The Tropical Cyclone PRecipitation, Infrared, Microwave, and Environmental Dataset (TC PRIMED) team published a Python package (https://pypi.org/project/ tcprimedapi/1.0a0/) to help users navigate and access the dataset on its Amazon Web Service (AWS) Simple Storage Service (S3) bucket (https://noaa-nesdis-tcprimed-pds.s3.amazonaws.com/ index.html#v01r01/). TC PRIMED is an artificial-intelligence-ready dataset that collocates disparate sources of tropical cyclone data for algorithm development and verification (https://rammb-data.cira.colostate.edu/tcprimed/). Through the support of the NOAA Center for Artificial Intelligence, TC PRIMED was made publicly available on the AWS S3 bucket as part of the NOAA Open-Data Dissemination (NODD) program. The Python package facilitates easier access to TC PRIMED data on the AWS S3 bucket by allowing users to query and retrieve data based on the a) tropical cyclone season, basin and/or number, b) TC PRIMED file type (i.e., particular satellite, sensor, or TC PRIMED environmental files), c) dates, and/or d) version type (final or preliminary). Users can look at examples of its application on its GitHub repository (https://github.com/ CSU-CIRA/tcprimedapi/).
(POC: Naufal Razin, CIRA, Naufal.Razin@colostate.edu, Chris Slocum, STAR, 970-491-2409, Christopher.Slocum@noaa.gov. Funding: ONR/NCAI)
The Regional and Mesoscale Meteorology Branch (RAMMB) of NOAA/NESDIS conducts research on the use of satellite data to improve analysis, forecasts and warnings for regional and mesoscale meteorological events. RAMMB is co-located with the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University in Fort Collins, CO.
