Homogenization of Swedish mean monthly temperature series 1860–2021

Abstract

AbstractThe Swedish monthly average 2 m temperature observational data set is homogenized with a new automated version of the homogenization tool HOMogenizaton softwarE in R. Data from 836 individual time series (1860–2021) are merged into 456 time series with a novel automatic merging method. Merging limits the need of interpolation of data and increase the number of long time series without a net loss of data. Twenty‐two of the merged time series were found to be homogeneous. For the other time series, the median time per break‐point is 17 years. 37% of the detected break‐points are supported in meta data. 42% of the data are corrected by ±0.5°C or less, 3% by ±1°C or more. On average corrections are negative, larger in the early periods, and larger in the summertime. The average trend 1860–2021 in the resulting merged and homogenized data set is (0.13 ± 0.03)°C decade, which does not significantly differ from that of the raw observational data. Extremely warm months, defined as being outside of three times the standard deviation from the average of the full time series, are most frequent and extremely cold months least frequent in the most recent 30‐year period (1991–2020). In the homogenized data set, extremely warm months are even more frequent and extremely cold months even less frequent in 1991–2020, than in the raw observational data set.