cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1042473
title: Weather Dataset From Vallon De Nant, Switzerland, Until July 2017

description: Weather data collected in the Vallon de Nant, Switzerland v0.1<br>
Data collected by the reasearch team of Bettina Schaefli, UNIL

Period: August 2016 - July 2017

for further information, please contact: anthony.michelon@unil.ch

Grant: SNSF PP00P2\_157611
description: This will be expanded to include more data (hydrological, & meteorological), and more complete metadata.
DOI: 10.5281/zenodo.1217184
title: Bsverticalozone Database

description: An updated and improved version of a global, vertically resolved, monthly mean zonal mean ozone database has been calculated – hereafter referred to as the BSVertOzone database, the BSVertOzone database. Like its predecessor, it combines measurements from several satellite-based instruments and ozone profile measurements from the global ozonesonde network. Monthly mean zonal mean ozone concentrations in mixing ratio and number density are provided in 5 latitude zones, spanning 70 altitude levels (1 to 70km), or 70 pressure 5 levels that are approximately 1km apart (878.4hPa to 0.046hPa). Different data sets or "Tiers" are provided: "Tier 0" is based only on the available measurements and therefore does not completely cover the whole globe or the full vertical range uniformly; the "Tier 0.5" monthly mean zonal means are calculated from a filled version of the Tier 0 database where missing monthly mean zonal mean values are estimated from correlations at level 20 against a total column ozone database and then at levels above and below on correlations with lower and upper levels respectively. The Tier 10 0.5 database includes the full range of measurement variability and is created as an intermediate step for the calculation of the "Tier 1" data where a least squares regression model is used to attribute variability to various known forcing factors for ozone. Regression model fit coefficients are expanded in Fourier series and Legendre polynomials (to account for seasonality and latitudinal structure, respectively). Four different combinations of contributions from selected regression model basis functions result in four different "Tier 1" data set that can be used for comparisons with chemistry-climate model simulations that do not 15 exhibit the same unforced variability as reality (unless they are nudged towards reanalyses). Compared to previous versions of the database, this update includes additional satellite data sources and ozonesonde measurements to extend the database period to 2016. Additional improvements over the previous version of the database include: (i) Adjustments of measurements to account for biases and drifts between different data sources (using a chemistry-transport model simulation as a transfer standard), (ii) a more objective way to determine the optimum number of Fourier and Legendre expansions for the basis 20 function fit coefficients, and (iii) the derivation of methodological and measurement uncertainties on each database value are traced through all data modification steps. Comparisons with the ozone database from SWOOSH (Stratospheric Water and OzOne Satellite Homogenized data set) show excellent agreements in many regions of the globe, and minor differences caused by different bias adjustment procedures for the two databases. However, compared to SWOOSH, BSVertOzone additionally covers the troposphere.
DOI: 10.5281/zenodo.13752499
title: Prolonged exposure to heat enhances mosquito tolerance to viral infection

description: Raw data of the manuscript
DOI: 10.5281/zenodo.13925688
title: QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules

description: This is the QeMFi (Quantum chemistry MultiFidelity) dataset (previously CheMFi, name updated post peer review process) generated for the molecules of the WS22 database. Multifidelity machine learning (MFML) for quantum chemical properties involves building a composite model using various fidelities as opposed to a single fidelity. This dataset is presented to the community as a collection of multifidelity data for various quantum chemical properties for benchmarking of future MFML models. The README.md file contains more details about this dataset and use-cases.
DOI: 10.5281/zenodo.14410427
title: AI and Finance
DOI: 10.5281/zenodo.3373812
title: Defense Meteorology Satellite Program (DMSP) Electron Precipitation (SSJ) Auroral Boundaries, 2010-2014

description: This dataset contains comma seperated value (CSV) files describing the equatorward and poleward edges of the auroral oval in magnetic and geocentric coordinates as determined in Kilcommons et al. 2017 (https://doi.org/10.1002/2016JA023342), using the ssj_auroral_boundary Python package version 1 (https://doi.org/10.5281/zenodo.3267414) This dataset spans 15 satellite years 2010-2014, DMSP spacecraft flights 16, 17 and 18.
DOI: 10.5281/zenodo.3475898
title: Supplement to "Microwave and submillimeter wave scattering of oriented ice particles"

description: This data set contains the simulated brightness temperatures and the corresponding atmospheric states for the radiative transfer simulations for the journal article "Microwave and submillimeter wave scattering of oriented ice particles", which is on Atmospheric Measurement Techniques (AMTD).
DOI: 10.5281/zenodo.3540757
title: Impact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6-LIM3 global ocean–sea ice model

description: Model output and observational data and scripts corresponding to the manuscript "Impact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6-LIM3 global ocean–sea ice model" <strong>Abstract. </strong> This study assesses the impact of different sea ice thickness distribution (ITD) configurations on the sea ice concentration (SIC) variability in ocean-standalone NEMO3.6-LIM3 simulations. Three ITD configurations with different numbers of sea ice thickness categories and boundaries are evaluated against three different satellite products (hereafter referred to as “data”). Typical model and data interannual SIC variability is characterized by k-means clustering both in the Arctic and Antarctica between 1979 and 2014 in two seasons, January–March and August–October, which show the largest coherence across clusters in individual months. Analysis in the Arctic is done before and after detrending the series with a 2nd degree polynomial to separate interannual from longer-term variability. Before detrending, winter clusters capture SIC response to atmospheric variability at both poles and summer cluster a positive and negative trend in the Arctic and Antarctic SIC respectively. After detrending, Arctic clusters reflect SIC response to interannual atmospheric variability predominantly. Model–data cluster comparison suggests that no specific ITD configuration or category number increases realism of the simulated Arctic and Antarctic SIC variability in winter. In the Arctic summer, more thin-ice categories decrease model–data agreement without detrending but increase agreement after detrending. Overall, a single-category configuration agrees the worst with data. Direct model–data comparison of SIC anomaly fields shows that more thick-ice categories improve winter SIC variability realism in Central Arctic regions with very thick ice. By contrast, more thin-ice categories reduce model–data agreement in the Central Arctic in summer, due to an overly large simulated sea ice volume. In summary, whereas better resolving thin ice in NEMO3.6-LIM3 can hamper model realism in the Arctic but improve it in Antarctica, more thick-ice categories increase realism in the Arctic winter. And although the single-category configuration performs the worst overall, no optimal configuration is identified. Our results suggest that no clear benefit is obtained from increasing the number of sea ice thickness categories beyond the current usual standard of 5 categories in NEMO3.6-LIM3.
description: For additional information or any request, please email eduardo(dot)moreno(at)bsc(dot)es
DOI: 10.5281/zenodo.3548747
title: ESR-thermochronometry of the Hida range of the Japanese Alps: Validation and future potential

description: <strong>Supplementary data for the above titled paper published in <em>Geochronology</em>. </strong> <strong>Contents:</strong> Raw OSL data, Raw ESR data, DRAC dose rate input spreadsheet. <strong>OSL-thermochronometry Raw Data.</strong> KRG16-05 KRG16-06 KRG16-101 KRG16-104 KRG16-111 KRG16-112<br> <strong>ESR-thermochronometry Raw Data.</strong> KRG16-05 Al & Ti-centres KRG16-06 Al & Ti-centres KRG16-101 Al & Ti-centres KRG16-104 Al & Ti-centres (4.3 kGy isothermal holding experiment) KRG16-104 Al & Ti-centres (2.15 kGy isothermal holding experiment) KRG16-111 Al & Ti-centres KRG16-112 Al & Ti-centres <strong>Dosimetry data.</strong>
DOI: 10.5281/zenodo.3727673
title: ARTS Microwave Single Scattering Properties Database (Oriented Particles)

description: The database contains microwave and submillimeter wave single scattering data of azimuthally randomly oriented frozen hydrometeors. Main applications lie in polarized active/passive microwave and submillimeter wave remote sensing. This database is an independent add-on to the ARTS Microwave Single Scattering Properties Database. A description of the simulation methods and database is available in the following article. Please cite it if you use the database for a publication. Brath, M., Ekelund, R., Eriksson, P., Lemke, O., and Buehler, S. A.: Microwave and submillimeter wave scattering of oriented ice particles, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-382, in review, 2019. The dataset contains one aggregate habit and one pristine ice crystal habit. Furthermore, 35 frequencies from 1 to 886 GHz, and 3 temperatures, 190, 230 and 270 K, are included. The data were calculated using the discrete dipole approximation method (DDA) in combination with a self developed orientation averaging approach. Interfaces for easy user access is available under a separate upload, due to different licensing, under the title ARTS Microwave Single Scattering Properties Database Interfaces, in which only the Python3 interface can be used for browsing and importing of the single scattering data of azimuthally randomly oriented. The archive InputAzimuthallyRandom.tar.gz contains the shape files, which have be used as input for the DDA simulations. <strong>Unpacking</strong> The data files for the oriented particles follow the same directory structure as the ARTS Microwave Single Scattering Properties Database. Each tar file contains an SSD directory and the subdirectories for a specific particle orientation. Furthermore, it contains as a quick overview a report of the scattering properties for total random orientation. If the totally randomly oriented particle database is already present, these files should be unpacked in the same location that contains the SSD folder. In Unix, all files can be unpacked with: <pre><code class="language-bash">for ssdfile in SSD-AziRnd-ice*.tar; do tar -xvf $ssdfile done </code></pre>
DOI: 10.5281/zenodo.3763442
title: RACMO2.3p3 monthly-accumulated shortwave radiation data for Greenland (September 2000 - 2018)

description: This data set contains RACMO2.3p3 output for Greenland between September 2000 to 2018 at 11 km. Netcdf files are provided for monthly-averaged data for shortwave downward (swsd) and net shortwave (swsn) radiation for total-sky and clear-sky conditions. In addition, the topography and ice mask are added in a separate file. This data set is used in the manuscript "Evaluation of a new snow albedo scheme for the Greenland ice sheet in the regional climate model RACMO2".
DOI: 10.5285/0579d4a8-e315-41d7-af43-25fb50c7d3da
title: Multi-spectral unmanned aerial system imagery, S6, south-west Greenland, July 2017: Level 1 (unmosaiced radiance measurements)

description: This dataset consists of the unprocessed radiance measurements downloaded directly from the unmanned aerial system imaging platform used to image the ice sheet surface at S6 on the south-west Greenland K-transect during July 2017, along with captures of reflectance panels and sensor calibration parameters which enable these imagery to be transformed to reflectance measurements. Funding was provided by the NERC standard grant NE/M021025/1.
description: Flights occurred on: 2017-07-15 2017-07-17 2017-07-20 2017-07-21 2017-07-22 2017-07-23 2017-07-24 Precise flight times are encoded in TIFF headers. Spatial coverage: (UTM Zone 22N), (degrees): Upper Left (571523.742, 7441194.238), (49d 21'14.77"W, 67d 4'46.37"N) Lower Left (571523.742, 7440834.722), (49d 21'15.56"W, 67d 4'34.77"N) Upper Right (571877.909, 7441194.238), (49d 20'45.44"W, 67d 4'46.07"N) Lower Right (571877.909, 7440834.722), (49d 20'46.23"W, 67d 4'34.46"N) Centre (571700.826, 7441014.480), (49d 21'0.50"W, 67d 4'40.42"N) The full methodology used to acquire the measurements in this dataset are presented in: Cook et al. (2019) Algae accelerate melting of the Greenland Ice Sheet, The Cryosphere Discussions Tedstone et al. (2019) Algal growth and weathering crust structure drive variability in Greenland Ice Sheet ice albedo, The Cryosphere Discussions
description: Instrumentation: MicaSense RedEdge multispectral camera integrated onto Steadidrone Mavrik-M quadcopter.
description: No quality control or data cleaning applied.
DOI: 10.5285/a87b7897-354c-4435-a1bc-e6053e7569e0
title: Multi-spectral unmanned aerial system imagery, UPE_U, north-west Greenland, July 2018: Level 1 (unmosaiced radiance measurements)

description: This dataset consists of the unprocessed radiance measurements downloaded directly from the unmanned aerial system imaging platform used to image the ice sheet surface near UPE_U in the north-west of the Greenland Ice Sheet, along with captures of reflectance panels and sensor calibration parameters which enable these imagery to be transformed to reflectance measurements. Funding was provided by the NERC standard grant NE/M021025/1.
description: Flights occurred on: 2018-07-23 2018-07-24, am 2018-07-24, pm 2018-07-26 Precise flight times are encoded in TIFF headers. Spatial coverage: (UTM Zone 22N), (degrees): Upper Left (415832.692, 8088772.973), (53d 33'43.82"W, 72d 52'44.15"N) Lower Left (415832.692, 8088443.273), (53d 33'42.27"W, 72d 52'33.52"N) Upper Right (416181.942, 8088772.973), (53d 33' 5.59"W, 72d 52'44.63"N) Lower Right (416181.942, 8088443.273), (53d 33' 4.06"W, 72d 52'34.00"N) Centre (416007.317, 8088608.123), (53d 33'23.93"W, 72d 52'39.07"N) The full methodology used to acquire the measurements in this dataset are presented in: Cook et al. (2019) Algae accelerate melting of the Greenland Ice Sheet, The Cryosphere Discussions Tedstone et al. (2019) Algal growth and weathering crust structure drive variability in Greenland Ice Sheet ice albedo, The Cryosphere Discussions
description: Instrumentation: MicaSense RedEdge multispectral camera integrated onto Steadidrone Mavrik-M quadcopter.
description: No quality control or data cleaning applied.
DOI: 10.5676/gruan/rs92-gdp.2
title: RS92 GRUAN Data Product Version 2 (RS92-GDP.2)

description: This dataset comprises reference radiosoundings performed with the Vaisala RS92.

Reference in this case means that:
   - all known biases are corrected for
   - best possible vertically resolved uncertainty estimates
   - well-documented correction algorithms
   - extensive meta data collection

The GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) data processing for the Vaisala RS92 radiosonde was developed to meet the criteria for reference measurements. These criteria stipulate the collection of metadata, the use of well-documented correction algorithms, and estimates of the measurement uncertainty. An important and novel aspect of the GRUAN processing is that the uncertainty estimates are vertically resolved. The algorithms that are applied in version 2 of the GRUAN processing to correct for systematic errors in radiosonde measurements of pressure, temperature, humidity, and wind, as well as how the uncertainties related to these error sources are derived. Currently, the RS92 is launched on a regular basis at 13 out of 15 GRUAN sites.

An additional GRUAN requirement for performing reference measurements with the RS92 is that the manufacturer-prescribed procedure for the radiosonde's preparation, i.e. heated reconditioning of the sensors and recalibration during ground check, is followed. In the GRUAN processing however, the recalibration of the humidity sensors that is applied during ground check is removed. For the dominant error source, solar radiation, laboratory experiments were performed to investigate and model its effect on the RS92's temperature and humidity measurements.

GRUAN uncertainty estimates are 0.15 K for night-time temperature measurements and approximately 0.6 K at 25 km during daytime. The other uncertainty estimates are up to 6 %RH for humidity, 10–50 m for geopotential height, 0.6 hPa for pressure, 0.4–1 m/s for wind speed, and 1° for wind direction. Daytime temperature profiles for GRUAN and Vaisala processing are comparable and consistent within the estimated uncertainty. GRUAN daytime humidity profiles are up to 15 % moister than Vaisala processed profiles, of which two-thirds is due to the radiation dry bias correction and one-third is due to an additional calibration correction.

Redundant measurements with frost point hygrometers (CFH and NOAA FPH) show that GRUAN-processed RS92 humidity profiles and frost point data agree within 15% in the troposphere. No systematic biases occur, apart from a 5 % dry bias for GRUAN data around -40 °C at night.
DOI: 10.6073/pasta/051e6f0681b1a05d06f1516d448d83b8
title: Time-series of 5 minute water temperatures averages from Lake E6 near Toolik Field Station, Alaska Summerr 2005.

description: Time-series of temperatures were measured using self-contained temperature loggers on taut-line moorings with a subsurface float 1 m below the air-water. Data are 5 minute averages of 10 second measuremsents.
DOI: 10.6073/pasta/0892203589595da10989458b6c59b6f1
title: Time-series of 5 minute water temperatures averages from Toolik Lake, Toolik Field Station, Alaska, Summer 2005.

description: Time-series of temperatures were measured using self-contained temperature loggers on taut-line moorings with a subsurface float 1 m below the air-water. Theses are the 5 minute averages of 10 second measuremsents.
DOI: 10.6073/pasta/12eb98a258a58ad48867796798bd815d
title: Time-series of 5 minute water temperatures averages from Toolik Lake, Toolik Field Station, Alaska, Summer 2007.

description: Time-series of temperatures were measured using self-contained temperature loggers on taut-line moorings with a subsurface float 1 m below the air-water. Theses are the 5 minute averages of 10 second measuremsents.
DOI: 10.6073/pasta/16a9543aa5a72ead75c40a89038e8f0f
title: McMurdo Dry Valleys LTER - High frequency measurements from Commonwealth Glacier Meteorological Station (COHM) - Taylor Valley, Antarctica - 1993 to present

description: As part of the McMurdo Dry Valleys Long Term Ecological Research program, meteorological data are collected from various locations throughout the McMurdo Dry Valleys of Antarctica. This package contains 15-minute data from the Commonwealth Glacier Meteorological Station (COHM), located in Taylor Valley. COHM was established in 1993, during the 93/94 field season.
DOI: 10.6073/pasta/3fdd4c2d590d5485770e031d7e8678d8
title: Water temperatures from Toolik Lake in Summer 2004.

description: Time series at 5 minute intervals of water temperatures at several depths from a moored chain of thermistors.
DOI: 10.6073/pasta/558a26a196417102957047ae1b7c31fd
title: Time-series of 5 minute water temperatures averages from Lake E6 near Toolik Field Station, Alaska Summer 2004.

description: Time-series of temperatures were measured using self-contained temperature loggers on taut-line moorings with a subsurface float 1 m below the air-water. Data are 5 minute averages of 10 second measuremsents.
DOI: 10.6073/pasta/58ac3c3cc56f45190a60ba5a399e8c9d
title: Time-series of 5 minute water temperatures averages from Lake E5 near Toolik Field Station, Alaska Summer 2001.

description: Time-series of temperatures were measured using self-contained temperature loggers on taut-line moorings with a subsurface float 1 m below the air-water. Data are 5 minute averages of 30 second measuremsents.
DOI: 10.6073/pasta/728016d29b9a7df1eec1cf1ac9b17c23
title: McMurdo Dry Valleys LTER: Landscape Albedo in Taylor Valley, Antarctica from 2015 to 2019

description: This data package contains reflectance data and associated aerial images collected using a helicopter-suspended "albedo box," in which a shortwave radiometer and camera where mounted facing downward. The purpose of this study was to measure how surface reflectance varies within and across landscape types (glaciers, lakes, and soils) over the course of a single field season as well as across multiple field seasons.Â We made five flights in the 2015-2016 field season (20 November 2015, 7 December 2015, 24 December 2015, 5 January 2016, and 12 January 2016), five flights in the 2016-2017 field season (11 November 2016, 3 December 2016, 14 December 2016, 3 January 2017, 23 January 2017), four flights in the 2017-2018 field season (22 November 2017, 7 December 2017, 27 December 2017, 13 January 2018), and two flights in the 2018-2019 field season (23 November 2018, 9 January 2019). Flights originated from Lake Hoare field camp, flew down-valley over Canada Glacier, Lake Fryxell, and Commonwealth Glacier, then turned around and flew up-valley to Taylor Glacier Meteorological Station, after which they returned to Lake Hoare field camp. Flights took roughly one hour and were flown at approximatelyÂ 25.72 m s-1Â (50 knots) andÂ 91.44 m (300 ft) above the ground surface.Â These data can be normalized to incoming solar radiation (measured in-situ at meteorological stations) to calculate landscape albedo. When collected several times throughout a season, these results canÂ show how snow distribution and physical changes to glacier and lake ice impact the amount of incoming radiation that is absorbed, while also tracking the influence of deposited sediment on ice surfaces. Moreover, these data are important for quantifying the long-term changes in energy connectivity between the atmosphere and the landscape (i.e., addressing Hypothesis 1 of the MCM V funding cycle).
DOI: 10.6073/pasta/72b6851a637a29982ae6898a7f61a0eb
title: McMurdo Dry Valleys LTER - High frequency measurements from Canada Glacier Meteorological Station (CAAM) - Taylor Valley, Antarctica - 1994 to present

description: As part of the McMurdo Dry Valleys Long Term Ecological Research program, meteorological data are collected from various locations throughout the McMurdo Dry Valleys of Antarctica. This package contains 15-minute data from the Canada Glacier Meteorological Station (CAAM), located in Taylor Valley (Latitude: -77.61334, Longitude: 162.96437, Elevation: 264 meters above sea level). CAAM was established in 1994, during the 94/95 field season.Â
DOI: 10.6073/pasta/94cc2e0f6a7f26654e3cae655d5c7cc1
title: Time-series of 5 minute water temperatures averages from Lake E5 near Toolik Field Station, Alaska Summer 2005.

description: Time-series of temperatures were measured using self-contained temperature loggers on taut-line moorings with a subsurface float 1 m below the air-water. Theses are the 5 minute averages of 10 second measuremsents.
DOI: 10.6073/pasta/c3b858f1bc3bfd6c375524f6168be35f
title: Time-series of 5 minute water temperatures averages from Lake E5 near Toolik Field Station, Alaska Summer 2003.

description: Time-series of temperatures were measured using self-contained temperature loggers on taut-line moorings with a subsurface float 1 m below the air-water.of water temperatures at several depths from a moored chain of thermistors. Theses are the 5 minute averages of 10 second measuremsents.