Improving Weather and Climate Predictions by Training of Supermodels

The authors of this weather-and-climate study did not resist the allure of shiny words:

“Improving Weather and Climate Predictions by Training of Supermodels,” Francine Schevenhoven, Frank Selten, Alberto Carrassi, and Noel Keenlyside, Earth System Dynamics, epub 2019. (Thanks to Tom Gill for bringing this to our attention.) The authors, at the University of Bergen, Norway, Bjerknes Centre for Climate Research, Bergen, Norway, Royal Netherlands Meteorological Institute, and Nansen Environmental and Remote Sensing Center, Bergen, Norway, report:

“Recent studies demonstrate that weather and climate predictions potentially improve by dynamically combining different models into a so called “supermodel”. Here we focus on the weighted supermodel – the supermodel’s time derivative is a weighted superposition of the time-derivatives of the imperfect models, referred to as weighted supermodeling….  Here we apply two different training methods to a supermodel of up to four different versions of the global atmosphere-ocean-land model SPEEDO.”