{"url":"/dataset/automated-surface-weather-observing-systems","name":"ASOS Data","full_name":"Automated Surface/Weather Observing Systems (ASOS/AWOS) Data","description_markdown":"The Automated Surface Observing Systems (ASOS) program is a joint effort of the National Weather Service (NWS), the Federal Aviation Administration (FAA), and the Department of Defense (DOD). These automated systems collect observations on a continual basis, 24 hours a day. \r\n\r\nAutomated Weather Observing System (AWOS) units are operated and controlled by the Federal Aviation Administration. These systems are among the oldest automated weather stations and predate ASOS. They generally report at 20-minute intervals and, unlike ASOS, do not report special observations for rapidly changing weather conditions.\r\n\r\nASOS observations are operationally generated each hour, and special observations are provided whenever the weather changes. These special reports are generated when conditions exceed preselected weather element thresholds, e.g., the visibility decreases to less than 3 miles.","description_withheld":null,"homepage":"","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Time series","url":"/datasets/modality/time-series"}],"tasks":[{"name":"Solar Irradiance Forecasting","url":"/task/solar-irradiance-forecasting","datasets_with_task":"/datasets/task/solar-irradiance-forecasting"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ASOS Data"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/solar-irradiance-forecasting-on-automated","task":"Solar Irradiance Forecasting","dataset_variant":"ASOS Data","rows":1,"metrics":["Accuracy","MAE","MSE","R^2","Variance"],"first_row_in_archive_order":{"model":"MST-GCN","paper":"/paper/day-ahead-hourly-solar-irradiance-forecasting","metrics":{"Accuracy":"0.79","MAE":"0.12","MSE":"0.23","R^2":"0.94","Variance":"0.94"},"code_links":[{"title":"higd963/MST-GCN","url":"https://github.com/higd963/MST-GCN"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/day-ahead-hourly-solar-irradiance-forecasting","title":"Day-Ahead Hourly Solar Irradiance Forecasting Based on Multi-Attributed Spatio-Temporal Graph Convolutional Network","date":"2022-09-21","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}