*2.2. Case Studies*

In the following section, we describe the case studies that were used to evaluate the proposed *NeXtNow* model. The two case studies were conducted using datasets from Romania (provided by the NMA) and Norway (provided by the MET), which were selected because they belonged to different geographical/climatic areas and contained different radar measurements (as further highlighted in Table 1), thus allowing us to test the performance of the *NeXtNow* model more thoroughly.

### 2.2.1. First Case Study (NMA Data)

The NMA dataset that was used in our first case study was collected by a Doppler single-polarization radar that is located in central Romania. During a full volume scan, which is completed every 6 min, the radar outputs many different products that are related to the location, intensity and movement of precipitating clouds and their associated meteorological phenomena. For the experiments, we used the base reflectivity (R) product and the base velocity (V) product. The radar collects these base products at nine elevation angles, effectively gathering nine sets of velocity and reflectivity data at each time step. For both products, we used the data from the lowest four elevation angles, which resulted in eight products in total: R01, R02, R03, R04, V01, V02, V03 and V04. The reflectivity and Doppler radial velocity were used for the NMA case study as these are the first products that are analyzed by forecasters to identify weather features. The use of velocity fields can be theoretically useful because they can introduce the effects of convergence zones into the model for the prediction of the initiation and evolution of convective storms. The experiments that are presented in Section 3 empirically sustained this hypothesis.

To train, validate and test the model, 20 summer days with heavy rain, wind and hail and without any meteorological events were extracted from the observations, which corresponded to events that were observed in June 2010 (2nd, 10th, 12th, 13th, 14th, 19th, 20th, 22nd, 23rd and 24th), June 2017 (from 3rd to 7th) and June 2018 (11th, 13th, 15th, 16th and 21st). The study area was the central Romania region (central Transylvania) as the radar is located near the village of Bobohalma. The month of June was selected for the NMA case study as, in Romania, it is the month that the most convective storms and convective systems develop in the Carpathian basin. The dataset included days both with and without severe meteorological events and thus, a diverse dataset was obtained. Out of the entire area that is scanned by the radar, we focused on a central square with a size of 256 × 256 cells (the radar is located in the middle of this square).

### 2.2.2. Second Case Study (MET Data)

The MET radar dataset that was used in our second case study consisted of composite reflectivity values that were obtained from the MET Norway Thredds Data Server [32]. The data, which are available at [33], were obtained by processing the raw reflectivity measurements that were retrieved from multiple radars. Thus, the reflectivity product that is stored at the MET Norway is a composite map that is obtained from all elevations and tilts by taking into account the radar scans that have the best quality and not the strongest reflectivity across the elevations. This composite reflectivity product is obtained by applying an interpolation procedure and using different weights for the various radars, depending on their quality and other meteorological or non-meteorological factors that can alter the radar measurements. The reflectivity values that were used in our experiments were collected at intervals of 5 min.

To train, validate and test the model, days with and without meteorological events were selected from December 2020 (23rd, 25th, 26th and 27th), January 2021 (17th and 18th), March 2021 (3rd and 4th), April 2021 (12th and 13th), June 2021 (the entire month) and January 2022 (1st–25th). The days were selected so as to obtain a diverse dataset that contained days both with and without severe meteorological events and included both summer and winter months. The analyzed geographical area was a region surrounding Oslo. From the entire map, a square of 256 × 256 pixels was selected.

Table 1 describes the datasets that were used in our case studies. The second column in the table indicates the radar products of interest and the last column shows the number of days on which the radar data that were used in each case study were collected.


**Table 1.** A description of the datasets that were used in our case studies.
