# Weather Radar in Complex Orography
## 4 Solutions and Results
### Multisource Data Integration  
One way of coping with the limitations of radar measurements over complex orography is to combine them with data from other sources, such as rain gauge measurements, satellite imagery, lightning data, ground observations of hail and NWP output. An obvious approach, which has a long history, is the merging of radar QPE with rainfall measurements from rain gauges, see, for instance, the evaluation of different techniques presented in [158], the method proposed in [159] and references therein. This approach can also be used, in principle, in mountainous regions. However, the merging of radar and rain gauge data can only deliver good results if both data streams have passed a rigorous automatic data quality control, which is a particularly demanding task for complex orography. A space-time cokriging with external drift technique, specifically developed for operational real-time radar rain gauge merging in mountainous Switzerland (CPC), was presented in [90] and was mentioned in the previous section. The CPC algorithm published in 2014 [90] has been extended to 5-min disaggregation [92] and many aspects have been refined with a particular focus on robustness and a proper treatment of the gradients in convective cells. In addition to measurements from radar and rain gauges, it is also possible to add snow measurements conducted on glaciers [125, 160, 161], or fields of precipitation retrieved from satellite data, see, for instance, [162, 163] for two studies over the European Alps. In the cases mentioned before, independent estimates of the same variable, that is, the precipitation rate at the ground, were combined in one value. The combination of radar, satellite, lightning and NWP data in multisource thunderstorm tracking and nowcasting systems represent a different case. These various sources provide different but complementary information. When combined, they form a comprehensive picture of thunderstorms and the related hazards. For examples of thunderstorm nowcasting systems, developed for the use in complex orography, see [93, 107, 164, 94]. A third type of real-time multisource data integration is the seamless blending [59, 85, 88] of radar QPE, Lagrangian radar extrapolation nowcasts [87, 165] and NWP forecasts, following the pioneering work of [166, 167]. These blending methods all involve radar nowcasts being seamlessly blended with NWP forecasts, while taking into account the respective skills of the two sources as a function of the lead time. The blended product starts from the radar QPE at time zero. Over the first few hours, it gives large weights to the Lagrangian \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & **1997** & **2005** & **2007** & **2009** & **2012** & **2014** & **2016** & **2018** & **2020** \\  & & **2006** & **2008** & **2010** & **2013** & **2015** & **2017** & **2019** & **2021** \\ \hline Number of radars & 3 & 3 & 3 & 3 & 3 & 3/4 & 5 & 5 & 5 \\ \hline \multicolumn{8}{c}{**Scatter in dB**, hourly precipitation, the whole of Switzerland} \\ \hline Radar-only & 4.0 & 2.9 & 2.9 & 2.9 & 2.9 & 2.9 & 2.7 & 2.8 & 2.5 \\ Radar rain gauge & & 2.5 & 2.3 & 2.4 & 2.2 & 2.1 & 1.9 & 1.9 & 1.7 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Accuracy of real-time radar precipitation estimates for two operational products, a radar-only QPE (PRECIP) [4] versus a radar rain gauge merging with a cokriging with external drift technique (CPC) [90]. Accuracy is expressed as scatter in dB, see Figure 19, for hourly precipitation amounts in the summer months JJA. The scatter has decreased over the years, which points to a continuous improvement of the QPE algorithms. Automatic rain gauges of the whole of Switzerland are used for the evaluation. The tested rain gauge was left out of the cokriging (cross-validation) for the radar rain gauge combined QPE. The shown numbers are based on standardised procedures that are routinely used for verification purposes; no manual data selection or tuning was performed.