Toward a Systematic Evaluation of Warm Conveyor Belts in Numerical Weather Prediction and Climate Models. Part II: Verification of Operational Reforecasts

Abstract Warm conveyor belts (WCBs) associated with extratropical cyclones transport air from the lower troposphere into tropopause region and contribute to upper-level ridge building formation of blocking anticyclones. Recent studies indicate that this constitutes an important source magnifier forecast uncertainty errors in numerical weather prediction (NWP) models. However, a systematic evaluation representation WCBs NWP models has yet be determined. Here, we employ logistic regression developed Part I identify inflow, ascent, outflow stages European Centre for Medium-Range Weather Forecasts (ECMWF) subseasonal reforecasts Northern Hemisphere winter period January 1997 December 2017. We verify these WCB terms occurrence frequency biases, reliability, skill. Systematic biases emerge already at early lead times around 3 days underestimation over North Atlantic eastern Pacific 40% relative climatology. Biases predictor variables can partially explain or outflow. Despite overconfidence predicting high probabilities, skillful forecasts are on average possible up time 8–10 more skill compared region. Our results corroborate current limited large-scale circulation scales beyond 10 might tied upscale error growth.