changes. The effect of teriflunomide was studied in 30 patients with multiple sclerosis and 30 control subjects. Patients underwent a full cognitive profile assessment using the Brief Repeatable Battery of Neuropsychological Tests and a neuroimaging examination with a 3.0 T working scanner.Our results suggested that treatment with teriflunomide could potentially not only slow down the accumulation of microstructural tissue damage in Grey Matter and With Matter, but also better preserve the cognitive profile, particularly by highlighting the benefits in the memory domain. Thanks to drug therapy, brain volume in our patients has remained constant, leading to improvements in memory, indicating teriflunomide as a neuroprotective potential and further strengthening the evidence of a link between loss of brain volume and cognitive impairment.

Optical polarimetric, photometric and spectroscopic observations of the TDE AT 2020mot with Nordic Optical Telescope

The dataset contains: 1. Polarization data from November 10th, 2020: raw FITS images of the tidal disruption event <a href="https://www.wis-tns.org/object/2020mot">AT 2020mot</a>  (polAT2020mot.zip), master bias, master flat-fields (calibs.zip) and raw FITS images of a polarization standard stars (polstandards.zip) that can be used for the instrumental polarization correction. 2. The imaging data from February 19th, 2021: raw fits images of the tidal disruption event <a href="https://www.wis-tns.org/object/2020mot">AT 2020mot</a> (imaging.zip) , master bias, master flat-fields (imagingcalibs.zip) and reduced and summed R+i image (TDEsum.fits) that was used to fit the host galaxy profile. 3. The spectra from February 19th, 2021: raw fits of the spectra obtained using grisms #7 and #20 (spectroscopy.zip, includes calibration files) and the reduced spectra (TDE.fits). The dataset was obtained with the Nordic Optical Telescope (NOT).

Data and codes for "Increasing deep-water overflow from the Pacific into the South China Sea revealed by mooring observations"

Data files and code files on manuscript entitled "Increasing deep-water overflow from the Pacific into the South China Sea revealed by mooring observations" in Matlab format. Five files are included to draw figures in the manuscript. Details about the variables in the mat files are described in README.txt.

DeLiAn – a growing collection of depolarization ratio, lidar ratio and Ångström exponent for different aerosol types and mixtures from ground-based lidar observations

DeLiAn is a collection of lidar-derived aerosol intensive optical properties for several aerosol types. The intensive parameters are the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarisation lidar measurements. DeLiAn is available in two data formats: NetCDF and excel workbook. The intensive optical properties are presented at the typical lidar wavelengths, 355, 532 and 1064 nm, for 13 aerosol categories in total. The variables included in the datafiles are listed below. For each variable, a full description is provided in the long_name attribute (applicable for the netCDF file only). The same information is provided in the first excel sheet (“List of variables”). <ul> <li> ScienceData <ul> <li>angstrom_exponent_backscatter_355_532</li> <li>angstrom_exponent_backscatter_532_1064</li> <li>angstrom_exponent_extinction_355_532</li> <li>campaign_rv</li> <li>date</li> <li>error_angstrom_exponent_backscatter_355_532</li> <li>error_angstrom_exponent_backscatter_532_1064</li> <li>error_angstrom_exponent_extinction_355_532</li> <li>error_lidar_ratio_355</li> <li>error_lidar_ratio_532</li> <li>error_particle_linear_depolarization_ratio_355</li> <li>error_particle_linear_depolarization_ratio_532</li> <li>lidar_ratio_355</li> <li>lidar_ratio_532</li> <li>location</li> <li>measurement_type</li> <li>number_samples</li> <li>particle_linear_depolarization_ratio_355</li> <li>particle_linear_depolarization_ratio_532</li> <li>reference</li> <li>system</li> </ul> </li> </ul> For any further information or expression of interest with respect to DeLiAn, please contact Athena Augusta Floutsi (<a href="mailto:floutsi@tropos.de">floutsi@tropos.de</a>) and/or Holger Baars (baars@tropos.de).

opencc-by-nc-4.0Mar 2023View details →

Bio-optical observations of the Baltic Sea and coastal areas, 2008-2012

This a dataset of optical-biogeochemical measurement results was collected during 2008-2012 as part of spring and summer cruises with R/V Aranda as well as from flow-through water samples taken with the Ferrybox system on M/S Finnmaid. The majority of observations were made in the Gulf of Finland, Baltic Proper, Archipelago Sea, and Gulf of Bothnia in the Baltic Sea. A number of riverine and inshore observations are also included. The data collection is owned by the Finnish Environment Institute SYKE and made available under a CC-BY-NC licence.  Detail on methods and protocols are provided in the following papers  <ul> <li>Simis, Stefan GH; Ylöstalo, Pasi; Kallio, Kari Y; Spilling, Kristian; Kutser, Tiitt. 2017. Contrasting seasonality in optical-biogeochemical properties of the Baltic Sea. PLoS One 12(4), e0173357. https://doi.org/10.1371/journal.pone.0173357</li> <li>Ylöstalo, Pasi; Seppälä, Jukka; Kaitala, Seppo; Maunula, Petri; Simis, Stefan. 2016. Loadings of dissolved organic matter and nutrients from the Neva River into the Gulf of Finland–Biogeochemical composition and spatial distribution within the salinity gradient. Marine Chemistry 186, 58-71. https://doi.org/10.1016/j.marchem.2016.07.004</li> </ul> A large number of individuals took part in these bio-optical research cruises over the years. The authors of this dataset are particularly grateful to the contributions by international visitors, students and volunteers taking part in one or more cruises, as well as crew and support staff operating the research vessel and ship-of-opportunity.  Variables included in the dataset include:  <table> <tbody> <tr> <td>Column name</td> <td>unit/format</td> <td>Description</td> </tr> <tr> <td>Secchi</td> <td>m</td> <td>Secchi disk depth</td> </tr> <tr> <td>AirTemp(38)</td> <td>°C, 01H</td> <td>Air temperature from ship weather channel 38, 1-h average</td> </tr> <tr> <td>SeaTemp(42)</td> <td>°C, 01H</td> <td>Sea temperature from ship weather channel 42, 1-h average</td> </tr> <tr> <td>WindSpeed(92)</td> <td>m/s, 10M</td> <td>Wind speed from ship weather channel 92, 10-min average</td> </tr> <tr> <td>WindDir(96)</td> <td>°, 10M</td> <td>Wind direction from ship weather channel 96, 10-min average</td> </tr> <tr> <td>Salinity(104)</td> <td>PSU, 01H</td> <td>Salinity from ship weather channel 104, 1-h average</td> </tr> <tr> <td>Rel.humid(54)</td> <td>%, 01H</td> <td>Relative humidity from ship weather channel 54, 1-h average</td> </tr> <tr> <td>Chla</td> <td>mg/m3</td> <td>Chlorophyll-a concentration (cold ethanol extraction and calibrated fluorescence)</td> </tr> <tr> <td>TSM_avg</td> <td>mg/L</td> <td>Total Suspended Matter Dry Weight, Average</td> </tr> <tr> <td>OSM_avg</td> <td>mg/L</td> <td>Dry weight of Organic fraction of TSM, Average</td> </tr> <tr> <td>ISM_avg</td> <td>mg/L</td> <td>Dry weight of Inorganic fraction of TSM, Average</td> </tr> <tr> <td>DOC_avg</td> <td>µM</td> <td>Dissolved Organic Carbon concentration, Average</td> </tr> <tr> <td>TDN_avg</td> <td>µM</td> <td>Total Dissolved Nitrogen concentration, Average</td> </tr> <tr> <td>NH4</td> <td>µM</td> <td>Ammonium concentration</td> </tr> <tr> <td>NO32</td> <td>µM</td> <td>Nitrate-Nitrate concentration</td> </tr> <tr> <td>NO2</td> <td>µM</td> <td>Nitrite concentration</td> </tr> <tr> <td>PO4</td> <td>µM</td> <td>Phosphate concentration</td> </tr> <tr> <td>SiO4</td> <td>µM</td> <td>Silicate concentration</td> </tr> <tr> <td>TN</td> <td>µM</td> <td>Total nitrogen concentration</td> </tr> <tr> <td>TP</td> <td>µM</td> <td>Total phosphorous concentration</td> </tr> <tr> <td>pH</td> <td>pH</td> <td>pH value</td> </tr> <tr> <td>Temp_CTD</td> <td>°C</td> <td>Water temperature measured by Seabird CTD on sampling rosette</td> </tr> <tr> <td>Salinity_CTD</td> <td>SSU</td> <td>Salinity measured by Seabird CTD on sampling rosette</td> </tr> <tr> <td>POC</td> <td>µM</td> <td>Particulate Organic Carbon concentration, Average</td> </tr> <tr> <td>PON</td> <td>µM</td> <td>Particulate Organic Nitrogen concentration, Average</td> </tr> <tr> <td>POP</td> <td>µM</td> <td>Particulate Organic Phosphorus concentration, Average (30.973762 g/Mol)</td> </tr> <tr> <td>Turbidity</td> <td>PSU</td> <td>Turbidity</td> </tr> <tr> <td>aCDOM</td> <td>m^-1</td> <td>spectral absorption coefficient of coloured dissolved organic matter</td> </tr> <tr> <td>CloudCover</td> <td>0-1</td> <td>Fraction (0-1) of cloud cover assesed from photos taken in the field.</td> </tr> <tr> <td>Kd</td> <td>m^-1</td> <td>spectral Vertical diffuse downwelling irradiance coefficient</td> </tr> <tr> <td>a_nap</td> <td>m^-1</td> <td>spectral absorption coefficient by non-pigmented fraction of suspended matter</td> </tr> <tr> <td>a_tsm</td> <td>m^-1</td> <td>spectral absorption coefficient by suspened matter</td> </tr> <tr> <td>R0</td> <td>-</td> <td>spectral Subsurface Irradiance Reflectance</td> </tr> <tr> <td>pigments</td> <td>mg/m3</td> <td>Chlorophyll and other pigments extracted and quantified using a combination of calibrated fluorometry and HPLC</td> </tr> </tbody> </table>

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Vessel traffic observations and associated waterbird surveys, March 2020 – February 2021, Roberts Point and Ogden Point, Victoria, BC, Canada

The coastal waters of southern British Columbia, Canada, encompass habitat of international conservation significance to coastal and marine birds, including sizeable areas designated in the early 1900s as Migratory Bird Sanctuaries (MBS) to protect overwintering waterfowl from hunting near urban centres. Two of these, Shoal Harbour (SHMBS) and Victoria Harbour (VHMBS), have seen significant marine infrastructure development in recent decades and experience considerable vessel traffic. We conducted a pilot study using shore-based observers to develop small-vessel baselines for the winter months when regional waterbird numbers are highest. During our surveys, we recorded considerable inter-site variability in vessel traffic characteristics, with one site (SHMBS) a source of nearly twice as many vessels in total as the other (VHMBS). For waterbirds, hourly 3-minute 'snapshot' surveys, combined with daily tallies of incidental observations, showed that community composition also varied by locality, with one site dominated by gulls (Laridae), cormorants (Phalacrocoracidae), and seaducks (Tribe Mergini), and the other by gulls, cormorants, and alcids (Alcidae). Our results demonstrate that fine-scale local variability must be taken into account when managing for vessel traffic disturbance of waterbirds, particularly at sites of high human population density and increasing coastal development. Results are in press in PLoS ONE (doi:10.1371/journal.pone.0283791).

opencc-zeroMar 2023View details →

In situ observation dataset under the complete seasonal cycle of lake ice

This dataset contains in situ observations of lake ice under a complete seasonal cycle. The study area is Lake Hanzhang in northeast China and the observation period is from winter 2020 to spring 2021. The observations include meteorological, hydrological and optical data. The files contain the following data fields: Readme – a detailed description of data Equipment list – instrument type and accuracy Meteorological data – air temperature, relative humidity, wind speed, pressure, surface temperature Solar radiation data – incident solar radiation and reflected solar radiation Ice thickness and snow depth – ice thickness (ice bottom) and snow depth (ice surface) Ice-water temperature – ice temperature and water ice temperature Spectral irradiance - incident (air) – incident spectral irradiance from 320 - 950 nm (air) Spectral irradiance - reflectance (air) – reflectance spectral irradiance from 320 - 950 nm (air) Spectral irradiance - incident (water - 70 cm to ice surface) – incident spectral irradiance from 320 - 950 nm (water - 70 cm to ice surface) Spectral irradiance - incident (water - 110 cm to ice surface) – incident spectral irradiance from 320 - 950 nm (water - 110 cm to ice surface)

opencc-by-4.0Apr 2022View details →

Orbital-resolved observation of Singlet Fission

Datasets used for the publication "<a href="https://www.nature.com/articles/s41586-023-05814-1">Orbital-resolved observation of Singlet Fission</a>" . The datasets will be published after the corresponding article has been published in a journal. The datasets are stored in the HDF5 file format and can be easily handled with the python package <a href="https://docs.h5py.org/en/stable/">HDF5</a>. They contain a list of 3D datasets with the axes (kx, ky, E). Each entry of the list corresponds to a different time delay. The time delays are indicated for each dataset and equally spaced for the continuous datasets. The energy axis was shifted in the figures and referenced to the maximum energy of the valence band (EVBM) obtained by fitting Gaussians to the EDCs. Dataset_1short_snapshots is used for Fig. 2a, b (TT) and Fig. 4g (t = -200, 40, 50, 60, 70, 80, 90, 150 [fs]) Dataset_1long_snapshots is used for Fig. 2a, b (TT) and Fig. 4g (t = 500, 1000, 2000, 10000 [fs]) Dataset_2_snapshots is used for Fig. 2b (S, X, VBM),  Ext. data Fig. 1a, b, c, Ext. data Fig. 2 (t = -80, -20, -10, 0, 10, 20, 30, 100 [fs]) Dataset_3_continuous is used for Fig. 4a, b, c, d, e, f and Ext. data Fig. 1d, e, Ext. data Fig. 3, Ext. data Fig. 5, Ext. data Fig. 6, Ext. data Fig. 7, Ext. data Fig. 9 (t = -10 to 140 [fs]) Dataset_4_continuous is used for Fig. 4f (-50 to 300 [fs]) Dataset_5_continuous is used for Fig. 4f (t = -100 to 600 [fs]) Dataset_6short_snapshots is used for Ext. data Fig. 4a (t = -300, 0, 20, 50, 100, 200 [fs]) Dataset_6long_snapshots is used for Ext. data Fig. 4a (t = -500, 500, 1000, 10000 [fs]) Dataset_7_continuous is used for Ext. data Fig. 4b, c (t = -60 to 170 [fs])

Observing system simulation experiments to evaluate transport model error on CO2 flux estimates

Atmospheric CO2 inversion using coarse-resolution transport model can cause large errors on surface carbon flux estimates. The transport model errors on flux estimates are isolated using observing system simulation experiments presented here.

opencc-by-4.0Jun 2022View details →

Data for JGR article: Observations of elves and radio wave perturbations by intese lightning

This folder contains data used for the journal paper: Observations of elves and radio wave perturbations by lightning

A global historical twice-daily (daytime and nighttime) land surface temperature dataset produced by AVHRR observations from 1981 to 2021 (2006–2021)

<ul> <li>Land surface temperature (LST) is a key variable for monitoring and evaluating global long-term climate change. However, existing satellite-based twice-daily LST products only date back to 2000, which makes it difficult to obtain robust long-term temperature variations. We developed the first global historical twice-daily LST dataset (GT-LST), with a spatial resolution of 0.05°, using Advanced Very High Resolution Radiometer Level-1b Global Area Coverage data from 1981 to 2021.</li> <li>Validation with in situ measurements from Surface Radiation Budget sites showed that the overall root-mean-square errors of GT-LST varied from 2.0 K to 3.9 K. Inter-comparison with a common LST product (i.e., MYD11A1) revealed that the overall root-mean-square-difference was approximately 3.2 K.</li> <li>More details of this dataset can be seen in readme.pdf.</li> <li>This dataset provides GT-LST product from 2006 to 2021.</li> </ul>

Observations from the distinct neural encoding of glimpsed and masked speech in multitalker situations

These data underlie the figures contained in "Distinct neural encoding of glimpsed and masked speech in multitalker situations"

List of weevils involved in brood site pollination. Published records and new observations

List of plant-weevil brood-site pollination mutualism obtained through literature review completed by unpublished observations. Weevil names and authorship follows the Weevil taxa database (accessed January 2023) otherwise stated. Plant names have been updated according to the World Flora Online (<a href="http://www.worldfloraonline.org/">http://www.worldfloraonline.org/</a>, accessed August 2022).

opencc-by-4.0May 2023View details →

Data for "Observed winter Barents Kara Sea ice variations induce prominent sub-decadal variability and a multidecadal trend in the Warm Arctic Cold Eurasia pattern"

Here the model experiment data used to create the figures in the article "Observed winter Barents Kara Sea ice variations induce prominent sub-decadal variability and a multi-decadal trend in the Warm Arctic Cold Eurasia pattern" are provided.

Fig. 3 in Taxonomic observations regarding four genera ofAfrotropical robber flies, Choerades Walker, 1851, Laphria Meigen, 1803, Nannolaphria Londt, 1977 and Notiolaphria Londt, 1977, and the description of Ericomyia gen. n. (Diptera, Asilidae, Laphriinae)

Fig. 3. Notiolaphria coerulescens (Macquart, 1834), ♂ Réunion (Photo: Dominique Matiré).

Fig. 24 in Taxonomic observations regarding four genera ofAfrotropical robber flies, Choerades Walker, 1851, Laphria Meigen, 1803, Nannolaphria Londt, 1977 and Notiolaphria Londt, 1977, and the description of Ericomyia gen. n. (Diptera, Asilidae, Laphriinae)

Fig. 24. Ericomyia atomentosa (Oldroyd, 1960) ♂, (Madagascar, 7 km W Ranomafana).

Fig. 2. Nannolaphria nigra Londt, 1977 in Taxonomic observations regarding four genera ofAfrotropical robber flies, Choerades Walker, 1851, Laphria Meigen, 1803, Nannolaphria Londt, 1977 and Notiolaphria Londt, 1977, and the description of Ericomyia gen. n. (Diptera, Asilidae, Laphriinae)

Fig. 2. Nannolaphria nigra Londt, 1977, habitat at Marutswa Forest Reserve, Bulwer, South Africa.

Fig. 1. Nannolaphria nigra Londt, 1977 in Taxonomic observations regarding four genera ofAfrotropical robber flies, Choerades Walker, 1851, Laphria Meigen, 1803, Nannolaphria Londt, 1977 and Notiolaphria Londt, 1977, and the description of Ericomyia gen. n. (Diptera, Asilidae, Laphriinae)

Fig. 1. Nannolaphria nigra Londt, 1977, ♂ Pietermaritzburg.