Development of skills needed to prepare for work in data assimilation for earth system analysis and prediction

Data assimilation has been critical for advancements in the so-called NWP quiet revolution (Bauer et al. 2015). The field of DA for Earth system analysis and prediction continues to evolve to address some of the current challenges such as evolution to multiscale, coupled assimilation, handling nonlinearity and non-Gaussianity, representation and estimation of system uncertainty, processing and assimilating the growing volumes and types of observational data, and integration of artificial intelligence. The Environmental Modeling Center at the National Centers for Environmental Prediction (part of NOAA’s National Weather Service) recently published its long term development plans for future operational DA for numerical weather prediction (Kleist et al., 2024, doi: https://doi.org/10.25923/kqra-6z66) and highlighted the need to “recruit, integrate, and retain the world’s best scientists in our field”. As the field of data assimilation is fundamentally inter- and trans-disciplinary in nature, NOAA will need to recruit individuals with a broad set of skills, theory, and technical experience. The establishment of the new multi-university Consortium for Advanced Data Assimilation Research and Education (CADRE) brings a unique opportunity to focus the development of skills for the next generation of data assimilation scientists. This presentation will highlight some of the skills that individuals need to be successful in the field of DA for applications at NOAA and outline a vision for a future pipeline of DA (and related) scientists to fulfill the promise of bringing better operational predictions of hazardous weather.