{"data":{"id":"10.4121/d0a8c82f-346f-45b7-82ca-2b9e27604414","type":"dois","attributes":{"doi":"10.4121/d0a8c82f-346f-45b7-82ca-2b9e27604414","prefix":"10.4121","suffix":"d0a8c82f-346f-45b7-82ca-2b9e27604414","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Marleen van Soest","givenName":"Marleen","familyName":"van Soest","affiliation":[],"nameIdentifiers":[]},{"name":"Stephan de Roode","nameType":"Personal","givenName":"Stephan","familyName":"de Roode","nameIdentifiers":[{"nameIdentifier":"0000-0003-3217-8009","nameIdentifierScheme":"https://orcid.org/"}],"affiliation":[]},{"name":"Ardjan Sturm","nameType":"Personal","givenName":"Ardjan","familyName":"Sturm","nameIdentifiers":[{"nameIdentifier":"0000-0002-0377-1316","nameIdentifierScheme":"https://orcid.org/"}],"affiliation":[]},{"name":"Harm Jonker","givenName":"Harm","familyName":"Jonker","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"ASPIRE data and code for machine learned ecRad surrogate models"}],"publisher":"4TU.ResearchData","container":{},"publicationYear":2026,"subjects":[{"subject":"Atmospheric Sciences","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"0401"},{"subject":"Atmosphere and Weather","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"9602"},{"subject":"Earth Sciences","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"04"},{"subject":"Environment","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"96"},{"subject":"radiative transfer"},{"subject":"machine learning"},{"subject":"Regional weather model"},{"subject":"cloud radiative effect"},{"subject":"Time: 180 scenes in 60 days in 2024 at 9:00, 12:00, 15:00 local time in Australia, and 36 scenes in 12 days in 2024 at 9:00, 12:00, 15:00 local time in the Netherlands"}],"contributors":[{"name":"TU Delft, Faculty of Civil Engineering and Geosciences, Department of Geoscience and Remote Sensing, Atmospheric Remote Sensing","nameType":"Organizational","contributorType":"Other","affiliation":[],"nameIdentifiers":[]},{"name":"Whiffle B.V., Delft","nameType":"Organizational","contributorType":"Other","affiliation":[],"nameIdentifiers":[]}],"dates":[{"date":"2026-10-20","dateType":"Issued"}],"language":"en","types":{"ris":"COMP","bibtex":"misc","citeproc":"article","schemaOrg":"SoftwareSourceCode","resourceType":"Software","resourceTypeGeneral":"Software"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.4121/d0a8c82f-346f-45b7-82ca-2b9e27604414.v1","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["netCDF"],"version":"1","rightsList":[{"rights":"Creative Commons Zero v1.0 Universal","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc0-1.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Datasets and python code for the training and testing of ecRad surrogate models. The input data is output of the mesoscale atmospheric model ASPIRE and embedded ecRad scheme for 180 scenes in 60 days in 2024. The domain is 240 m x 240 km x 20 km, the horizontal resolution is 2 km x 2 km, and the vertical grid size increases from 50 m at the surface to 100 m at the top of the domain, with a total of 128 vertical levels. A detailed description can be found in the readme.txt file.","descriptionType":"Abstract"}],"geoLocations":[{"geoLocationPlace":"Brisbane, Australia and Cabauw, the Netherlands"}],"fundingReferences":[{"awardTitle":"Renewable Energy Forecasts from Observations and high-Resolution Modeling project (REFORM)","funderName":"Dutch Research Council NWO","awardNumber":"18657"}],"xml":"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