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High‐quality time series of meteorological observations are required for reliable assessments of climate trends. To analyze inhomogeneities in time series, parallel measurements can be used. Germany's national meteorological service DWD (Deutscher Wetterdienst) operates a network of climate reference stations. At these stations, manual and automatic observations have been taken in parallel. These parallel measurements therefore allow analyzing the impact of the transition on the homogeneity of time series of several meteorological parameters. Here, we present results for temperature. The differences between automatic and manual measurements are tested on breakpoints caused by instrumental defects or changes in the measurement conditions. The time series are highly correlated such that small breaks can be identified. The detected breakpoints are verified against metadata if available. In the case of no available metadata information, a procedure is suggested to identify the inhomogeneous time series (manual or automatic time series). Afterwards, the time series are homogenized. The homogenized time series are used to analyze the impact of changing the observing system from manual to automatic measurements on daily mean temperature. [ABSTRACT FROM AUTHOR]

Precise quantification of climate change depends on long time series of meteorological variables. Such time series should be as homogeneous as possible but some changes of measurement conditions cannot be prevented. At German climate reference stations, parallel measurements are used to analyze the effects of changes in measurement systems for example for the transition from manual to automatic instruments. These parallel measurements aim to identify measurement uncertainties and to analyze the comparability of measurement systems to investigate the homogeneity. In this study, we investigate daily sunshine duration. Traditionally, manual measurements of daily sunshine duration are taken with Campbell-Stokes sunshine recorders. For automatic measurements the SONIe or SCAPP instrument is used. The different measurement principles (glass sphere and photodiode) cause systematic differences between the observations. During summer, values for manual observations are larger especially in case of frequent alternations between sunny and cloudy conditions. Furthermore, the standard deviation of the differences between the two measurement systems is larger during summer because of the greater day length. To adjust the automatic measurements a linear regression model is suggested based on parallel measurements from 13 climate reference stations in Germany. To validate the regression coefficients, a leave-one-out cross validation was performed (by leaving out data of individual stations). The regression coefficients (derived from different sets of stations) are similar, thereby indicating a robust data set for the estimation of the linear model. With this method we want to prevent breaks in long time series of daily sunshine duration caused by the transition from manual to automatic instruments. [ABSTRACT FROM AUTHOR]