The Meteorological Assimilation Data Ingest System (MADIS), developed by The National Oceanic and Atmospheric Administration’s (NOAA) Office of Atmospheric Research (OAR) and the National Weather Service (NWS), extends NOAA’s observational networks by collecting, integrating, Quality Controlling (QC), and distributing observations from NOAA and non-NOAA organizations. MADIS partners with international agencies; federal, state, and local agencies (e.g. state Departments of Transportation); universities; volunteer networks; and the private sector (e.g. airlines, railroads) to integrate observations from their stations with those of NOAA. The end result of this partnering is a finer density, higher frequency global observational database. MADIS currently provides access to observations for over 60,000 surface stations worldwide. MADIS adds value to all observations it collects by reducing the many different formats of the data into a common format with uniform observational units and time steps and applying QC techniques to the observations to assess data validity. MADIS provides graphical displays, subscription services, and developer application interfaces for users requesting access to MADIS data and metadata. MADIS can also restrict access to data based on provider requirements. MADIS started as a research project in 2001 funded by both OAR and the NWS. On January 21, 2015 MADIS achieved operational status at the NWS’ National Centers for Environmental Prediction (NCEP) Central Operations (NCO) as part of the Integrated Dissemination Program (IDP) with the MADIS archive housed at the National Environmental Satellite, Data, and Information Service (NESDIS) National Centers for Environmental Information (NCEI). Having achieved operational status MADIS has been leveraged by NOAA as a conduit or pathway for other observational systems to transition to operations. The NWS’ Hydrometeorological Automated Data System (HADS), Automated Flood and Warning System (AFWS), and SNOw TELemetry (SNOTEL) system were fully transitioned to MADIS. Combining these systems allows for the bigger combined system to take advantage of the strengths of each individual system to improve pathways and information flowing to the end-users and speed the process of getting changes to the field. Part of this talk will discuss what the improvements are and what is left to do to realize these improvements in operations. NOAA’s Unmanned Aircraft Systems (UAS) Sensing Hazards with Operational Unmanned Technology (SHOUT) project reached out to MADIS for a concept of operations to capture real-time data from the remote sensing systems available during flight and the ability to archive the data for future use. This talk will also focus on what was achieved and available today and what is left to do to fully realize the SHOUT remote sensing capabilities in MADIS.
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