# Rainfall Erosivity Main Features and Their Associated Synoptic Conditions in North-Eastern Romania
## 2 Materials and Methods
### Data Used  
In this study, we have used multiple types of meteo-climatic data. Firstly, in order to give a general overview of soil erosion over northeastern Romania, we have used the ERA-5 dataset [32]. In addition, the same type of data was used to depict the synoptic conditions associated with the most intense rainfalls over the analyzed region. Therefore, a database of downscaled bioclimatic indicators derived from the ERA-5 reanalysis [33] and available on the Copernicus Climate Data Store was used. The database contains the  
Figure 1: Geographical location of the study area at continental (**a**) and country (**b**) scales, hyposometric characteristics (**c**), and Walter–Lieth climograms for Mááárájac (**d**) and Cáárja (**e**) weather stations.  
mean values of 76 bioclimatic indicators for the period 1979-2024, at a spatial resolution of 1 km \(\times\) 1 km. The indicators utilized in this study encompass annual precipitation (BIO12) and the precipitation of the wettest month (BIO13), employed for the calculation of the Fournier Index. The monthly mean precipitation values were further leveraged for the determination of the Modified Fournier Index. The data were extracted from the database using climate data operators (CDO) [34], as well as the ncdf4 package in R program language [35]. The subsequent processing and interpolation was also conducted in R using the terra, sf, stars, and dplyr packages. The processed raster files were imported in QGIS 3.16 to obtain the final cartographic products.  
Secondly, in order to enhance the accuracy of the analysis developed firstly on gridded datasets [36], we have also used ground-based data from two independent weather stations (Carja in Vaslui County and Madarjac in Iasi County, Figure 1c). We underline that these two weather stations are self-managed weather stations, offering the advantage of hourly precipitation amount resolution that can provide more precise insights at the regional and local scale on rainfall intensity [37; 38]. It is also important to note that these two weather stations bring new information on hourly rainfall data in some areas largely uncovered by official weather measurements in northeastern Romania. The data from these weather stations were collected from 2013 to 2019, representing a time interval sufficiently consistent to draw the general image of synoptic conditions associated with intense rainfall at the hourly level. Out of the hourly data from the two weather stations, we selected those days that recorded at least one hour with rainfall greater than 5 mm, building a dataset consisting of 63 independent days between 2013 and 2019. Using all these days, the synoptic climatology of moderate and heavy rains was built, using two methods.  
The general synoptic conditions were delineated through the utilization of composite maps from the aforementioned period, encompassing the spatial distribution of the following parameters: 500 hPa geopotential height, sea level pressure (SLP), Convective Available Potential Energy (CAPE), and precipitation amount. Concurrently, distinct weather patterns were identified through the implementation of a Self-Organizing Maps (SOMs) methodology. The data necessary for conducting the composite analysis maps and the SOMs, which serve as a pillar for building the synoptic climatology of moderate and heavy rains, were also downloaded from the ERA-5 gridded dataset [32].