Evaluation of the Added Value of Probabilistic Nowcasting Ensemble Forecasts on Regional Ensemble Forecasts

Abstract

Ensemble forecasting systems have become an important tool for estimating the uncertainties in initial conditions and model formulations and they are receiving increased attention from various applications. The Regional Ensemble Prediction System (REPS), which has operated at the Beijing Meteorological Service (BMS) since 2017, allows for probabilistic forecasts. However, it still suffers from systematic deficiencies during the first couple of forecast hours. This paper presents an integrated probabilistic nowcasting ensemble prediction system (NEPS) that is constructed by applying a mixed dynamic-integrated method. It essentially combines the uncertainty information (i.e., ensemble variance) provided by the REPS with the nowcasting method provided by the rapid-refresh deterministic nowcasting prediction system (NPS) that has operated at the Beijing Meteorological Service (BMS) since 2019. The NEPS provides hourly updated analyses and probabilistic forecasts in the nowcasting and short range (0–6 h) with a spatial grid spacing of 500 m. It covers the three meteorological parameters: temperature, wind, and precipitation. The outcome of an evaluation experiment over the deterministic and probabilistic forecasts indicates that the NEPS outperforms the REPS and NPS in terms of surface weather variables. Analysis of two cases demonstrates the superior reliability of the NEPS and suggests that the NEPS gives more details about the spatial intensity and distribution of the meteorological parameters.

摘 要

集合预报系统已成为估计模式初始条件及其不确定性的重要工具, 气象集合预报的应用价值也越来越受到重视. 本文提出了一种集成概率临近预报系统(NEPS), 该系统采用混合动力-集成方法, 将区域集合预报系统(REPS) 对预报不确定性进行定量估计的优势, 与集成预报系统对短临预报时效高分辨率精准预报的优势结合起来, 在区域集合预报系统基础上, 实现更高时间分辨率 (逐 1 小时更新、 逐 1 小时预报) 和更高空间分辨率 (500 米分辨率) 的 0–6 小时集合短临概率预报. 预报产品包括温度、 风和降水等气象要素的快速更新、 高时空分辨率的确定性产品及其概率预报产品. 批量检验与个例应用的结果表明, 集成概率临近预报系统(NEPS), 可以向终端用户提供更多有关温度、 风和降水等气象要素的空间强度和分布特征, 以及相应的不确定性预报的细节.