Normand Gagnon

TL;DR: The Subseasonal Experiment (SubX) as discussed by the authors is a multimodel subseasonal prediction experiment designed around operational requirements with the goal of improving sub-seasonal forecasts.

TL;DR: An updated global ensemble prediction system became operational at the Meteorological Service of Canada in July 2007 and includes the use of 20 members instead of 16, a single dynamical core, stochastic physical tendency perturbations and a kinetic energy backscatter algorithm, an ensemble Kalman filter with four-dimensional data handling, and a decrease in horizontal grid spacing.

TL;DR: In this paper, a new monthly forecasting system is set up based on the operational Global Ensemble Prediction System (GEPS), which is composed of two components: 1) the real-time forecast, where the GEPS is extended to 32 days every Thursday; and 2) a 4-member hindcast over the past 20 years, which is used to obtain the model climatology to calibrate the monthly forecast.

TL;DR: In this article, the impact of uncertainties in surface parameter and initial conditions on numerical prediction with the Canadian Regional Ensemble Prediction System (REPS) is assessed. And the sensitivity to these perturbations is quantified especially for 2-m temperature, 10-m wind speed, cloud fraction, and precipitation up to 48-h lead time.

TL;DR: It is legitimate to wonder whether improvements in terms of biases and dispersions, and by extension the skill improvements, are only due to the balancing between opposite model errors.