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We present some first insights into hourly automatic pollen measurements from two campaigns performed at MeteoSwiss (spring to early summer 2015 and 2016). While the focus of the campaigns was on device validation, the data obtained provided the possibility to carry out a statistical analysis to estimate airborne pollen concentrations at hourly resolution. We compare the time series from the automatic system with reference manual measurements to assess the validity of the automatic system. As expected, during peak immission periods there is a strong correlation between manual and automatic measurements. On days with average pollen concentrations less than 100 grains per cubic metre, only the high-sampling automatic system provides reasonable results. We show how this system provides sub-daily exposition patterns, which cannot easily be derived from the manual measurements, and comment on their relevance for patient information systems. Finally, we present a selection of daily cycles for pollen immission at the observation site and analyse the influence of weather parameters on pollen emission and immission. [ABSTRACT FROM AUTHOR]

Phenological data have become increasingly important as indicators of long-term climate change. Consequently, long-term homogeneity of the records is an important aspect. In this paper, we apply a breakpoint detection algorithm to the phenological series from the Swiss Phenology Network (SPN). A combination of three statistical tests is applied and different constraints are tested with respect to the choice of reference series. Breakpoint detection is only possible for a fraction of the series due to the shortness of some series and the lack of suitable reference series. Spring phases are more likely to be suitable than fall phases because of their higher spatial correlation. Out of nearly 3000 phenological series with at least 20 data points, only about 5% were found to be significantly inhomogeneous, although a visual validation indicates that many mid-sized breakpoints remained undetected. The detected breakpoints were compared with metadata and more than half of them could be attributed to a change of observer. [ABSTRACT FROM AUTHOR]