## 4 Methods and Data Analysis
### Data Analysis  
For at least three decades, the differential GPS (DGPS), and later DGNSS, technique has been the dominant operational mode for high-accuracy positioning for the geodesy, geoscience and navigation communities. Currently, however, the availability of precise GNSS orbit- and clock-data products with centimeter accuracy let PPP (precise point positioning) soar [30]. PPP is a GNSS-positioning method that employs readily available satellite orbit and clock-correction data from a global network to perform absolute 3D positioning, determining receiver-clock error and the total tropospheric delay using measurements from a single GNSS receiver. However, the single-receiver approach for PPP, traditionally, has also had some drawbacks, the most significant of which is its long con vergence times (about a few tens of minutes) necessary for the ambiguity float solution to converge to achieve the required cm-level accuracy in positioning [30]. Recently, several analysis centres made available satellite phase biases, consistent with satellite orbits and clocks. allowing a valuable extension of the PPP concept towards PPP-RTK (real-time kinematics) [31]. This is the case of the post-processed Canadian Spatial Reference System Precise Point Positioning (CSRS-PPP) online web service, based on the application of backward filtering for ambiguity resolution [32]. For the purposes of our study, we have retrieved the tropospheric delay quantities and PWV from GPS data, processed with both DGPS and PPP techniques. More precisely, three different strategies of data analyses and associated products have been used:  
1. [label=(0)]
2. GAMIT/GLOBK [33]
3. Nevada geodetic laboratory solutions [34]
4. The post-processed Canadian Spatial Reference System Precise Point Positioning (CSRS-PPP) online web service [32]. We analysed, with the above-mentioned techniques, three different data sets acquired by the NeVoCGPS network: a long data set, ranging from 2005 to 2016, and two short data sets, of 8 days and 5 days, respectively. The short series include time intervals when severe storms hit the Campania region. For the long time series, only differential method 1 [33] was used, because it also was used during those years. In fact, as mentioned above, only in more recent years have PPP techniques reached accuracy standards comparable to differential methods. Therefore, for our study, the differential method was the most suitable for studying the long-term temporal evolution of the tropospheric delay parameters. On the other hand, for short time series, aimed at studying storms, we used all the methods listed above, both differential and PPP techniques, and compared hourly differential and fast (5 min) and very fast (30 s) PPP solutions. These faster techniques could, in the future, play a decisive role in obtaining parameters of meteorological interest in real and near-real time. For the first data set, we mainly focused on the Vesuvius sector of the network, since the latter is the most suitable to study the topographic effects on the characteristics of the estimated parameters. Due to the harsh topography, GPS stations in the Vesuvius area are distributed at different altitudes ranging from a few tens of metres to about 1000 m above sea level (Table 1). In detail, we have retrieved the tropospheric delay parameters and PWV from processing, carried out with GAMIT/GLOBK, of an 11-year-long data set. Then, we inspected the main spectral characteristics and the time evolution of the parameters of interest in GNSS meteorology, i.e., ZTD, ZWD and PWV. For the second and third datasets, we focused on the city of Napoli to investigate how GNSS-derived parameters can contribute to understanding the spatiotemporal evolution of three major thunderstorm/heavy rain events that hit the Neapolitan area during 2019 and 2020. Presently, a brief overview on these strategies of analysis is outlined. A set of continuous GPS (Figure 1) data was analyzed with the software GAMIT/GLOBK [33].