Multi-University Consortium for Advanced Data Assimilation Research and Education (CADRE)

Data assimilation (DA) plays a critical role in Earth system prediction, and faces significant challenges associated with the next generation high-resolution, multiscale, coupled earth system modeling and a large amount of diverse and complex observations. The recent promises of data-driven weather prediction through advancement of machine learning and artificial intelligence also suggest new opportunities for data assimilation. However, serious gaps in DA workforce and the lack of sustained innovative DA research support inhibit addressing these challenges as well as reacting to the new opportunities.

In this presentation, the trans-disciplinary nature of DA and challenges of DA associated with the next generation Earth system prediction will be discussed first. A new Multi-University Consortium for Advanced Data Assimilation Research and Education (CADRE), recently funded by NOAA, is then introduced. CADRE is led by University of Oklahoma and is in close partnership with Howard University, Pennsylvania State University, the University of Maryland, Colorado State University, and the University of Utah. Additionally, University of Illinois Urbana-Champaign, State University of New York at Albany and City College of New York will participate as non-funded university partners. CADRE will perform innovative DA research towards improving forecasts from short range to S2S (sub-seasonal to seasonal) scales and will develop the next generation of DA workforce. CADRE will achieve these goals through its comprehensive and integrated research, education, outreach and R2O2R program and close collaboration with NOAA including its OAR lab, NWS centers and EPIC, JCSDA (Joint Center for Satellite Data Assimilation), UK Met Office Academic Partnership (MOAP) program (e.g. University of Reading), TDSA (Transatlantic Data Science Academy), and other weather enterprise partners. CADRE seeks to achieve the following goals: (1) Increasing the number of graduate students and postdocs formally trained in DA with NOAA UFS and JEDI DA system work experience; (2) Enhancing the national and international DA workforce pipeline development through training and outreach focusing on diversity and inclusion; (3) Seeking solutions through JEDI to challenging DA issues in the UFS short range (RRFS, HAFS), medium range (GFS) and sub-seasonal to seasonal (S2S) predictions; and (4) Promoting intellectual and technical exchanges in R2O and O2R. More detailed plans and progress made will be discussed at the conference.