Recent upgrades to the Met Office convective‐scale ensemble: An hourly time‐lagged 5‐day ensemble

Abstract

AbstractIn this article, we introduce a new configuration of the Met Office convective‐scale ensemble for numerical weather prediction, for the Met Office Global and Regional Ensemble Prediction System over the United Kingdom (MOGREPS‐UK). The new version, which became operational in March 2019, uses an hourly time‐lagged configuration to take advantage of the hourly 4D‐Var data assimilation run in the deterministic UK model with variable horizontal resolution, the UKV. An 18‐member ensemble is created by running three members every hour and time‐lagging these over a 6 hr window. This configuration is compared against the previous operational configuration, a 6‐hourly convective‐scale ensemble running 12 members. The main benefits of the time‐lagged ensemble are to increase the ensemble size, to add small‐scale uncertainties in the initial conditions and to generate more timely forecasts. The time‐lagged configuration is shown to objectively improve the forecast at all lead times, with larger improvements in the first few hours. The improvement is seen in the ranked probability scores and is mainly associated with the improvements in the spread of the ensemble with an increase of about 5 to 10% in both summer and winter seasons. A larger ensemble size is necessary in the time‐lagged configuration for it to outperform or maintain as good a performance against the previous 6‐hourly configuration for all lead times. Alongside the update to an hourly configuration, the forecast length is more than doubled to 120 hr. Objective verification shows that the time‐lagged configuration performs better than the high‐resolution deterministic, UKV, and the global ensemble, MOGREPS‐G, up to T + 120 hr. Increasing the size of the time‐lagged ensemble through lagging over additional cycles leads to small but significant improvements, larger in most cases than those that can be obtained through neighbourhood processing.