Ensemble weather forecast post-processing with a flexible probabilistic neural network approach

Ensemble forecast post-processing is a necessary step in producing accurate probabilistic forecasts. Conventional post-processing methods operate by estimating the parameters of a parametric distribution, frequently on a per-location or per-lead-time basis. We propose a novel, neural network-based method, which produces forecasts for all locations and lead times, jointly. To relax the distributional assumption of many post-processing methods, our approach incorporates normalizing flows as flexible parametric distribution estimators. This enables us to model varying forecast distributions in a mathematically exact way. We demonstrate the effectiveness of our method in the context of the EUPPBench benchmark, where we conduct temperature forecast post-processing for stations in a sub-region of western Europe. We show that our novel method exhibits state-of-the-art performance on the benchmark, outclassing our previous, well-performing entry. Additionally, by providing a detailed comparison of three variants of our novel post-processing method, we elucidate the reasons why our method outperforms per-lead-time-based approaches and approaches with distributional assumptions

Integrating nowcasting with crisis management and risk prevention in a transnational and interdisciplinary framework

This paper presents the recent WWRP/WMO Forecast Demonstration Project INCA-CE (INtegrating nowCAsting for Central Europe) co-funded by the European Union. Twenty-four partners of national and regional hydro-meteorological services, national and regional crisis and disaster management centers, and authorities for road management world-wide have participated in INCA-CE for international cooperation on nowcasting development, interdisciplinary cooperation for nowcasting applications and transnational cooperation for nowcasting services. INCA-CE has implemented the nowcasting system INCA at the project partner countries, applied INCA nowcasting in civil protection, operational hydrology and road safety, and improved the INCA system based on the end user's requirements. The main difference to other similar projects is that end user's involvement and the improvements involve the whole end user value chain. The project has developed several ideas for end users on how to interpret nowcasting products (INCA-SWING) and on how to deal with the nowcasting products in their working practice (INCA-MCPEX and ISW). INCA-CE is also oriented strongly to transnational cooperation in nowcasting development and implementation, in easy access to a homogenized set of nowcasting products from those INCA providers to end users in the region, and in the transnational use of real-time products by end users in cases of high impact weather across borders