Rate My Professor Craig Bishop

Bishop’s pioneering ensemble-based data assimilation and ensemble-forecasting methods are implemented operationally by prominent institutions such as the European Centre for Medium-Range Weather Forecasts, UK Met Office, US National Weather Service, US Navy, and meteorological services in Japan, Korea, and Brazil. His contributions have significantly advanced numerical weather prediction globally. A Fellow of the American Meteorological Society since 2012, he is the founding co-chair of the World Meteorological Organization’s Working Group on Predictability, Dynamics and Ensemble Forecasting and serves as an associate editor for the Quarterly Journal of the Royal Meteorological Society. He previously chaired the Science Steering Committee of the Joint Center for Satellite Data Assimilation from 2007 to 2010, was elected to the International Commission on Dynamical Meteorology in 2010, and acted as Distinguished Visiting Scientist at the University of Reading in 2015. His current research centers on data assimilation science, leveraging models, observations, and estimation theory to initialize ensemble forecasts and quantify systematic and stochastic model errors. Notable publications include chapters in Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (2013) and articles such as “Ensemble Transform Kalman Filter-based ensemble perturbations in an operational global prediction system at NCEP” and “Implicit ensemble tangent linear models (IETLMs) for model differentiation” (2022).