FSL to Share Observations and Observation-handling Technology
A new project has been established at FSL for the purpose of supporting meteorological research by sharing FSL observations and observation-handling technology with the greater meteorological community. The project, known as MADIS (the Meteorological Assimilation Data Ingest System), is dedicated toward making value-added data available from FSL's Central Facility with the goal of improving weather forecasting, by providing support for data assimilation, numerical weather prediction, and other hydrometeorological applications.
MADIS subscribers have access to a reliable and easy-to-use database containing real-time and archived datasets available via either FTP or by using Unidata's Local Data Manager (LDM) software. Quality Control (QC) of MADIS observations is also provided, since considerable evidence exists that the retention of erroneous data, or the rejection of too many good data, can substantially distort forecast products. Observations in the FSL database are stored with a series of flags indicating the quality of the observation from a variety of perspectives (e.g. temporal consistency and spatial consistency), or more precisely, a series of flags indicating the results of various QC checks. Users of MADIS can then inspect the flags and decide whether or not to ingest the observation.
MADIS also includes an Application Program Interface (API) that provides users with easy access to the data and quality control information. The API allows each user to specify station and observation types, as well as QC choices, and domain and time boundaries. Many of the implementation details that arise in data ingest programs are automatically performed. Users of the MADIS API, for example, can choose to have their wind data automatically rotated to a specified grid projection, and/or choose to have mandatory and significant levels from radiosonde data interleaved, sorted by descending pressure, and corrected for hydrostatic consistency.
The API is designed so that the underlying format of the database is completely invisible to the user, a design that also allows it to be easily extended to other databases. In the initial version of the API, support is provided for the FSL database, and also for the database used in the National Weather Service (NWS) Advanced Weather Interactive Processing System (AWIPS) deployed at NWS weather forecast offices.
The FSL MADIS database and API are freely available to interested parties in the meteorological community. Datasets available in the initial version of MADIS include radiosonde, automated aircraft, wind profiler, and surface datasets. The latter includes over 3500 mesonet stations from local, state, and federal agencies, and private firms. Organizations already receiving MADIS datafeeds include the National Center for Atmospheric Research and the NWS's National Centers for Environmental Prediction. For more information. see the MADIS web pages.
Name: Patty Miller