  Forecast verification is critical for continuous improvement in
meteorological organizations. The Jive verification system was originally
developed to assess the accuracy of public weather forecasts issued by the
Australian Bureau of Meteorology. It started as a research project in 2015 and
gradually evolved to be a Bureau operational verification system in 2022. The
system includes daily verification dashboards for forecasters to visualize
recent forecast performance and "Evidence Targeted Automation" dashboards for
exploring the performance of competing forecast systems. Additionally, there is
a Jupyter Notebook server with the Jive Python library which supports research
experiments, case studies, and the development of new verification metrics and
tools.
  This paper describes the Jive verification system and how it helped bring
verification to the forefront at the Bureau of Meteorology, leading to more
accurate, streamlined forecasts. Jive has been used to provide evidence to
support forecast automation decisions and has helped to understand the evolving
role of meteorologists in the forecast process. It has given operational
meteorologists tools for evaluating forecast processes, including identifying
when and how manual interventions lead to superior predictions. Work on Jive
led to new verification science, including novel metrics that are
decision-focused, including for extreme conditions. Jive also provided the
Bureau with an enterprise-wide data analysis environment and has prompted a
clarification of forecast definitions.
  These collective impacts have resulted in more accurate forecasts, ultimately
benefiting society, and building trust with forecast users. These positive
outcomes highlight the importance of meteorological organizations investing in
verification science and technology.
