cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3981154
title: Vertical cloud radiative heating from the EC-Earth3 v3.3.1 model.

description: The h5 files contain variables used for the article “Vertical structure of cloud radiative heating in the tropics: confronting the EC-Earth v3.3.1/3P model with satellite observations”. The experiment was done with the EC-Earth3 model (https://portal.enes.org/models/earthsystem-models/ec-earth/ec-earth). The model run was done in atmosphere-only mode with prescribed SST for the years 2005 - 2010. Year 2005 and 2006 are considered as spin-up time and are therefore not included. The experiment is described in more detail in the article. The files are named as follows: model-version_resolution_year_month_variable..h5<br> The following variables (named after ECMWF Parameter database) from the model output are included in the dataset:<br> - 107: Top of the atmosphere (TOA) SW radiation (all sky)<br> - 108: TOA SW radiation (clear sky)<br> - 109: TOA SW radiation (cloudy sky)<br> - 110: TOA LW radiation (all sky)<br> - 130: Temperature<br> - 133: Specific humidity<br> - 246: Specific cloud liquid water content<br> - 247: Specific cloud ice water content<br> - 248: Fraction of cloud cover<br> - 54: Pressure The latlon.h5 file contains the latitude and longitude for the dataset. <br> <br> To get the complete dataset for the experiment, see:<br> DOI: 10.5281/zenodo.3958826 for the radiation part of the PRIMAVERA high-resolution data.<br> DOI: 10.5281/zenodo.3960087 for the humidity part of the PRIMAVERA high-resolution data.<br> DOI: 10.5281/zenodo.3947700 for the PRIMAVERA standard-resolution data.<br> DOI: 10.5281/zenodo.3981154 for the V3.3.1 standard-resolution data.<br> DOI: 10.5281/zenodo.4734468 for the python code.
DOI: 10.5281/zenodo.4447228
title: SRON S5P - RemoTeC scientific TROPOMI XCH4 dataset

description: The datasets uploaded contain SRON S5P - RemoTeC scientific TROPOMI XCH4 data that has been post processed from the 'raw' orbit-by-orbit dataset available for download at https://ftp.sron.nl/open-access-data-2/TROPOMI/tropomi/ch4/14_14_Lorente_et_al_2020_AMTD/ (last access: 20 January 2021). File [1] contains global TROPOMI and GOSAT proxy XCH4 daily collocated means averaged into a 2 x 2 degree grid for the period 1 January 2018–31 December 2019. File [2] contains global TROPOMI XCH4 data for 2019 averaged in a cylindrical equal-area grid with 0.3 x 0.5 degree resolution at the Equator. [1] tropomi_gosat_pr_xch4_2x2latlon_dailymeans_14_14_6575_7304_20182019_correction_albedo_only.nc [2] tropomi_xch4_14_14_corr_only_alb_2yr.nc
DOI: 10.5281/zenodo.4646423
title: Fluvial-UMass/Gleason-et-al-TC-2021: Pre-publication archive creation

description: First release of verified code to recreate figures for Gleason et al TC 2021 "Hourly surface meltwater routing for a Greenlandic supraglacial catchment across hillslopes and through a dense topological channel network"
description: Cite the TC journal paper, not this dataset, please
DOI: 10.5281/zenodo.4790962
title: Support data and codes for the evaluation experiment section of the paper: "Mass and geometry reconstruction of snowfall particles from multi angle snowflake camera (MASC) images"

description: Codes and data to support the evaluation of the 3D-GAN method, described in the article: "Mass and geometry reconstruction of snowfall particles from multi angle snowflake camera (MASC) images", submitted to AMTD in 2021. A README is included in the data/code, with details on how to reproduce the results shown in the paper.
DOI: 10.5281/zenodo.4887044
title: WOMBAT: A fully Bayesian global flux-inversion framework, version 1 (intermediate files)

description: Code for reproducing the results of the WOMBAT v1 paper is available on Github. However, fully reproducing the results takes a very long time because of the need to run an atmospheric chemical transport model. To ease this, this dataset contains intermediate files comprising the outputs of the model. These can be used to run the flux inversions; instructions can be found on the code repository.
DOI: 10.5281/zenodo.7236060
title: Model simulation data used in "An inconsistency in aviation emissions between CMIP5 and CMIP6 and the implications for short-lived species and their radiative forcing" (Thor et al., GMD, 2022)

description: This archive contains files that were used to produce the results published in the article "An inconsistency in aviation emissions between CMIP5 and CMIP6 and the implications for short-lived species and their radiative forcing" by Thor et al. The directory nml contains namelist setups (configuration files) used for each of the simulations that were performed for this study.<br> The used MESSy version is d2.54.0.3-pre2.55-02-2077-g6eca90858-dirty_6eca90858ecb4ee8fb8900681a94a79ac3d612af_2021-01-26T11:10:08+01:00_2021-02-18T09:14:01+0100 for the QCTM simulations and d2.54.0.3-pre2.55-02-1466-g1fb086944_1fb0869442bf4f1bb10a7dd5f36e4bde5c0cf6d7_2020-10-27T18:17:50+01:00_2020-10-27T18:24:16+0100 for the aerosol simulations (http://www.messy-interface.org). The directory figures contains ipython scripts that were used to produce the figures in the paper.
DOI: 10.5281/zenodo.7320916
title: Quantifying particle-to-particle heterogeneity in aerosol hygroscopicity

description: Chemical compositions in an aerosol polulation can generally be classified into the nearly hydrophobic (NH), the less hygroscopic (LH), and the more hygroscopic (MH) components according to their capacities of water absorption. The distribution of these three components varies between and within particles due to the complex sources and aging processes, causing the particle-to-particle heterogeneity in aerosol hygroscopicity. Although this heterogeneity is of great importance to the evaluation of aerosol climatic and environmental effects, it has not been paid attention to in previous studies. This study proposes an algorithm to quantify the particle-to-particle heterogeneity from in-situ measurements for the first time. This algorithm can efficiently characterize the evolution of aerosol heterogeneity with time in the atmosphere and provide a framework for quantifying heterogeneities to merge observations into numerical models to deeply investigate how heterogeneity in aerosol hygroscopicity influences aerosol effects on climate and environment.
DOI: 10.5285/57821b58804945deaf4cdde278563ec2
title: Obs4MIPs: Monthly-mean diurnal cycle of top of atmosphere outgoing shortwave radiation from the GERB instrument (GERB-HR-ED01-1-1 rsut 1hrCM), v20231221

description: This dataset contains top of atmosphere (TOA) outgoing shortwave radiation from the Geostationary Earth Radiation Budget (GERB) instrument on board the Meteosat-9 geostationary satellite, for the period from May 2007 until December 2012. In this dataset (labelled 'GERB-HR-ED01-1-1 rsut 1hrCM'), the data provided consist of monthly-mean diurnal cycles, with each day resolved into 1-hour means. Data are only available for eight months of each year (January, February, May, June, July, August, November and December), due to operational constraints of the GERB instrument. 

This is version 1.1 of the product and contains significant improvements over the original version. These improvements include lower estimated uncertainties owing to missing data having been filled where possible and subsequently a greater availability of data within the period provided. Users are strongly encouraged to use this latest version of the products.

It has been produced in Obs4MIPs (Observations for Model Intercomparisons Project) format, as part of an activity to increase the use of GERB satellite observational data for the modelling and model analysis communities. This is not currently a standard GERB satellite instrument product, but does represent an effort on behalf of the GERB project team to identify a product that is appropriate for routine model evaluation. The data have been reprocessed and reformatted, utilising additional data sources where necessary, to create a product primarily intended for comparison with climate model output.
DOI: 10.5285/6ebcb73158b14cd5a321b7c0bc6ed393
title: ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost ground temperature for the Northern Hemisphere, v2.0

description: This dataset contains permafrost ground temperature data produced as part of the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. It forms part of the first version of their Climate Research Data Package (CRDP v1). It is derived from a thermal model driven and constrained by satellite data. Grid products of CDRP v1 are released in annual files, covering the start to the end of the Julian year. This corresponds to average annual ground temperatures and is provided for specific depths (surface, 1m, 2m, 5m , 10m). Case A: It covers the Northern Hemisphere (north of 30°) for the period 2003-2017 based on MODIS Land Surface temperature merged with downscaled ERA5 reanalysis near-surface air temperature data. Case B: It covers the Northern Hemisphere (north of 30°) for the period 1997-2002 based on downscaled ERA5 reanalysis near-surface air temperature data which are bias-corrected with the Case A product for the overlap period 2003-2018 using a pixel-specific statistics for each day of the year.
DOI: 10.5285/7aa17e66aaab4ece87064272b9f94e3a
title: Obs4MIPs: Monthly-mean diurnal cycle of top of atmosphere outgoing longwave radiation from the GERB instrument (GERB-HR-ED01 rlut 1hrCM)

description: This dataset contains top of atmosphere (TOA) outgoing longwave radiation from the Geostationary Earth Radiation Budget (GERB) instrument on board the Meteosat-9 geostationary satellite, for the period from May 2007 until 2012. In this dataset (labelled 'GERB-HR-ED01 rlut 1hrCM'), the data provided consist of monthly-mean diurnal cycles, with each day resolved into 1-hour means. Data are only available for six months of each year (January, May, June, July, November and December), due to operational constraints of the GERB instrument. It has been produced in Obs4MIPs (Observations for Model Intercomparisons Project) format, as part of an activity to increase the use of GERB satellite observational data for the modelling and model analysis communities. This is not currently a standard GERB satellite instrument product, but does represent an effort on behalf of the GERB project team to identify a product that is appropriate for routine model evaluation. The data may have been reprocessed, reformatted, or created solely for comparisons with climate model output.
DOI: 10.5285/90148d9b1f1c40f1ac40152957e25467
title: Obs4MIPs: Monthly-mean diurnal cycle of top of atmosphere outgoing longwave radiation from the GERB instrument (GERB-HR-ED01-1-1 rlut 1hrCM), v20231221

description: This dataset contains top of atmosphere (TOA) outgoing longwave radiation from the Geostationary Earth Radiation Budget (GERB) instrument on board the Meteosat-9 geostationary satellite, for the period from May 2007 until December 2012. In this dataset (labelled 'GERB-HR-ED01-1-1 rlut 1hrCM'), the data provided consist of monthly-mean diurnal cycles, with each day resolved into 1-hour means. Data are only available for eight months of each year (January, February, May, June, July, August, November and December), due to operational constraints of the GERB instrument.

This is version 1.1 of the product and contains significant improvements over the original version. These improvements include lower estimated uncertainties owing to missing data having been filled where possible and subsequently a greater availability of data within the period provided. Users are strongly encouraged to use this latest version of the products.

It has been produced in Obs4MIPs (Observations for Model Intercomparisons Project) format, as part of an activity to increase the use of GERB satellite observational data for the modelling and model analysis communities. This is not currently a standard GERB satellite instrument product, but does represent an effort on behalf of the GERB project team to identify a product that is appropriate for routine model evaluation. The data have been reprocessed and reformatted, utilising additional data sources where necessary, to create a product primarily intended for comparison with climate model output.
DOI: 10.5439/1095580
title: ARM: AOS: Aethalometer, measures Black Carbon

description: AOS: Aethalometer, measures Black Carbon
DOI: 10.12770/0dc16d62-05f6-4bbe-9dc4-6d47825a5931
title: OceanSODA standardised surface ocean carbonate system matchup dataset

description: In recent years, large datasets of in situ marine carbonate system parameters (partial pressure of CO2 (pCO2), total alkalinity, dissolved inorganic carbon and pH) have been collated. These carbonate system datasets have highly variable data density in both space and time, especially in the case of pCO2, which is routinely measured at high frequency using underway measuring systems. This variation in data density can create biases when the data are used, for example for algorithm assessment, favouring datasets or regions with high data density. A common way to overcome data density issues is to bin the data into cells of equal latitude and longitude extent. This leads to bins with spatial areas that are latitude and projection dependent (eg become smaller and more elongated as the poles are approached). Additionally, as bin boundaries are defined without reference to the spatial distribution of the data or to geographical features, data clusters may be divided sub-optimally (eg a bin covering a region with a strong gradient). To overcome these problems and to provide a tool for matching in situ data with satellite, model and climatological data, which often have very different spatiotemporal scales both from the in situ data and from each other, a methodology has been created to group in situ data into ‘regions of interest’, spatiotemporal cylinders consisting of circles on the Earth’s surface extending over a period of time. These regions of interest are optimally adjusted to contain as many in situ measurements as possible. All in situ measurements of the same parameter contained in a region of interest are collated, including estimated uncertainties and regional summary statistics. The same grouping is done for each of the other datasets, producing a dataset of matchups. About 35 million in situ datapoints were then matched with data from five satellite sources and five model and re-analysis datasets to produce a global matchup dataset of carbonate system data, consisting of 287,000 regions of interest spanning 54 years from 1957 to 2020. Each region of interest is 100 km in diameter and 10 days in duration. An example application, the reparameterisation of a global total alkalinity algorithm, is shown. This matchup dataset can be updated as and when in situ and other datasets are updated, and similar datasets at finer spatiotemporal scale can be constructed, for example to enable regional studies. This dataset was funded by ESA Satellite Oceanographic Datasets for Acidification (OceanSODA) project aims at developing the use of satellite Earth Observation for studying and monitoring marine carbonate chemistry.
DOI: 10.1594/pangaea.896770
title: Hydrographical time series data of the littoral zone of Kongsfjorden, Svalbard 2016

description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll A and turbidity data from the AWIPEV underwater observatory from the year 2016 in a temporal resolution of 1 hour. The cabled observatory is located in 12m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-spitsbergen.html) For a detailed description of the data see associated metadatafile "metadata_svulobs_2016_hydrography.pdf".
description: Time series plots:Chlorophyll a: http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2016_chlorophyll_a.pdfOxygen saturation: http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2016_oxygen_saturation.pdfSalinity: http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2016_salinity.pdfTemperature, water: http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2016_temperature.pdfTurbidity (Formazin Turbidity Unit): http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2016_turb_ftu.pdf
DOI: 10.1594/pangaea.896771
title: Hydrographical time series data of the littoral zone of Kongsfjorden, Svalbard 2015

description: The dataset contains temperature, salinity, oxygen saturation, chlorophyll A and turbidity data from the AWIPEV underwater observatory from the year 2015 in a temporal resolution of 1 hour. The cabled observatory is located in 12m water depth and comprises single or multiple sensors for a specific parameter (see https://www.awi.de/en/science/biosciences/shelf-sea-system-ecology/main-research-focus/cosyna/underwater-node-spitsbergen.html) For a detailed description of the data see associated metadatafile "metadata_svulobs_2015_hydrography.pdf".
description: Time series plots:Chlorophyll a: http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2015_chlorophyll%20a.pdfOxygen saturation: http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2015_oxygen_saturation.pdfSalinity: http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2015_salinity.pdfTemperature, water: http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2015_temperature.pdfTurbidity (Formazin Turbidity Unit): http://store.pangaea.de/Publications/FischerP-etal_2018/All_NRT_1_2015_turb_ftu.pdf
DOI: 10.1594/pangaea.913719
title: Polarimetric phase-sensitive Radio Echo Sounder measurements at EDML, 2017

description: Polarimetric phase-sensitive Radio Echo Sounder (PpRES) measurements at Kohnen station next to EDML, Antarctica. LD0.1, LD1 and LD10 are measurements in logarithmic distances and G11, ..., G33 are measurements for a 3x3 grid with 10 m horizontal and vertical distance between the grid points, see the attached map (map_PpRES_Data.jpg) for clarification. The file names include the degree of the measurement representing the orientation of the antennas (clockwise rotation, 0 degree for the flow direction) and HH, HV, VH, VV denotes the polarization, see orientation_polarization_PpRES.jpg.
DOI: 10.1594/pangaea.914808
title: Continuous meteorological observations at station Ny-Ålesund (2020-03)
DOI: 10.1594/pangaea.923638
title: Forest inventories on circular plots on the expedition Chukotka 2018, NE Russia

description: We undertook a large-scale forest inventory in central Chukotka in summer 2018 on a joint Russian-German expedition by the AWI (Potsdam) and the NEFU (Yakutsk). We covered different densities of larch forest plots accross the tundra-taiga gradient.Tree height estitmations were conducted after training with a clinometer (SUUNTO, Finland) for trees present on 22 sites inventoriziong all trees (N=2624) on 15 m radial plots.
description: We acknowledge funding by the ERC consolidator grant Glacial Legacy of Ulrike Herzschuh (see Additional Funding).
DOI: 10.1594/pangaea.923784
title: Individual tree and tall shrub partial above-ground biomass of central Chukotka in 2018

description: Tree and tall shrub above ground biomass (AGB) samples were taken in five areas: a treeless mountainous tundra (16-KP-04; Lake Rauchuagytgyn area), tundra-taiga transition zone (16-KP-01, Lake Ilirney area; 18-BIL-00) and a northern taiga (18-BIL-01, 18-BIL-02). In total, 31 sample plots with 15-m radius were investigated for tree and tall shrub AGB. The only present tree species there is Larix cajanderi Mayr. By tall shrubs we mean Pinus pumila (Pall.) Regel, Alnus viridis ssp. fruticosa (Rupr.) Nyman and Salix spp. L.Three living trees (the lowest, a tree with the average height and the highest) per each site were cut down. From each individual tree certain representative samples were taken: samples of branches, needles, cones and tree stem discs. Sampled branches were divided into four categories: 1) big (first order, connected to the stem), 2) medium (second order, connected to the big branches), 3) small (third order, connected to the medium branches), 4) dead (including dead cones). Needles are typically found on the third order branches. Cones were divided by colour (red, brown and grey). Tree stem discs were taken at the base of a tree (0 cm, disc A), breast height (130 cm, disc B) and top/close to the top of a tree (260 cm, disc C). To estimate each tree's stem biomass, the stem was assumed to have a cone shape. Dead trees were also sampled, but irregularly (not at every sample plot). In most cases, they did not have branch and needle material, so the samples of dead trees mostly consist of tree discs' samples.Tall shrubs were representatively sampled similarly to trees – three individuals per site. Samples included branch, leaves/needles and cones/catkin biomass.All harvested AGB samples were weighed fresh in the field and subsampled. All subsamples were oven dried (60 °C, 48 h for shrub and tree branch samples, up to one week for tree stem discs) and weighed again.Protocol for total tree and shrub AGB estimation can be found enclosed as a separate file.All data were collected by scientists from Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research and University of Potsdam, Germany, The Institute for Biological problems of the Cryolithozone, Russian Academy of Sciences, Siberian branch, and The Institute of Natural Sciences, North-Eastern Federal University of Yakutsk, Yakutsk, Russia.”All data were collected during the “Chukotka 2018” expedition, that has been supported by the German Federal Ministry of Education and Research (BMBF), which enabled the Russian-German research programme “Kohlenstoff im Permafrost KoPf” (grant no. 03F0764A) and by the Initiative and Networking Fund of the Helmholtz Association and by the ERC consolidator grant Glacial Legacy of Ulrike Herzschuh (grant no. 772852).
DOI: 10.1594/pangaea.925612
title: Continuous meteorological observations at station Ny-Ålesund (2020-04)
DOI: 10.1594/pangaea.927451
title: High resolution sea ice drift and deformation off the North Coast of Greenland in March 2018

description: High resolution sea ice drift and deformation fields in March 2018 in the Wandel Sea and adjacent Arctic Ocean are presented. The fields cover a 30 days period of strong deformation of young ice that had formed in a preceding polynya event. Drift fields were obtained from Sentinel-1, HH polarization SAR images acquired in enhanced wide mode. These had a pixel resolution of 50 m in Polar Stereographic North projection (latitude of true scale: 70 N, center longitude: 45 W). We used an ice tracking algorithm introduced by Thomas et al. (2008, 2011) and modified by Hollands and Dierking (2011) to derive drift from sequential pairs. Based on satellite data coverage, the time steps between two scenes varied between 0.9 and 2 days. The resulting drift data set was defined on a regular grid with a spatial resolution of 700 m. Outliers in the velocity data were reduced by a 3x3 point running median filter covering an area of 2.1x2.1 km. For the deformation estimates, we calculated deformation using a linear approximation based on Green's Theorem that relates the double integral over a plane to the line integral along a simple curve surrounding the plane. We discretized the curve applying the trapezoid method that linearly interpolates velocity between the vertices of the grid cells.