# OPERA the Radar Project
## 3 Results  
### Increasing Homogeneity of the European Radar Composites  
For quality assessment, OPERA has benefited from co-operation with data users--such as [10,11] --and has also executed its own studies. These studies have made use of the large archive of products we have. Various shortcomings, which are not visible in the 15 min products, can be identified using long-term rainfall accumulations calculated from the archived data. Echoes not related to precipitation, spatial discontinuities or unrealistic spatial variations, and gaps in spatial coverage are examples of shortcomings that can be identified. Next to rainfall accumulations, the frequency of threshold exceedance and the frequency of the special pixel values nodata and undetect are also useful to map. These kinds of long-term statistics can be used as efficient monitoring tools to identify and evaluate the impact of changes in the processing chain. The first maps show the frequency of nodata for the years 2012 and 2018 (Figure 2). This comparison shows a substantial geographical extension of the network. In 2018, most of Europe is covered, with a data availability exceeding 98%. Figure 3 shows the total rainfall accumulation for 2012 and 2018. Such maps allow for the identification of various artifacts and unrealistic spatial variations. In most areas, an increased homogeneity of the composite was obtained in 2018. Assessment of rainrate composites shows that the increase in homogeneity of composites is due to national improvements, both of the radars themselves and of the data sent to OPERA. Furthermore, the beam blocking correction and satellite-based clutter removal methods, implemented in December 2015, also improved the quality of the composite. This is illustrated in Figure 4, which shows the frequency of undetect values in 2015 and 2016. The undetect value can be interpreted as a \"dry pixel\". The pixels which are never dry (i.e., blue pixels in the figure) are very likely contaminated by non-meteorological signals, even if these signals are very low in intensity. Comparing 2015 and 2016, we can see the impact of the centralized clutter cancellation methods implemented in the end of 2015. Figure 2: Frequency of _nodata_ values in (**a**) 2012 and (**b**) 2018. It must be noted that some unwanted side effects can be obtained when unwanted echoes, such as sea clutter, are present in a blocked area. In that case, the beam blockage correction will result in an increase of the these unwanted signals. Figure 5 shows the frequency of exceedance of the 0.1 mm/h threshold for 2012 and 2018. It allows identification of areas that are contaminated by ground echoes strong enough to be wrongly interpreted as precipitation. It is easy to identify sectors pointing towards individual radars (e.g., in southern Spain). These signals are related to transmitting devices operating at the same frequency as the radar, which clearly affect the quality of the composite [12]. The comparison of 2012 and 2018 shows a reduction of these disturbances in Eastern Europe, but an increase in other regions. Figure 4: Frequency of undetected values in (**a**) January–November 2015 and (**b**) January–November 2016. Figure 3: Annual precipitation in (**a**) 2012 and (**b**) 2018. To quantitatively assess the quality of the OPERA products, an external reference is needed. Hence, the rainrate composites were compared to the accumulated precipitation using the mesoscale analysis system MESAN [13]. Figure 6 (left) shows the number of days in December 2017 where the precipitation intensity in any of the composites is greater than 0.0 mm/h. This data set was, subsequently, used to normalize the precipitation intensity difference (OPERA-MESAN). Figure 6 (right) shows the corresponding average daily bias for December 2017. In general, weather radars underestimated precipitation at the borders of the network due to beam overshooting. This was especially evident at Northern latitudes, but also in the South during winter.