Stratification of the Vertical Spread-Skill Relation by Radiosonde Drift in a Convective-Scale Ensemble

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 over a winter season. 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 under the climatolgical variance throughout the atmosphere, whilst the temperature is over the climatological variance in the lower atmosphere and under it aloft, suggesting that there could be temperatures that exist outside climatological expectations. 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.

Biography: David did his undergraduate degree at the University of Reading graduating in 2013. Following his undergraduate David completed his PhD and a short post-doc both at the University of Reading on behaviour of convective-scale ensembles. David then moved to Paris for two years as a post-doc at École Normale Supérieure as part of the Laboratoire de Météorologie Dynamique evaluating extra-tropical cyclones in climate models. In March 2020 David joined the Met Office where he started in Regional Model Evaluation and Development (RMED). Since April 2024 he has a split role between RMED and Weather and Climate Impact and Extremes.