A process and system for managing the metadata needed to better understand and use the observations in Numerical Weather Prediction and Operational Decision Support

The National Oceanic and Atmospheric Administration's Meteorological Assimilation Data Ingest System (MADIS) collects, decodes, processes, quality controls, and distributes automated weather reports collected from commercial aircraft worldwide. These data are known as AMDAR (Aircraft Meteorological Data Relay) data. AMDAR data provide high-quality upper air observations and profiles at airports from a number of sensors. AMDAR data are used operationally by weather forecasters, the FAA, in numerical weather prediction models, decision support systems, etc. To optimally use AMDAR data, many different types of metadata are needed from many different sources. To meet the requirements of AMDAR data users, these metadata need to be published in several different formats including ISO metadata records in XML, Product Description documents (PDD) in Microsoft Word, JSON, Text, and other formats as needed for automated processing of the data. The types of metadata needed in addition to the typical ISO metadata include aircraft observation processing metadata, ARINC processing metadata, and MADIS processing metadata. Additionally, feedback (another form of metadata) along the processing chain down to the end user needs to be maintained. How well do these AMDAR data and metadata meet the end user's needs? Historically, AMDAR metadata has been collected and made available to users of the data through a manual process. This system proposes automating the collection, processing, quality control, and publishing of metadata for AMDAR data. Subscribers to AMDAR metadata will be notified of changes to the metadata and updated ISO metadata records and PDDs will be published.