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32 results for “2022 Weather”
Publications from government weather and climate authorities on the X platform and replies from citizens in five Brazilian cities during a year between 2021 and 2022
<p>This dataset contains messages published and replies received by government weather and climate authorities on the X (former Twitter) social media platforms. The data comprises government weather and climate authorities for the Brazilian cities of São Paulo, Rio de Janeiro, Belo Horizonte, Porto Alegre, and Belém. Government weather and climate authorities are city hall departments or sectors responsible for informing and keeping the population updated about weather events.</p><p>Publications made by the authority and replies published by citizens to these publications are observed. This data supports the study on the interaction dynamics between the climate authority and citizens over time.</p><p><strong>Data Structure</strong></p><p>Two files are available <strong>publications.csv</strong> and <strong>replies.csv</strong>.</p><p>Each line in the publications' file (<strong>publications.csv</strong>) refers to an authority publication/tweet. For each publication, it is stored the public authority's unique Twitter identifier (<i>AUTHORITY_ID</i>), the tweet unique identifier (<i>TWEET_ID</i>), the Unix timestamp that indicates when it was published (<i>TIMESTAMP</i>), and the text of the publication (<i>TEXT</i>). </p><p>Each line in the replies file (<strong>replies.csv</strong>) is a reply from a citizen to an authority. For each reply, it is stored the authority's unique Twitter identifier (<i>AUTHORITY_ID</i>), the unique identifier of the authority's tweet being replied to (<i>TWEET_ID</i>), the replier masked unique Twitter identifier (<i>AUTHOR_ID</i>), and the reply Unix timestamp (<i>TIMESTAMP</i>) that indicates when it was published.</p><p>All data were collected through the X's application programming interface (API) provided to scientific researchers. Publications and replies were posted by users (authorities and citizens) with public visibility.</p><p><strong>Data Content</strong></p><p>The dataset covers 1-year observation period, starting on July 17, 2021, and ending on June 16, 2022. It contains a total of 10,229 publications and 5,471 replies. The observed authorities are as follows:</p><p> </p><p><strong>City Authority name X handle </strong><i><strong>AUTHORITY_ID</strong></i></p><p>São Paulo Centro de Gerenciamento de Emergências Climáticas da Prefeitura de SP <i>@cge_sp </i>268407434</p><p>Rio de Janeiro Sistema de Alerta localizado no Centro de Operações do Rio (COR) @<i>alertario </i>87487749</p><p>Belo Horizonte Defesa Civil de Belo Horizonte @<i>defesacivilbh </i>837731966</p><p>Porto Alegre Defesa Civil Porto Alegre @<i>defesacivilpoa </i>1037420896473022466</p><p>Belém Defesa Civil de Belém @<i>defesacivilbel </i>1346501728632500225</p><p> </p><p>As weather and climate authorities are government bodies, the whole content of their publications is of public interest according to Brazilian law. Thus, the text messages in their publications on social media are in the public domain and are stored in this dataset. As the data structure describes, text messages of citizens' replies are not stored. According to the terms of use of the X platform, citizen text messages cannot be publicly stored outside the X platform. Such text messages are public on that platform, and, for reproductivity, they can be recollected using the platform web page or API informing the <i>TWEET_ID</i> stored in this dataset.</p>
TEAMx-PC22 (TEAMx pre-campaing 2022) - ACINN automatic weather station data set from Nafingalm
<p><strong>ABSTRACT</strong></p> <p>This data set was collected with an automatic weather station (AWS) of <a href="http://acinn.uibk.ac.at/">ACINN</a> at the Nafingalm, Austria, in summer 2022 in the framework of the TEAMx pre-campaign 2022 (TEAMx-PC22). The aim of TEAMx-PC22 was to test new instruments, new instrument configurations and new measurement sites to support the planning of the main TEAMx observational campaign (TOC) in 2024/2025. More details about TEAMx can be found at <a href="http://www.teamx-programme.org">http://www.teamx-programme.org</a> as well as in Serafin et al. (2020) and in Rotach et al. (2022).</p> <p><strong>DATA SET DESCRIPTION</strong></p> <p><strong>1. Location</strong></p> <p>The AWS was located close to a small lake at the Nafinglam in the Weer Valley, Tyrol, Austria. The exact location is: 47.2151419°N / 11.712628°E / 1928 m MSL</p> <p><strong>2. Period</strong></p> <p>The TEAMx-PC22 lasted from mid-May 2022 to early October 2022. However, the AWS data set provided here contains the period from 15 June to 12 September 2022. The time series has a measurement interval of 5 minutes and, depending on the parameter, contains both mean values and instantaneous values.</p> <p><strong>3. Instrument details</strong></p> <p>A detailed description of the AWS, its sensors, parameters, calibration and correction procedures is provided as part of the netCDF file metadata, as well as in a PDF file containing the netCDF header extracted with the Linux command ncdump -h.</p> <p><strong>4. Data file</strong></p> <p>The data are provided in a single netCDF file teamx_pc22_aws_nafingalm.nc together with a description of its content in the PDF file teamx_pc22_aws_nafingalm_ncdump_output.pdf.</p> <p><strong>5. Analysis</strong></p> <p>A first analysis of the data was performed in a Bachor thesis (Viebahn, 2023), which is available upon request from the first author of this data set.</p> <p><strong>6. Contact</strong></p> <p>Contact alexander.gohm(at)uibk.ac.at for any questions regarding the data set.</p> <p><strong>7. References</strong></p> <p>Rotach, M. W., S. Serafin, H. C. Ward, M. Arpagaus, I. Colfescu, J. Cuxart, S. F. J. D. Wekker, V. Grubišic, N. Kalthoff, T. Karl, D. J. Kirshbaum, M. Lehner, S. Mobbs, A. Paci, E. Palazzi, A. Bailey, J. Schmidli, C. Wittmann, G. Wohlfahrt, D. Zardi, 2022: A collaborative effort to better understand, measure, and model atmospheric exchange processes over mountains. <em>Bulletin of the American Meteorological Society</em>, <strong>103</strong>, E1282–E1295. <a href="https://doi.org/10.1175/bams-d-21-0232.1">https://doi.org/10.1175/bams-d-21-0232.1</a></p> <p>Serafin, S., M. W. Rotach, M. Arpagaus, I. Colfescu, J. Cuxart, S. F. J. De Wekker, M. Evans, V. Grubišić, N. Kalthoff, T. Karl, D. J. Kirshbaum, M. Lehner, S. Mobbs, A. Paci, E. Palazzi, A. Raudzens Bailey, J. Schmidli, G. Wohlfahrt, B. Zardi, 2020: <em>Multi-scale transport and exchange processes in the atmosphere over mountains: Programme and experiment</em>. Innsbruck University Press. <a href="https://doi.org/10.15203/99106-003-1">https://doi.org/10.15203/99106-003-1</a></p> <p>Viebahn, T., 2023: <em>Windregime und Stabilität in einem alpinen Seitental im Sommer: Eine Standortcharakterisierung im Rahmen der TEAMx Vorkampagne 2022.</em> Bachlor thesis, University of Innsbruck, 75 pp.</p>
Weather data from Langebaanweg, South Africa, from 2015 to 2022
<p>Weather data from Langebaanweg, South Africa, from 2015 to 2022. The measurement location is latitude -32.9720 and longitude 18.1570. The dataset contains the hourly measurements of the wind speed, the wind direction, and the rainfall. </p>
Forecasting Capability Verification of the Pangu-Weather and ECMWF Models for the 2022 Summer Weather in Jiangsu Province, China
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Distinct New Particle Formation and Growth Events under Heatwave Weather of Summer 2022 at Urban Chongqing, Southwest China
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Data from Automatic Weather Station (AWS) measurements at Berlin–Mobile deployment (BEMOBI) from 2022-03-22 to 2022-08-13 [RAW]
<p>Original data files from AWS measurements.</p>
Data from Automatic Weather Station (AWS) measurements at Berlin – Gropiusstadt (BEGROP) from 2022-01-28 to 2022-10-20 [RAW]
<p>Original data files from AWS measurements.</p>
Data from Automatic Weather Station (AWS) measurements at Berlin – Friedrichstadt (BEFRIE) from 2021-07-15 to 2022-10-06 [RAW]
<p>Original data files from AWS measurements.</p>
Data from Automatic Weather Station (AWS) measurements at Berlin – Wedding (BEWEDD) from 2021-10-26 to 2022-10-12 [RAW]
<p>Original data files from AWS measurements.</p>
Data from Automatic Weather Station (AWS) measurements at Berlin – Westend (BEWEST) from 2021-11-25 to 2022-10-14 [RAW]
<p>Original data files from AWS measurements.</p>
Data from Automatic Weather Station (AWS) measurements at Berlin–Grunewald (BEGRUN) from 2022-05-10 to 2022-10-17 [RAW]
<p>Original data files from AWS measurements.</p>
Data from Automatic Weather Station (AWS) measurements at Berlin – Märkisches Viertel (BEMAVI) from 2022-06-23 to 2022-10-21 [RAW]
<p>Original data files from AWS measurements.</p>
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.