The widely used Global Historical Climatology Network (GHCN) monthly temperature dataset is available in two formats—non-homogenized and homogenized. Since 2011, this homogenized dataset has been updated almost daily by applying the “Pairwise Homogenization Algorithm” (PHA) to the non-homogenized datasets. Previous studies found that the PHA can perform well at correcting synthetic time series when certain artificial biases are introduced. However, its performance with real world data has been less well studied. Therefore, the homogenized GHCN datasets (Version 3 and 4) were downloaded almost daily over a 10-year period (2011–2021) yielding 3689 different updates to the datasets. The different breakpoints identified were analyzed for a set of stations from 24 European countries for which station history metadata were available. A remarkable inconsistency in the identified breakpoints (and hence adjustments applied) was revealed. Of the adjustments applied for GHCN Version 4, 64% (61% for Version 3) were identified on less than 25% of runs, while only 16% of the adjustments (21% for Version 3) were identified consistently for more than 75% of the runs. The consistency of PHA adjustments improved when the breakpoints corresponded to documented station history metadata events. However, only 19% of the breakpoints (18% for Version 3) were associated with a documented event within 1 year, and 67% (69% for Version 3) were not associated with any documented event. Therefore, while the PHA remains a useful tool in the community’s homogenization toolbox, many of the PHA adjustments applied to the homogenized GHCN dataset may have been spurious. Using station metadata to assess the reliability of PHA adjustments might potentially help to identify some of these spurious adjustments.

The area of the Seven Rila Lakes is situated in the North-West part of the Rila Mountain at an altitude between 2100 and 2500 m a.s.l. within the borders of Rila National Park. There are 140 glacial lakes in Rila Mountain but the area of the Seven Rila Lakes is the most visited and famous with its natural beauty and sacred significance. It is a valuable part of the national natural heritage. The popularity of this area grows constantly with the number of visitors from the country and abroad. This process leads to the deterioration of the natural conditions in the site. At the same time, it is not clear what is the effect of climate change on the environment in the lake’s area. There are many factors that contribute to the degradation of ecosystems in the protected area of the Seven Rila Lakes and pose risk to this valuable natural heritage. These factors are natural (mainly climate change-related), anthropogenic (associated with the excessive tourist pressures on the ecosystems in the protected area), and management (stemming from the ongoing conservation policy over the years). This study explores to what extent climate change may put at risk the ecosystems of Seven Rila Lakes. Mean monthly data from The European Center for Medium-Range Weather Forecasts (ECMWF) ERA5-Land reanalysis were used in this study. The resolution of these data is 0.1 x 0.1 (9 x 9 km) and their period is 1981-2020. Reanalysis data include air temperature, precipitation, evaporation, snow depth, etc. Based on data from various sources such as reanalysis data, in situ measurements, and statistical modeling, a scenario, based on current trends in different climatic elements, has been developed in order to project future changes and their impact on lake ecosystems. The results of the modelling of climate change show that in the coming decades an increase in temperature is expected in the high mountain regions of South-western Bulgaria and in particular in the Seven Rila Lakes area. This, combined with the ever-increasing flow of tourists, and high demand for the provided cultural ecosystem services, and insufficient management practices, put at risk the state of the lakes and their capacity to provide the same quality of cultural ecosystem services in the future, which attracts tourists in the area now. Recommendations have been made for the optimization of the management of the protected area in accordance with the observed trends.