AI-Readiness of the Tropical Cyclone Precipitation, Infrared, Microwave, and Environmental Dataset (TC PRIMED)
The Tropical Cyclone Precipitation, Infrared, Microwave, and Environmental Dataset (TC PRIMED) is a dataset centered around tropical cyclone observations from low-Earth orbitting satellites that includes 1) inter-calibrated passive microwave observations, 2) retrieved rainfall, 3) coincident infrare...
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Zusammenfassung: | The Tropical Cyclone Precipitation, Infrared, Microwave, and Environmental Dataset (TC PRIMED) is a dataset centered around tropical cyclone observations from low-Earth orbitting satellites that includes 1) inter-calibrated passive microwave observations, 2) retrieved rainfall, 3) coincident infrared observations and derived metrics, 4) tropical cyclone track and intensity information, 5) ECMWF ERA5 fields and derived diagnostics, and 6) precipitation radar observations from the TRMM and GPM Core Observatory satellites. This extensive dataset covers a period from 1998 to 2019 and has the potential to improve our understanding of tropical cyclone processes and tropical cyclone forecasts. One of the ways in which TC PRIMED can contribute to tropical cyclone studies is through the application of artificial intelligence (AI) approaches. Here, we evaluate the AI-readiness of TC PRIMED and outline future work to improve its AI-readiness. This poster was presented at the July 2022 ESIP Meeting, held in Pittsburgh, PA. |
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DOI: | 10.6084/m9.figshare.20286513 |