Model-Based Systems Engineering Digital Twin: Capabilities-Based Requirements Analysis of the Advanced Quantitative Precipitation Information System

The Advanced Quantitative Precipitation Information (AQPI) System provides San Francisco Bay Area users with a single source of meteorological observations ranging from national weather model forecasts to local high resolution radar quantitative precipitation estimations (QPE). As a complex and sociotechnical system, AQPI lends itself to following the Complex, Large-scale, Interconnected, Open, Sociotechnical (CLIOS) process defined by Joseph Sussman. Following the CLIOS process and separating the physical model from the institutional sphere, a systems engineering approach naturally aligns with the Model-Based Systems Engineering (MBSE) methodology. Using block diagrams and internal block diagrams to capture the physical system, the engineer expresses the institutional sphere using behavioral modeling of use cases and activity diagrams. An MBSE behavioral analysis model for AQPI was developed in 2021 based upon the project concept. This preliminary model defined a foundation for the development of an AQPI Digital Twin.Systems mature from concept through implementation, and Digital Twins are no different. In 2022, AQPI hosting transitioned from National Oceanic and Atmospheric Administration (NOAA) to the Cooperative Institute for Research in the Atmosphere (CIRA). With the completion of the transition, the AQPI model required an update to match implementation as of April 2023. Using capabilities-based requirements analysis, the updated AQPI model matures a step closer to becoming the Digital Twin of the AQPI system and a single source of truth for development and system evaluation in support of operations and maintenance.