{ "@context": "http://schema.org/", "@type": "Dataset", "url": "https://antcat.antarcticanz.govt.nz/geonetwork/srv/eng/catalog.search#/metadata/7c6288b5-80e2-447d-8bdb-6e3cec4424e0", "includedInDataCatalog":{ "@type":"DataCatalog", "url":"https://antcat.antarcticanz.govt.nz/geonetwork/srv/" }, "inLanguage":"eng", "name": "Antarctic Daily Mesoscale Air Temperature Dataset Derived from Remotely Sensed Land and Ice Surface Temperature \u2013 AntAir ICE", "dateCreated": "2023-11-27T00:00:00", "datePublished": "2023-11-27T00:00:00", "thumbnailUrl": "https://antcat.antarcticanz.govt.nz:/geonetwork/srv/api/records/7c6288b5-80e2-447d-8bdb-6e3cec4424e0/attachments/marwan_asp.png", "description": "AntAir ICE is an air temperature dataset for terrestrial Antarctica, the ice shelves, and the seasonal sea ice around Antarctica in a 1km2 spatial grid resolution and a daily temporal resolution available from 2003-2021. AntAir ICE was produced by modelling air temperature from MODIS ice surface temperature and land surface temperature using linear models. In-situ measurements of air temperature from 117 Automatic Weather Stations were used as the response variable. Each day has a bricked spatial raster with two layers, saved as a GeoTIFF format and in the Antarctic Polar Stereographic projection (EPSG 3031). The first layer is the predicted near surface air temperature for that day in degree Celsius * 10 and the second layer is the number of available MODIS scenes for that day ranging from 0 to 4. Areas with cloud contamination or without sea ice are marked with no data. Files for each year (2003-2021) are compressed with a ZIP files for each quarter.\n\nPython 3.8 was used for conversion of the MODIS products from HDF files to raster and all data handling and processing was thereafter done in R version 4.0.0. All data processing and modelling procedures are available as R scripts on a public Github repository: https:\/\/github.com\/evabendix\/AntAir-ICE. Using this code it is possible to download new available MODIS LST and IST scenes and apply the model to continue the near-surface air temperature dataset.\n\nRelated Publication: https:\/\/doi.org\/10.1038\/s41597-023-02720-z\n\nGET DATA: https:\/\/doi.org\/10.1594\/PANGAEA.954750", "identifier": { "@id": "https://doi.org/10.1594/PANGAEA.954750", "@type": "PropertyValue", "propertyID": "https://registry.identifiers.org/registry/doi", "value": "doi:10.1594/PANGAEA.954750", "url": "https://doi.org/10.1594/PANGAEA.954750" }, "keywords":[ "","AIR TEMPERATURE","WEATHER STATIONS","AWS","Passive Remote Sensing","MODIS","ANTARCTICA","ASP" ] ,"creator": { "@type":"Person" ,"name": "Bendix Nielsen, E." ,"email": "eva.nielsen@pg.canterbury.ac.nz" ,"contactPoint": { "@type" : "PostalAddress" } } ,"publisher": { "@type":"Organization" ,"name": "PANGAEA" ,"email": "info@pangaea.de" ,"contactPoint": { "@type" : "PostalAddress" } } ,"distribution": { "@type":"DataDownload", "contentUrl": "https://doi.org/10.1594/PANGAEA.954750", "encodingFormat": "WWW:LINK-1.0-http--link", "name": "Distribution Metadata" } ,"spatialCoverage": {"@type": "Place", "geo": [ {"@type": "GeoShape", "box": "-90.00 -160.00 -55.00 -40.00" }, {"@type": "GeoShape", "box": "-90.00 40.00 -55.00 160.00" }] } ,"temporalCoverage": "2003-01-01/2021-01-01" ,"license": "https://creativecommons.org/licenses/by/4.0/" , "citation": "Bendix Nielsen, E., Katurji, M., Zawar-Reza, P., Meyer, H., ( 2023 ) Antarctic Daily Mesoscale Air Temperature Dataset Derived from Remotely Sensed Land and Ice Surface Temperature – AntAir ICE. PANGAEA. https://doi.org/10.1594/PANGAEA.954750, Accessed: 2026-07-29+12:00" }