Assessing lagged convective-scale weather ensembles for improved flood forecasting in fast-responding catchments

High-resolution ensemble weather forecasts are essential for forecasting floods in complex topography with fast-responding catchments. However, they are computationally expensive. This study explores a cost-effective alternative via the use of time-lagged ensembles, defined as ensemble forecasts from the same model initialised at different times but verifiying at the same time.

We evaluate lagged ensemble products, with varying configurations and proportions of lagged members, constructed from convective-scale numerical weather predictions (NWP) ensembles to forecast extreme flood events for fast-responding catchments. We compare four lagged products for two extreme event case studies in France and New Zealand. Lagged NWP ensemble products are used to drive hydrological models and evaluate flood forecasts across a range of performance evaluations based on traditional event-based metrics and user-focused strategies. We construct forecast diagrams and associated metrics based on the Brier Score for varying flood threshold severities to evaluate anticipatory and overly alarmist predictions.  

Comparisons with a control burst ensemble (without any lagging) reveal that flood forecasts derived from lagged convective-scale NWP ensembles have the potential to better capture extreme flood events, albeit with some limitations. Benefits vary with time and lagged product configuration, but generally, lagged ensemble products match or surpass their control counterparts, particularly in spread-skill, anticipatory prediction of a severe flood threshold, and consistency of forecasts -- critical to retaining trust from the emergency management sector. However, lagged products tend to increase overly alarmist predictions at early forecast ranges but become a more effective strategy at longer ranges over a larger region.

Utilising forecast diagram metrics based on the Brier Score allows the evaluation of multiple basins and ensemble products, incorporating an end-user-focused perspective for decision-making, such as anticipation of flood exceedance thresholds. The results provide valuable insights into lagged convective-scale weather ensembles' potential benefits and limitations in enhancing flood forecasting accuracy and reliability.