Warm conveyor belts as amplifiers of forecast uncertainty

Abstract

Warm conveyor belts (WCBs) are rapidly ascending air streams associated with extratropical cyclones. WCBs exert a substantial influence on the evolution of the large-scale midlatitude flow and have previously been related to increased forecast uncertainty in case studies. This study provides a first systematic investigation of the role of WCBs for errors in medium-range ensemble forecasts in the Atlantic–European region. The study is enabled through a unique data set, allowing for a Lagrangian detection of WCBs in three years of operational ensemble forecasts from the European Centre for Medium-Range Weather Forecasts. By analysing the relationship between commonly used error metrics of variables that characterise the large-scale flow and WCBs, the study aims to shed light on the question of the extent to which WCBs act as a source of forecast errors and as an amplifier of pre-existing errors in a state-of-the-art global operational numerical weather prediction model. We show that forecasts with high WCB activity are on average characterised by an amplified Rossby-wave pattern and anticyclonic flow anomalies downstream. We find that the forecast skill is generally reduced when the WCB activity is high, and that WCB activity is particularly increased when the error growth is largest. To establish a causal relationship, we employ two composite approaches. The first focuses on the time of largest error growth and the second calculates normalised forecast error fields centered on WCB objects. Both approaches yield a consistent picture: anomalously high errors are initially associated with misrepresentations of an upstream trough. In regions of WCB ascent and outflow, the errors grow rapidly in terms of magnitude and scale and are projected onto the upper-level large-scale circulation. We also find indications that WCBs can cause errors even when the upstream flow is well represented. Notwithstanding, evidence is robust for WCBs acting as an amplifier of forecast uncertainty.