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Comparison of manual and automatic daily sunshine duration measurements at German climate reference stations

2019/08/19 by Lisa Hannak, Karsten Friedrich, Florian Imbery +1 · 1 citation
Computer Science · Earth and Planetary Sciences · Environmental Science · #Solar Radiation and Photovoltaics #Atmospheric chemistry and aerosols #Atmospheric aerosols and clouds

paper · pdf · doi:10.5194/asr-16-175-2019

openalex publication_date 2019/08/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04

Abstract

Abstract. 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.

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