1B.6 Current Status of Clarus Functionality in the NWS’ Meteorological Assimilation Data Ingest System (MADIS)

Monday, 13 January 2020: 9:45 AM
209 (Boston Convention and Exhibition Center)
Leon Benjamin, CIRES/Univ. of Colorado, Boulder, CO; and G. Pratt

The Federal Highway Administration (FHWA) Clarus initiative was designed to provide broader weather information support for surface transportation system operators in their efforts to improve safety, reliability and security of transportation users. MADIS has been a crucial data delivery system for the National Weather Service’s (NWS) Weather Forecast Offices (WFO) for many years. On a daily basis, NWS forecasters and many other users utilize MADIS data to refine and improve information to protect life and property. MADIS is an essential capability allowing NOAA to collect and identify high quality observations which form the foundation of NOAA’s Numerical Weather Prediction (NWP) digital analysis and verification processes. MADIS, like Clarus, ingests, QCs, and disseminates observations for operational decision support. The operational needs for improved situational awareness from both a NOAA and DOT perspective made MADIS the choice for the FHWA’s Clarus initiative to move from research to operations.

An Interagency Agreement (IA) was signed by NOAA and FHWA to start the transition effort the second Quarter of Fiscal Year 2013 (2QFY13). The effort of transitioning Clarus functionality to MADIS was put on hold while MADIS was being transitioned from research to operations (2013 – 2015). MADIS was declared operational at the NWS National Centers for Environmental Prediction (NCEP) Central Operations (NCO) as part of the Integrated Dissemination Program (IDP) in January of 2015 and Clarus transition efforts to MADIS started in late calendar year 2015. The Clarus functionality to be added to MADIS consisted of the following:

  • Enhancing MADIS to handle all Clarus observations types and metadata.
  • Enhance MADIS to handle multiple like observation types from one site.
  • Add and maintain RWIS contributors.
  • Enhancing MADIS graphical display capabilities to handle RWIS observations and metadata.
  • Enhancing MADIS subscription services for users to acquire RWIS observations.
  • Enhancing MADIS to handle Clarus QC algorithms.

The biggest enhancements to MADIS to handle Clarus functionality were for handling all RWIS observations, multiple like observations from one site, and Clarus QC algorithms. The MADIS software release in early 2018 provided the infrastructure enhancements required to handle these items. This talk will high-light the current status of the above three enhancements to MADIS and future work to complete these tasks. The talk with focus on the user interfaces for displaying and retrieving the RWIS data and metadata from MADIS.

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