cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/wdcc/en_climatology_2000-2010
title: EARLINET climatology (2000-2010)

description: Project: A European Aerosol Research Lidar Network to Establish an Aerosol Climatology - Aerosols affect life on earth in several ways. They play an important role in the climate system; the effect of aerosols on the global climate system is one of the major uncertainties of present climate predictions. They play a major role in atmospheric chemistry and hence affect the concentrations of other potentially harmful atmospheric constituents, e.g. ozone. They are an important controlling factor for the radiation budget, in particular in the UV-B part of the spectrum. At ground level, they can be harmful, even toxic, to man, animals, and plants. Because of these adverse effects that aerosols can have on human life, it is necessary to achieve an advanced understanding of the processes that generate, redistribute, and remove aerosols in the atmosphere. A quantitative dataset describing the aerosol vertical, horizontal, and temporal distribution, including its variability on a continental scale, is necessary. The dataset is used to validate and improve models that predict the future state of the atmosphere and its dependence on different scenarios describing economic development, including those actions taken to preserve the quality of the environment. The EARLINET data set is the most comprehensive compilation of data available for this purpose. This project description is taken from: http://www.earlinet.org/index.php?id=earlinet_homepage Summary: EARLINET climatological lidar observations are performed on a regular schedule of one daytime measurement per week around noon (on Monday), when the boundary layer is usually well developed, and two night-time measurements per week (on Monday and Thursday), with low background light, in order to perform Raman extinction measurements. This regular schedule for observations minimizes the bias in the dataset possibly related to specific measurement conditions. The resulting dataset is used to obtain unbiased data for climatological studies. This dataset contains profiles of aerosol extinction, backscatter and lidar ratio. Several aerosol extinction/backscatter datasets can be present for the same climatological measurement in order to provide profiles either with a better temporal resolution or with an extended height range by using a larger temporal average. This is by far the largest dataset on the aerosol vertical distribution, and it is the only one which is collected systematically and is covering a whole continent.
DOI: 10.1594/wdcc/en_volcaniceruption_2000-2010
title: EARLINET observations related to volcanic eruptions (2000-2010)

description: Project: A European Aerosol Research Lidar Network to Establish an Aerosol Climatology - Aerosols affect life on earth in several ways. They play an important role in the climate system; the effect of aerosols on the global climate system is one of the major uncertainties of present climate predictions. They play a major role in atmospheric chemistry and hence affect the concentrations of other potentially harmful atmospheric constituents, e.g. ozone. They are an important controlling factor for the radiation budget, in particular in the UV-B part of the spectrum. At ground level, they can be harmful, even toxic, to man, animals, and plants. Because of these adverse effects that aerosols can have on human life, it is necessary to achieve an advanced understanding of the processes that generate, redistribute, and remove aerosols in the atmosphere. A quantitative dataset describing the aerosol vertical, horizontal, and temporal distribution, including its variability on a continental scale, is necessary. The dataset is used to validate and improve models that predict the future state of the atmosphere and its dependence on different scenarios describing economic development, including those actions taken to preserve the quality of the environment. The EARLINET data set is the most comprehensive compilation of data available for this purpose. This project description is taken from: http://www.earlinet.org/index.php?id=earlinet_homepage Summary: Aerosols originating from volcanic emissions have an impact on the climate: sulfate and ash particles from volcanic emissions reflect solar radiation, act as cloud condensation and ice nuclei, and modify the radiative properties and lifetime of clouds, and therefore influence the precipitation cycle. These volcanic particles can also have an impact on environmental conditions and could be very dangerous for aircraft in flight. In addition to the routine measurements, further EARLINET observations are devoted to monitor volcano eruptions. The EARLINET volcanic dataset includes extended observations related to two different volcanoes in Europe Mt. Etna (2001 and 2002 eruptions), and the Eyjafjallajökull volcano in Iceland (April - May 2010 eruption). This dataset includes also recent events of volcanic eruptions in the North Pacific region (2008-2010) that emitted sulfuric acid droplets into the upper troposphere - lower stratosphere (UTLS) height region of the northern hemisphere. The EARLINET volcanic observations in the UTLS are complemented by the long-term stratospheric aerosol observations collected in the Stratosphere category.
DOI: 10.17026/dans-x8n-vcbn
title: Rainfall damage to residential buildings in Amsterdam: a database of survey responses

description: A survey was carried out in 2016 among households in Amsterdam who suffered from rainfall damage in the past years. This database contains the survey response data. A paper that discusses the background, survey design and first results is published in Natural Hazards and Earth System Sciences, and also available in this dataset.Take note that additional conditions of use apply, which can be found in the file 'Creative Commons Attribution-NonCommercial 4.0 International CC BY-NC 4.pdf'.Abstract.Flooding is assessed as the most important natural hazard in Europe, causing thousands of deaths, affecting millions of people and accounting for large economic losses in the past decade. Little is known about the damage processes associated with extreme rainfall in cities, due to a lack of accurate, comparable and consistent damage data. The objective of this study is to investigate the impacts of extreme rainfall on residential buildings and how affected households coped with these impacts in terms of precautionary and emergency actions. Analyses are based on a unique dataset of damage characteristics and a wide range of potential damage explaining variables at the household level, collected through computer-aided telephone interviews (CATI) and an online survey. Exploratory data analyses based on a total of 859 completed questionnaires in the cities of Münster (Germany) and Amsterdam (the Netherlands) revealed that the uptake of emergency measures is related to characteristics of the hazardous event. In case of high water levels, more efforts are made to reduce damage, while emergency response that aims to prevent damage is less likely to be effective. The difference in magnitude of the events in Münster and Amsterdam in terms of rainfall intensity and water depth, is probably also the most important cause for the differences between the cities in terms of the suffered financial losses. Factors that significantly contributed to damage in at least one of the case studies are water contamination, the presence of a basement in the building and people’s awareness of the upcoming event. Moreover, this study confirms conclusions by previous studies that people’s experience with damaging events positively correlates with precautionary behaviour. For improving future damage data acquisition, we recommend to include cell-phones in a CATI survey to avoid biased sampling towards certain age groups.
DOI: 10.17632/hwpvspbc2j.1
title: Load-Price-Wind

description: Load-Price-Wind
DOI: 10.21222/c23p70
title: Next-Generation Liquefaction Database, Version 2
DOI: 10.4225/08/55e5165ec0d29
title: Waite Permanent Rotation Trial

description: History: rotation phase for each plot from 1925 to 1993.
Grain yield: for each plot from 1925 to 1993.
Total dry matter: for each plot from 1925 to 1991.
Pasture cuts: for each plot from 1950 to 1991.
Pasture composition: for each plot from 1950 to 1991.
Monthly climate data: from 1925 to 1993.
Soil carbon data: measured total organic carbon (by combustion) and size fractions (by MIR-PLSR prediction) and delta 14C values for select plots for 1963, 1973, 1983 and 1993 for each of 0-10 cm and 10-22.5 cm depths.
DOI: 10.4225/15/53266be438281
title: In-situ atmospheric ozone measurements observed during the SIPEX II voyage of the Aurora Australis, 2012
DOI: 10.4225/15/532f83302ff88
title: Hysplit atmospheric back-trajectories at 10m, 500m, 1000m, 1500m, 2000m, 2500m, 3000m, 3500m, 4000m collected during the SIPEX II voyage of the Aurora Australis, 2012
DOI: 10.4225/15/5342423241be4
title: In-situ total aerosol number using condensation particle counters as observed during the SIPEX II voyage of the Aurora Australis, 2012
DOI: 10.4225/15/546580a408d97
title: Aurora Australis Voyage VMS 2012/13 Track and Underway Data (SIPEX II)
DOI: 10.5067/1uqjwcypvx61
title: EASE-Grid Sea Ice Age, Version 2
DOI: 10.5067/aura/mls/data2005
title: MLS/Aura L2 Carbon Monoxide (CO) Mixing Ratio - Version 4
DOI: 10.5067/caliop/calipso/cal_lid_l2_05kmapro-prov-v3-30_l2-003.30
title: CALIPSO LID_L2_05kmAPro-Prov HDF File - Version 3.30
DOI: 10.5067/orbview-2/seawifs/l3m/poc/2014
title: SeaWiFS Level 3 Mapped Particulate Organic Carbon Data Version 2014
DOI: 10.5067/terra/mopitt/data202
title: MOPITT Derived CO (Thermal Infrared Radiances) HDF File - Version 6
DOI: 10.5281/zenodo.3361736
title: Embrapa Wine Grape Instance Segmentation Dataset – Embrapa WGISD

description: <strong>Embrapa Wine Grape Instance Segmentation Dataset – Embrapa WGISD</strong> For a detailed description of this dataset, following the <em>datasheet for the datasets</em> recommendation proposed by Gebru et al., check the <strong>README.md</strong> file. <strong>Motivation for Dataset Creation</strong> <em>Why was the dataset created?</em> Embrapa WGISD (<em>Wine Grape Instance Segmentation Dataset</em>) was created to provide images and annotation to study <em>object detection and instance segmentation</em> for image-based monitoring and field robotics in viticulture. It provides instances from five different grape varieties taken on field. These instances shows variance in grape pose,<br> illumination and focus, including genetic and phenological variations such as shape, color and compactness. <em>What (other) tasks could the dataset be used for?</em> Possible uses include relaxations of the instance segmentation problem: classification (Is a grape in the image?), semantic segmentation (What are the "grape pixels" in the image?), and object detection (Where are the grapes in the image?). The WGISD can also be used in grape variety identification.
description: The building of the WGISD dataset was supported by the Embrapa SEG Project 01.14.09.001.05.04, Image-based metrology for Precision Agriculture and Phenotyping, and the CNPq PIBIC Program (grants 161165/2017-6 and 125044/2018-6).
description: {"references": ["Santos, T.T., Souza, L.L., Santos, A.M., & Avila, S.E. (2019). Grape detection, segmentation and tracking using deep neural networks and three-dimensional association. ArXiv, abs/1907.11819."]}
DOI: 10.5285/08fbe63d-fa6d-4a7a-b952-5932e3ab0452
title: Gridded Global Surface Ozone Metrics data (1971-2015) for Atmospheric Chemistry Model Evaluation - version 2.4

description: This dataset consists of version 2.4 gridded surface ozone metrics for atmospheric chemistry model evaluation. These data have global coverage on both monthly and annual timescales from 1971-2015. Multiple model resolutions were used and can be easily identified within the filename.

Data are stored as NetCDF-4 files, with one file per model resolution at each time resolution. The files hold gridded surface ozone data from multiple databases (WMO GAW, EPA CASTNET, EPA AQS, Canadian CAPMON, Canadian NAPS, European EMEP, European AirBase, East Asian Acid Deposition Monitoring Network EANET), plus metadata. Metrics include the moments of the distribution, percentiles, maximum daily eight-hour average (MDA8), SOMO35, AOT40, and metrics related to air quality regulatory thresholds. In addition, metadata for all contributing sites (e.g. Site name, latitude, longitude) are included in each file.
DOI: 10.6084/m9.figshare.26862712
title: SPWV-H: A Spatially-enhanced Vertical Adjustment Model for Global Precipitable Water Vapor

description: <b>SPWV-H</b> is a MATLAB-based computational model designed for estimating global precipitable water vapor (PWV) based on a spatially-enhanced vertical adjustment approach. The model interpolates PWV values from surface grid data, accounting for height-dependent variations and geographic location. By integrating both exponential interpolation and cubic polynomial adjustments, this model allows for accurate estimations of PWV across different altitudes and latitudes.Key Features:<b>Grid-based Interpolation</b>: The model uses surface grid data from three distinct datasets (SPWV-H1, SPWV-H2, SPWV-H3) to estimate PWV values.<b>Vertical Adjustment</b>: Implements an exponential model for height-based interpolation and applies a cubic polynomial correction for low-latitude regions where no land is present.<b>Fourier-based Time Variability</b>: The model incorporates Fourier terms based on the day of year (DOY) to account for annual and semi-annual PWV cycles, making it suitable for time-series analysis.<b>Geographic Flexibility</b>: PWV estimates are adjusted for different geographic regions, with special consideration for low-latitude zones (between -30° and 30° latitude).Applications:<b>Climate Studies</b>: Useful for analyzing water vapor variations over time and space, especially in the context of climate change and atmospheric water cycle studies.<b>Weather and Climate Modeling</b>: Enhances numerical weather prediction models by providing accurate vertical PWV profiles.<b>Hydrological Studies</b>: Can be used to estimate water vapor contributions to precipitation and soil moisture in regional hydrological models.Requirements:<b>MATLAB</b> (Version R2016b or later).Data files for the three SPWV grid datasets (<code>SPWV-H1.txt</code>, <code>SPWV-H2.txt</code>, <code>SPWV-H3.txt</code>).How to Use:<b>Load Grid Data</b>: The model requires pre-processed grid data that contains surface-level PWV values and geographic coordinates (latitude, longitude, height).<b>Set Initial Parameters</b>: Define input parameters such as the beginning and ending height (in km), the initial PWV value (in mm), latitude, longitude, and day of the year (DOY).<b>Run the Model</b>: Call the <code>PWV_Interpolation_Model.m</code> script, which applies the vertical adjustment and spatial interpolation to compute the PWV for specified regions and heights.Citation:Yang, H., Ferreira, V., He, X., Zhan, W., Wang, X., Ji, S., 2025. Spatially enhanced interpolating vertical adjustment model for precipitable water vapor. J. Geod. 99, 12. https://doi.org/10.1007/s00190-025-01936-8
DOI: 10.7265/n5kp8037
title: MODIS Mosaic of Antarctica 2008-2009 (MOA2009) Image Map
DOI: 10.7289/v57p8wbf
title: NOAA Global Monitoring Division Tropospheric Ozone Program

description: This data set contains continuous UV photometric data of surface level ozone collected at 6m above ground level. Data records consist of UTC time, date, and processed ozone mixing ratio (parts per billion). Data is collected from global locations and is provided in 1 minute and 1 hour averages. Data are archived at the NOAA National Climatic Data Center (NCDC), but are produced and available from NOAA Earth System Research Laboratory (ESRL).
DOI: 10.14291/tccon.ggg2014.atm.r0/1221656
title: Atmospheric Line List for the 2014 TCCON Data Release

description: The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier Transform Spectrometers that record direct solar absorption spectra of the atmosphere in the near-infrared. From these spectra, accurate and precise column-averaged abundances of atmospheric constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This is the Atmospheric Line List for the 2014 TCCON Data Release.
description: <br>Cite this record as:<br>Toon, G. C. (2017). <i>Atmospheric Line List for the 2014 TCCON Data Release</i> [Data set]. CaltechDATA. https://doi.org/10.14291/tccon.ggg2014.atm.r0/1221656<br> or choose a  different citation style.<br>Download Citation<br>
DOI: 10.1594/ieda/100123
title: Flexure

description: CSDMS model
DOI: 10.1594/pangaea.587836
title: Dust concentration in the NGRIP ice core

description: Corresponding millennial-scale climate changes have been reported from the North Atlantic region and from east Asia for the last glacial period on independent timescales only. To assess their degree of synchrony we suggest interpreting Greenland ice core dust parameters as proxies for the east Asian monsoon systems. This allows comparing North Atlantic and east Asian climate on the same timescale in high resolution ice core data without relative dating uncertainties. We find that during Dansgaard-Oeschger events North Atlantic region temperature and east Asian storminess were tightly coupled and changed synchronously within 5-10 years with no systematic lead or lag, thus providing instantaneous climatic feedback. The tight link between North Atlantic and east Asian glacial climate could have amplified changes in the northern polar cell to larger scales. We further find evidence for an early onset of a Younger Dryas-like event in continental Asia, which gives evidence for heterogeneous climate change within east Asia during the last deglaciation.
description: Supplement to: Ruth, Urs; Bigler, Matthias; Röthlisberger, Regine; Siggaard-Andersen, Marie-Louise; Kipfstuhl, Sepp; Goto-Azuma, Kumiko; Hansson, Margareta E; Johnsen, Sigfús Jóhann; Lu, Huayu; Steffensen, Jørgen Peder (2007): Ice core evidence for a very tight link between North Atlantic and east Asian glacial climate. Geophysical Research Letters, 34, L03706
DOI: 10.1594/pangaea.723045
title: PeECE II - Pelagic Ecosystem CO2 Enrichment Study, Raunefjord, Bergen, Norway

description: The effects of CO2-induced seawater acidification on plankton communities were also addressed in a series of 3 mesocosm experiments, called the Pelagic Ecosystem CO2 Enrichment (PeECE I-III) studies, which were conducted in the Large-Scale Mesocosm Facilities of the University of Bergen, Norway in 2001, 2003 and 2005, respectively. Each experiment consisted of 9 mesocosms, in which CO2 was manipulated to initial concentrations of 190, 350 and 750 µatm in 2001 and 2003, and 350, 700 and 1050 µatm in 2005. The present dataset concerns PeECE II.
description: http://peece.ifm-geomar.de/index0103.htm. Last updated: 9 December 2010. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Lavigne and Gattuso, 2011) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI).
DOI: 10.1594/pangaea.726955
title: PeECE III - Pelagic Ecosystem CO2 Enrichment Study, Raunefjord, Bergen, Norway, 2005

description: The effects of CO2-induced seawater acidification on plankton communities were also addressed in a series of 3 mesocosm experiments, called the Pelagic Ecosystem CO2 Enrichment (PeECE I-III) studies, which were conducted in the Large-Scale Mesocosm Facilities of the University of Bergen, Norway in 2001, 2003 and 2005, respectively. Each experiment consisted of 9 mesocosms, in which CO2 was manipulated to initial concentrations of 190, 350 and 750 µatm in 2001 and 2003, and 350, 700 and 1050 µatm in 2005. The present dataset concerns PeECE III.
description: http://peece.ifm-geomar.de/index2005.htm. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Lavigne and Gattuso, 2011) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI).
DOI: 10.1594/pangaea.808714
title: Long-term eddy-covariance measurements from FINO2 platform above the Baltic Sea (NetCDF format)

description: Parameter:- DATE/TIME (Date/Time) * Geocode- HEIGHT above ground [m] (height) * Geocode- Valid values per 30min interval (max. 18000) [-] (Val)- Error flag, 0=no error, 1-3=unreliable data: 1=less than half of interval valid , 2=LICOR sensor not reliable, 3=ship transit at platform [-] (Flag)- Mean wind speed over 30 min from USAT [m/s] (FF)- Mean Wind direction over 30 min from USAT [deg] (DD)- Mean Wind in east-west direction over 30 min from USAT [m/s] (U)- Mean Wind in north-south direction over 30 min from USAT [m/s] (V)- Mean Vertical wind speed over 30 min from USAT [m/s] (W)- Mean Air temperature over 30 min from USAT [°C] (T)- Mean Humidity, absolute over 30 min from LICOR 7500 [g/m**3] (AH)- Mean CO2 concentration over 30 min from LICOR 7500 [g/m**3] (CO2)- Mean Humidity, relative over 30 min from ROTRONIC [%] (RH_rot)- Mean Humidity, absolute over 30 min from ROTRONIC [g/m**3] (AH_rot)- Mean Air temperature over 30 min from PT100 [°C] (T_pt100)- Variance of wind speed FF in 30 min time interval [m**2/s**2] (var_FF)- Variance of east-west wind U in 30 min time interval [m**2/s**2] (var_U)- Variance of north-south wind V in 30 min time interval [m**2/s**2] (var_V)- Variance of vertical wind speed W in 30 min time interval [m**2/s**2] (var_W)- Variance of air temperature in 30 min time interval [K**2] (var_T)- Variance of Humidity, absolute in 30 min time interval [g**2/m**6] (var_AH)- Variance of CO2 concentration in 30 min time interval [g**2/m**6] (var_CO2)- Shearing stress [m/s] (Ustar)- Monin-Obukhov-length [m] (MOS)- Roughness length [m] (Z0)- Upward momentum flux in air [kg/m/s**2] (QI)- Upward sensible heat flux with Schotanus correction [W/m**2] (QH)- Upward latent heat flux with Webb correction [W/m**2] (QE)- Upward CO2 flux with Webb correction [mg/m**2/s] (QC)