<p>Summer thunderstorms can cause strong socio-economic impacts over Germany. The project SINFONY (Seamless integrated forecasting system) at German Weather Service has the goal to improve short-range predictions of these storms. Nowcasting (NWC) currently is superior to numerical weather prediction (NWP) on the very-short range up to about two hours in predicting convective cells while NWP performs better afterwards. Within SINFONY products are developed that integrate both approaches for a seamless prediction. High-resolution reflectivities from the German radar network are used as observational data base and for NWC initialization. The respective reflectivities from NWP models are derived by employing the radar forward operator EMVORADO. Convective cells are identified from these reflectivities using the KONRAD3D cell detection tool.</p> <p>We present forecasts of convective cells from standalone NWC and NWP predictions and from a product that combines both systems. The recently developed NWC ensemble system KONRAD3D-EPS comprises 20 members with stochastic differences in the positions and life cycles of NWC objects. NWP objects come from ICON-D2-EPS (20+1 members) simulations employing a two-moment microphysics scheme with a forecast horizon of 8 hours. To combine these 41 members the NWP objects are clustered spatially, compared with each observation and the cluster closest to an observation is selected. Several properties of objects within a selected cluster are compared with the matching observed object using the Total Interest. Model objects that are similar enough to the observed object are selected and spatially shifted to make their centroid position equal to the observed cell. The trajectories of shifted NWP objects are then used, together with the NWC objects, as forecasts of convective cells. NWP objects that develop later in the forecast are considered as well but without the assignment to an observed object. Thus, with increasing lead time and the decease of cells that existed during the initialization of the combination, the product smoothly transitions into a purely model-based forecast.</p> <p><br />Having an ensemble of predicted objects necessitates some kind of information reduction. Here the pseudomember method is employed that selects the locally most representative objects from the ensemble. For the object-based verification we use the Median of Maximum Interest. It reveals for JJA 2022 that the methods described above deliver a seamless object-based forecast product for convective cells which unifies the strengths of NWC and NWP. For lead times between 30 and 120 minutes the combined product performs even better than each prediction type standalone.</p>
<p>The precise forecast of convective cells is essential for meteorological services as they can be accompanied by life-threatening severe hail, wind gusts, or heavy rain. However, state-of-the-art NWP models usually possess update frequencies of several hours so that forecasters must use predictions that are outdated when new thunderstorm cells develop. NWP models do often accurately simulate the intensity of convective cells, but with shifts in space and time. Object-based nowcasting algorithms with higher update frequencies became necessary to deliver information on the evolution of convective storms for the first two hours since observation. Furthermore, the combination of nowcasting and model data enables the relocation of simulated cells towards observed cells.</p> <p>Many deterministic object-based nowcasting tools as DWD&#8217;s KONRAD3D algorithm assume that detected cells will have persistent intensity. Within the SINFONY (Seamless INtegrated FOrecastiNg sYstem) project at DWD, we aim at modelling the life-cycles of storm cells in a truthful way and capturing the uncertainties of object-based nowcasts. Hence, we extended our nowcasting algorithm towards an ensemble prediction system called KONRAD3D-EPS. Each ensemble member is initialized by drawing from parameterized distributions of storm lifetime and maximum severity. Inspired by previous studies, e.g. Wapler (2021), KONRAD3D-EPS uses a set of horizontally flipped parabolas to model the life-cycle of convective cells in terms of their severity. In case of redetection of a convective cell, the algorithm corrects the previously estimated lifetime and severity maxima. Thus, the parabolas can be adapted individually for any convective storm in any weather condition.</p> <p>Besides life-cycle predictions, KONRAD3D-EPS delivers information on the probability of thunderstorm occurrence for the next 2 hours depending on detected cells and their severity. In order to condense the ensemble data, we also provide the representative member for each convective cell. This is done by applying the pseudomember algorithm by Johnson et al. (2020) to the ensemble data.</p> <p>We will give an overview of our probabilistic object-based nowcasting algorithm KONRAD3D-EPS and present its predictions for prominent example cases. Moreover, we will show first verification results.</p>
<p>At Deutscher Wetterdienst (DWD), the SINFONY project has been set up to develop a seamless ensemble prediction system for convective-scale forecasting with forecast ranges of up to 12 hours. It combines Nowcasting (NWC) techniques with numerical weather prediction (NWP) in a seamless way. So far NWC and NWP run on two different IT-Infrastructure levels. Due to the data transfer between both infrastructures, this separation slows down SINFONY, makes it complex and prone to disturbances. These disadvantages are solved by applying the interconnected part of the SINFONY on one single architecture using a Docker Container.</p> <p>With this aim in view a Docker-Container of the respective NWC components is created and executed on the infrastructure of NWP, the high performance linux computing cluster (HPC) of DWD. In test applications we already observed a speed up of roughly 20% by using the Container on the HPC-cluster instead of using NWC-Tools on the initial NWC IT-Architecture. The Container is already implemented in DWD&#8217;s experimental tool BACY for the assimilation cycle.</p> <p>A major innovation of SINFONY is the rapid update cycle (RUC), an hourly refreshing NWP procedure with a Forecast range of 8 hours, which will be extended to 12 hours soon. The container will be implemented to the RUC and used for the subsequent combination of NWP and NWC forecasts.</p> <p>In the presentation I will explain what a container is and discuss opportunities and risks of this technology. I will introduce how building the Container is integrated to the CICD procedures at DWD, how and where the Container is implemented to BACY and discuss latest results for the implementation to the RUC.</p>
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