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{"references": ["UNSD Demographic Statistics, available at http://data.un.org", "The World Bank GDP data, available at https://data.worldbank.org/", "UNFCCC: Greenhouse Gas Inventory Data, available at https://unfccc.int/process/transparency-and-reporting/greenhouse-gas-data/what-is-greenhouse-gas-data"]} Dataset containing all greenhouse gas emissions data submitted by countries under climate change convention (including CRF data) as published by the UNFCCC secretariat at 2021-12-03. The dataset is also available via datalad. To obtain the dataset with datalad, see the instructions at https://github.com/mikapfl/unfccc_di_data .

The HANZE dataset covers riverine, pluvial, coastal and compound floods that have occurred in 42 European countries. It contains: 2521 historical floods with impact data (1870-2020); 237 further historical floods with significant impacts, but without precise impact data (1950-2020) Nearly 15,000 modelled floods with a potential to cause significant impacts, classified by actual historical occurrence or non-occurrence impacts (1950-2020). Historical floods and the classification of modelled floods was completed by extensive data-collection from more than 900 sources ranging from news reports through government databases to scientific papers. Impact data collected or modelled include area inundated, fatalities, persons affected or economic loss. Economic losses were inflation- and exchange-rate adjusted to 2020 value of the euro. The historical catalogue (lsit A) also includes losses in the original currencies and price levels. The spatial footprint of affected areas is consistently recorded using more than 1400 subnational units corresponding, with minor exceptions, to the European Union’s Nomenclature of Territorial Units for Statistics (NUTS), level 3. Apart from the possibility to download the data, the database can be viewed, filtered and visualized online: https://naturalhazards.eu. The dataset contains the following files (CSV comma-delimited, UTF8, and ESRI shapefiles in zipped folders): HANZE_historical_floods_catalogue_listA.csv - historical floods with impact data (1870-2020) HANZE_historical_floods_catalogue_listB.csv - historical floods without impact data (1950-2020) HANZE_potential_flood_catalogue_all.csv - modelled potential floods (1950-2020) HANZE_list_of_references.csv - List of all references used in the catalogues HANZE_model_completness_analysis.csv - Comparison between modelled and reported footprints of historical floods Regions_v2010_simplified.zip - Map of subnational regions (v2010) Regions_v2021_simplified.zip - Map of subnational regions (regions v2021) v1.1: errors in two records in "HANZE_historical_floods_catalogue_listB.csv" (wrong country code in event ID 8227 and wrong start date in event ID 8237) were corrected. This work was supported by the German Research Foundation (DFG) through project "Decomposition of flood losses by environmental and economic drivers" (FloodDrivers), project no. 449175973 

CASCADE is a global dataset for 139 extant coccolithophore taxonomic units. CASCADE includes a trait database (size and cellular organic and inorganic carbon contents) and taxonomic-specific global spatiotemporal distributions (Lat/Lon/Depth/Month/Year) of coccolithophore abundance and organic and inorganic carbon stocks. CASCADE covers all ocean basins over the upper 275 meters, spans the years 1964-2019 and includes 33,119 taxonomic-specific abundance observations. Within CASCADE, we characterise the underlying uncertainties due to measurement errors by propagating error estimates between the different studies. Full details of the data set are provided in the associated Scientific Data manuscript. The repository contains five main folders: 1) "Classification", which contains YAML files with synonyms, family-level classifications, and life cycle phase associations and definitions; 2) "Concatenated literature", which contains the merged datasets of size, PIC and POC and which were corrected for taxonomic unit synonyms; 3) "Resampled cellular datasets", which contains the resampled datasets of size, PIC and POC in long format as well as a summary table; 4) "Gridded data sets", which contains gridded datasets of abundance, PIC and POC; 5) "Species lists", which contains spreadsheets of the "common" (>20 obs) and "rare" (<20 obs) species and their number of observations. The CASCADE data set can be easily reproduced using the scripts and data provided in the associated github repository: https://github.com/nanophyto/CASCADE/ (zenodo.12797197) Correspondence to: Joost de Vries, joost.devries@bristol.ac.uk v.0.1.2 has some fixes: 1. The wrongly specified S. neapolitana was removed from synonyms.yml (this species is now S. nana)2. Longitudes were corrected for Guerreiro et al., 20233. A double entry for Dimizia et al., 2015 was fixed4. Units in Sal et al., 2013 were correct to cells/L (previously cells/ml)5. Data from Sal et al., 2013 was re-done, as some species were missing6. Duplicate entries from Baumann et al., 2000 were dropped

This dataset and codebook correspond to the second round of survey data gathered in Denmark in 2023, within the project FULFILL - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes. As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from six countries: Denmark, France, Germany, Italy, Latvia, and India. The first round of the survey, consisted of recruiting a representative sample of approximately 2000 households in each country. In this second survey round, we recruit around 500 respondents from the initial survey round, ensuring representativity is maintained. This survey is very similar to the survey in the first round and includes a lot of identical items, including a quantitative assessment of the carbon footprint in the housing, mobility, and diet sectors, socio-economic factors such as age, gender, income, education, household size, life stage, and political orientation. Furthermore, the survey includes measures of quality of life, encompassing aspects such as health and well-being, environmental quality, financial security, and comfort. New for this second round, we have incorporated questions regarding the measures respondents adopted in response to the 2022 energy crisis.

The PV-Live dataset comprises data from a network of 40 solar irradiance measurement stations across the German state of Baden-Württemberg. All stations measure global horizontal irradiance and temperature with a pyranometer, and global tilted irradiance in east, south, and west direction with tilt angles of 25° with three photovoltaic reference cells in minute resolution. A quality control scheme has been developed specifically for this dataset and is applied to the measurements before publication. The minute resolution irradiance and temperature measurements are published with the derived quality flags. A description of the dataset and the quality control scheme is given in Lorenz et al. (2022) and Lorenz et al. (2020). The dataset contains data from September 2020 onwards. It will be continuously extended by adding data of the previous month on a monthly basis. QUALITY FLAGS Two types of flags are provided with the data. Each sensor is assigned a general quality flag, which is based on a combination of different tests. In addition, a shading flag is given, which is not sensor specific, i.e. it applies to all irradiance sensors simultaneously. The flags can have the levels 'passed, all tests complete', 'passed, not all tests complete', 'failed tests, likely erroneous' or 'failed tests, most likely erroneous'. If the flag level of the general quality flags is 'failed tests, most likely erroneous' the corresponding measurement value is set to NaN. DATA FORMAT The data is published as monthly .zip archives. Each archive contains the following files: 1. Tab separated data files (tng000XX_YYYY-MM.tsv) for each station, containing measurements and quality flags of one month 2. Tab separated station location metadata (metadata_stations_YYYY-MM.tsv) 3. Metadata of the dataset describing variable names and quality flag levels (metadata_measurements.json) 4. General comments on data availability and quality for the month (comments_quality_control_YYYY-MM.txt) 5. Log file of changes (change_log_YYYY-MM.txt) Station location metadata is given on a monthly basis because stations can be relocated. Therefore, we recommend to use the metadata valid for its corresponding month. VERSION UPDATES Version 7: - Recalculation of height information for all stations - One station has been moved to a new, nearby location on 16th September 2021 ACKNOWLEDGEMENTS The data have been collected and processed by Fraunhofer ISE in the framework of PV-Live, a project in cooperation with TransnetBW. We thank our station partners for cooperation in installing and maintaining our measurement stations: EnBW Solar, Badenova, Pohlen Solar, Oekogeno Solar7, Ecovision, Hochschule Ulm, Hofgemeinschaft Heggelbach, Soltechnics-solution and the Stadtwerke Karlsruhe, Grünstadt, Buchen, Crailsheim, Schwäbisch Hall, Pforzheim, Konstanz, Waldshut-Tiengen, Schwäbisch Gmünd, Ravensburg, Eberbach, Baden-Baden.

The Aneto Glacier, is the largest glacier in the Pyrenees. Its shrinkage and wastage have been continuous in recent decades, and there are signs of accelerated melting in recent years. In this study, changes in the surface and ice thickness of the Aneto Glacier from 1981 to 2022 are investigated using historical aerial imagery, airborne LiDAR point clouds, and UAV imagery. A GPR survey conducted in 2020, combined with data from photogrammetric analyses, allowed us to reconstruct the current ice thickness and also the existing ice distribution in 1981 and 2011. Over the last 41 years, the total glaciated area has shrunk by 64.7% and the ice thickness has decreased, on average, by 30.5 m. The mean remaining ice thickness in autumn 2022 was 11.9 m, as against the mean thicknesses of 32.9 m, 19.2 m reconstructed for 1981 and 2011 and 15.0 m observed in 2020 respectively. The results demonstrate the critical situation of the glacier, with an imminent segmentation into two smaller ice bodies and no evidence of an accumulation zone. We also found that the occurrence of an extremely hot and dry year, as observed in the 2021–2022 season, leads to a drastic degradation of the glacier, posing a high risk to the persistence of the Aneto Glacier, a situation that could extend to the rest of the Pyrenean glaciers in a relatively short time.

A lack of adequate high resolution climate proxy records for the Last Glacial Maximum (LGM) has prevented the extrapolation of climate–solar linkages on centennial time scales prior of the Holocene. Therefore, it is still unknown whether centennial climate variations of the last ten thousand years convey a universal climate change or merely represent a characteristic of the Holocene. Recently published high resolution climate proxy records for the LGM allowed us to extrapolate climate–solar linkages on centennial time scales ahead of the Holocene. Here we present the analysis of a high resolution pollen concentration record from Lake Kotokel in southern Siberia, Russia, during the LGM. The record reflects the dynamics of vegetation zones and temperature change with a resolution of ~ 40 years in the continental climate of north-eastern Asia. We demonstrate that our pollen concentration record, the oxygen isotope δ18O record from the Greenland ice core project NGRIP (NorthGRIP), the dust-fall contributions in Lake Qinghai, China, grain size in the Gulang and Jingyuan loess deposits, China, and the composite oxygen isotope δ18O record from the Alpine cave system 7H reveal cooler to warmer climate fluctuations between ~ 20.6 and 26 ka. Such fluctuations correspond to the ~ 1000-yr, 500-600-yr and 210-250-yr cycles possibly linked to the solar activity variations and recognized in high resolution Holocene proxies all over the world. We further show that climate fluctuations in the LGM and Holocene are spectrally similar suggesting that linkages between climate proxies and solar activity at the centennial time scale in the Holocene can be extended to the LGM. {"references": ["Vadim A. Kravchinsky, Rui Zhang, Ryan Borowiecki, Pavel E. Tarasov, Mirko van der Baan, Taslima Anwar, Avto Goguitchaichvili, Stefanie M\u00fcller, 2021. Centennial scale climate oscillations from southern Siberia in the Last Glacial Maximum. Quaternary Science Reviews, in press."]}