# Weather Radar in Complex Orography
## 4 Solutions and Results
### Availability and Timeliness
It is necessary to combine two or, ideally, all of the following strategies:  
* Maximising the availability of each single radar (this puts demands on: the hardware, system design, monitoring capabilities, organisation of the spare parts, training and operational organisation of the technicians and engineers, support contract with radar manufacturer);
* Exploiting the redundancy of overlapping radars, in a network approach, by means of intelligent multiradar compositing (this puts demands on the siting, maximum range, scan strategy and multiradar data processing);
* Incorporating data from foreign radars in the product generation;
* Having an automatic switch to a fallback solution, which is based on data from other observation systems or models (for instance, satellite and lightning data for thunderstorm nowcasting);
* Training the users to be able to handle the situation, in the case of failures or interruptions, with whatever data are available. Table 2 shows the availability of the Swiss radar network, expressed as the time of year in percentage. In particular, it shows: (A) the number of operational radars of the network, (B) the time of year the central radar server generates products, (C) the time of year the radar network delivers good quality quantitative information for all the pixels in the country, (D) the time of year during which a maximum of one radar is missing in the composite, and in (E), (F) and (G) the times of the year a single radar is in operation. (E) shows the average uptime of the radars and takes into account all the different types of interruption, that is, faults and preventive maintenance, whereas (F) shows the average uptime, but only considering faults. The numbers in (F) were calculated manually and are only available for the years 2015 and 2016. Preventive maintenance roughly amounts to 1%, and it is easy to make an estimate for the other years in line (F) by adding 1% to \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & \multicolumn{3}{c}{**Percentiles**} & \multicolumn{2}{c}{**Within**} \\  & **50 th** & **90 th** & **99 th** & **99.9 th** & **60 s** \\ \hline
**Unit** & **s** & **s** & **s** & **s** & \% \\ \hline Base products (including radar QPE) & 0 & 8 & 39 & 43 & 99.95 \\ Thunderstorm nowcasting & 5 & 16 & 45 & 82 & 99.87 \\ Heavy precipitation warnings & 5 & 16 & 46 & 82 & 99.87 \\ All products & 22 & 40 & 74 & 123 & 96.61 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Timeliness of products generated every 5 min by the Swiss radar network. Timeliness has been monitored automatically since 2019. The statistics in this table refer to a period of 1000 days, from January 2019 till September 2021. The numbers in seconds correspond to the average time between the nominal completion time of a volume scan and the time when the product is ready for submission to internal and external users. the numbers in line E). (E) and (F) show the arithmetic means of all the radars, while, in line (G), we pick the radar with the lowest uptime for each year. The numbers reported in (G) are below the users' requirement and illustrate the need to have overlapping radars in a mountainous region. The numbers in (B) and (C) are the ones that are relevant from a user's perspective.