Stratification of the vertical spread‐skill relation by radiosonde drift in a convective‐scale ensemble

Abstract

Abstract Ensemble forecasting systems provide useful insight into the uncertainty in the prediction of the atmosphere. However, most analysis considers ensembles in latitude, longitude, and time. Here, the vertical aspects of the spread‐skill relation are considered in a convective‐scale ensemble via comparisons with radiosonde ascents. The specific focus is on the impact of stratifying the spread‐skill relation by radiosonde drift. The drift acts as a proxy for the mobility of the atmosphere. The overall spread‐skill relation shows the temperature has a better relation than the dewpoint. However, the total variance comparisons between model and observations indicates that the dewpoint is underspread throughout the atmosphere, whilst the temperature is overspread through the lower atmosphere and underspread aloft. This suggests that the model bias is influencing the spread‐skill relation. Stratifying these results by the radiosonde drift indicates that the spread‐skill relation, and model bias, for both temperature and dewpoint degrades with increased mobility. For the most mobile situations, the ensemble is underspread throughout the atmosphere. These results have implications for ensemble design in terms of the role and influence of the driving ensemble in regional systems as more mobile situations will have a stronger dependence on the lateral boundary conditions. Longer term it may also imply that different strategies are required depending on the mobility of the synoptic conditions. Therefore, it argues for more consideration of “on‐demand” ensemble forecasting systems to allow a fairer representation of the uncertainty in different situations.

Keywords

• ensemble spread
• ensembles
• numerical weather prediction
• tephigrams
• United Kingdom