<h1>Dunbar, Oliver</h1> <h2>Monograph from <a href="https://authors.library.caltech.edu">CaltechAUTHORS</a></h2> <ul> <li>Lopez-Gomez, Ignacio and Christopoulos, Costa, el al. (2022) <a href="https://resolver.caltech.edu/CaltechAUTHORS:20220331-531674000">Training physics-based machine-learning parameterizations with gradient-free ensemble Kalman methods</a>; <a href="https://doi.org/10.1002/essoar.10510937.2">10.1002/essoar.10510937.2</a></li> <li>Bieli, Melanie and Dunbar, Oliver R. A., el al. (2022) <a href="https://resolver.caltech.edu/CaltechAUTHORS:20220207-89642000">An efficient Bayesian approach to learning droplet collision kernels: Proof of concept using "Cloudy", a new n-moment bulk microphysics scheme</a>; <a href="https://doi.org/10.1002/essoar.10510248.1">10.1002/essoar.10510248.1</a></li> <li>Dunbar, Oliver R. A. and Howland, Michael F., el al. (2022) <a href="https://resolver.caltech.edu/CaltechAUTHORS:20220119-572479000">Ensemble-Based Experimental Design for Targeted High-Resolution Simulations to Inform Climate Models</a>; <a href="https://doi.org/10.1002/essoar.10510142.1">10.1002/essoar.10510142.1</a></li> </ul>