The latest radar observations are widely used as the main source for deterministic precipitation nowcasting techniques, such as the Integrated Nowcasting through Comprehensive Analysis (INCA) system, in operational and research centers. However, this approach does not take into account other sources of information such as Ensemble Prediction Systems (EPS) from the Numerical Weather Prediction (NWP) models such as C‑LAEF (Convection-Permitting Limited Area Ensemble Forecasting). These systems, even though they do not outperform the Lagrangian extrapolation for several hours, can provide useful probabilistic information. INCA has a deterministic Quantitative Precipitation Nowcasting (QPN) module. For including uncertainties and errors in the prediction of precipitation, an ensemble generator is required. The created ensembles have to reproduce the temporal and spatial statistical properties of a real rainfall field. With this aim, a localized scheme known as Short Space Fast Fourier Transform (SSFT) is used. The information provided by C‑LAEF is introduced in the SSFT technique by using the Ensemble Kalman approach at grid scale and a Bayesian weighting to improve the ensemble mean with the latest information. Once the ensembles are generated with the information from C‑LAEF an empirical distribution matching is applied to avoid lose of variance and to keep the high rainfall values. The final EnQPF is verified in a probabilistic way for the period of July 2016. Several scores are used to evaluate the set of ensembles to determine whether the methodology produces sufficient uncertainty while keeping essential properties from the original field and the EPS.

中文翻译：

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受集合预报系统约束的概率降水临近预报系统。

最新的雷达观测资料被广泛用作确定性降水临近预报技术的主要来源，例如在运营和研究中心进行的通过综合分析的综合临近预报（INCA）系统。但是，此方法未考虑其他信息源，例如来自数值天气预报（NWP）模型的集合预报系统（EPS），例如C‑LAEF（允许对流的有限区域集合预报）。这些系统即使在几个小时内都没有超过拉格朗日外推法，却可以提供有用的概率信息。INCA具有确定性定量降水临近预报（QPN）模块。为了在降水预测中包括不确定性和误差，需要集成发生器。所创建的合奏必须再现真实降雨场的时间和空间统计特性。为此目的，使用了一种称为短空间快速傅立叶变换（SSFT）的本地化方案。C‑LAEF提供的信息已通过在网格规模上使用Ensemble Kalman方法和贝叶斯加权在SSFT技术中引入，以利用最新信息来改善整体均值。一旦使用来自C‑LAEF的信息生成了合奏，便会进行经验分布匹配，以避免方差损失并保持较高的降雨值。最终的EnQPF已通过概率验证了2016年7月的时间。