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We are discussing changepoint detection in tropospheric parameter time series that occurs in a numerical weather reanalysis model. Our approach applies a statistical method that is based on the maximum value of two sample t-statistics. We use critical values calculated by applying an asymptotic distribution. We also apply an asymptotic distribution to finding approximate critical values for the changepoint position. Experiments on “test” and “real” data illustrate the assumed accuracy and efficiency of our method. The method is assessed by its application to our series after adding synthetic shifts. A total of more than 3,000 original profiles are then analysed within the time-span of the years 1990-2015. The analysis shows that at least one changepoint is present in more than 9% of the studied original time series. The uncertainty of estimated times achieved tens of days for shifts larger than 9 mm, but it was increased up to hundreds of days in the case of smaller synthetic shifts. Discussed statistical method has potential for suspected change point detection in time series with higher time resolution. ARTICLE INFO

An assessment of method for changepoint detection applied in tropospheric parameter time series given from numerical weather model.