## 4 Results
### Impact of Temporal and Satellite Retrieval-Specific Sampling on IWV Aggregations and Distributions  
The impact of the low temporal sampling of observations from polar-orbiting satellites for the German domain as well as limitations to daytime clear-sky situations on the IWV statistics can be further investigated using the high temporal GPS IWV dataset in combination with the MSG-SEVIRI information on cloud coverage. Figure 7 shows the normalized histograms for all collected 15 min GPS IWV values within the one-year time period as well as for subsets based on daytime (from 9 h to 17 h LT), certain clear-sky (cloud coverage \(\leq\) 0.1), and certain cloudy (cloud coverage \(\geq\) 0.9) cases. Most distributions show a maximum around 8 kg/m\({}^{2}\). However, limitations to daytime and clear-sky cases appear to cause a bi-modal distribution with a first maximum around 5-7 kg/m\({}^{2}\) and a minimum around 9-10 kg/m\({}^{2}\). Also, a relative decline of high IWV values can be noticed. This relates well with the MODIS IWV distributions presented in Figure 3. Overall, the mean IWV and standard deviations for the different subsets vary within 3% of the mean values obtained using all 15 min GPS IWV values. The mean IWV value for the daytime and certain clear-sky cases is the lowest, while considering only daytime and certain cloudy cases has the highest mean IWV value. Figure 6: Averaging time period vs. error (using as reference GPS climatologies computed from all 15 min IWV values within an averaging time period) obtained from bootstrap using a sample size of 10,000 for each averaging time period. The dots show the median and the bars indicate the 5% and 95% confidence levels. **Left:** for GPS IWV values for all matched satellite pixels. **Middle:** for GPS IWV values for all matched satellite pixels with successfully retrieved satellite IWV values. **Right:** satellite IWV values for all matched satellite pixels and successfully retrieved satellite IWV values  
The high temporal resolution of the GPS IWV product allows the computation of the mean IWV diurnal cycle for the German domain. Figure 8 shows that the most pronounced mean IWV diurnal cycle is observed in the summertime with an amplitude of about 0.5 kg/m\({}^{2}\). This is related to surface heating due to increasing solar insolation during the day, stimulating convective processes with accompanying transport of moisture into the atmosphere. In the other seasons, the weather conditions and accompanying atmospheric moisture content are even more dominated by large-scale synoptic systems, typical for the mid-latitudes, and thus not necessarily showing a clear diurnal cycle for IWV [37]. This also explains the corresponding large hourly standard deviations, which go up to 6-8 kg/m\({}^{2}\) for all seasons (not shown). The large difference between 00h and 01h LT (23 and 24 UTC) is a known issue of the GPS near-real-time retrieval, which is also seen in the investigations by [PERSON] et al. [18] as well as in the assessment of the daily cycle at stations in North-America in [PERSON] et al. [39]. To check the representativity of our one-year dataset a longer GPS time series is also considered. Herein, the difference between the one-year IWV diurnal cycle and the one obtained from the years 2007-2013 is only small, especially considering the corresponding large standard deviations. The geographical distribution of the diurnal cycles was also investigated by computing mean IWV diurnal cycles for each GPS station (not shown). Within the German domain, the most pronounced IWV diurnal cycles, i.e., largest amplitudes, were found in the North-eastern part of the domain, which is a flat area near the coast. However, also in this case the magnitude of the standard deviations is much larger than the differences in mean diurnal cycles. The impact of the reduced temporal sampling of the satellite instruments on computed daily means shows a largest bias for MODIS in the autumn (SON) of about 0.25 kg/m\({}^{2}\).