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Forest ecosystem stress caused by climate change, in particularly prolonged and severe droughts, has already been manifested in several parts of Europe, including temperate and boreal forests. It is likely that droughts and heatwaves will occur more often, which might result in the ecological transition of the forests and loss of biodiversity. The assessment of climate change impact on forest ecosystems is complex, as response can vary in space (depending on the physiological vulnerability of ecosystems and site conditions), time, and among species (species resilience).In this project we investigate the influence of several climatic variables (2 m temperature, rainfall, evapotranspiration and climatic water balance) on the forests condition in Poland in the period 2002-2021. To this end we use ERA-5 Land reanalysis data and vegetation indices – NDVI and EVI – derived from the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) – MOD13Q and MYD13Q. The remotely sensed indicators on vegetation consist of 8-day composites and have 250-m spatial resolution, while the climatic data is 0.1° x 0.1° spatial and 1-day temporal resolution.The spatio-temporal trends of NDVI and EVI were computed for forest areas only, and their statistical significance was assessed. The monthly analyses were carried out for growing season (April-October). Multi-annual trends of climatic variables were prepared not only for the period 2002-2021, but also for the longer period 1971-2021, in order to strengthen the information coming from the climate trend analysis. The influence of the variability of climate elements on vegetation indices was assessed with the methods of linear regressions and spatial correlations. The results were broken down into sub-regions of similar physical-geographical features (nature-forest classification).Identification of the relation between changing climate and forests condition seems crucial, because forests are the important element in the planetary energy balance and CO2 absorption. In Poland almost 30% of country area (9.2 million ha) is covered with forests, but such research have not been conducted so far.

Well-maintained and regularly calibrated measuring instruments provide the most accurate solar radiation data. This extremely valuable research material makes it possible, among others, to analyse variability in solar radiation over the long term and its dependence on other atmospheric state elements such as cloud cover and atmospheric aerosol concentration. Unfortunately, ground-based measurements of solar radiation are often subject to various errors which are very difficult to detect. This is why quality control procedures and homogenisation of data are essential and should be performed prior to further analyses. This paper presents a method for quality control and homogenization of solar radiation data, which builds on the bias-based quality control (BQC) method (Urraca et al., 2017), and is tailored specially for detecting single erroneous daily values, and very long periods of small errors. The method was tested for 16 ground-based stations located in Poland for the period 1991–2015. In comparison with the number of errors detected by the BQC method, the number of detected errors increased significantly: 130 to 2890 more erroneous days were detected at each station. Consequently, the number of inhomogeneous data sets was reduced from 8 to 3 stations. The values on the days considered as erroneous were replaced with debiased values originating from the Surface Solar Radiation Data Set – Heliosat, Edition 2 (SARAH-2). The presented methodology can be also of use in any other places, especially those with many single erroneous days and no metadata publicly available.

The deployment of solar energy projects in a given region requires a precise estimation of potential solar resources. For that purpose, generating a typical meteorological year is of great importance, although in principle it is a tool used in construction or engineering. Various methods for deriving typical meteorological years have been developed, but their final results can be significantly different. In this paper, two major methodologies (TMY3 method and ISO 15927-4 standard) were applied to 12-year measured data series recorded during the period 2003–2014 in Belsk, central Poland. The sums of global solar radiation obtained in typical meteorological years were compared to the long-term average measured sums of global solar radiation in order to decide which method can be recommended as best reflecting solar conditions in Poland. According to this study, the differences between the respective TMY data sets and long-term measured data set (measured with percentage root mean square error – %RMSE) are bigger than 5%. ISO 15927-4 standard slightly better approximates solar conditions in central Poland than TMY3 method – the %RMSE equals 5.25% and 6.71% respectively.

This study presents the vertical profiles of aerosol optical and microphysical properties obtained from cable car and ground-based measurements in the Silesian Beskids, Poland. The data were collected during a measurement campaign between 25 February and March 11, 2018. An AE-51 micro-aethalometer and PMS7003 and OPC-N2 optical particle counters were mounted on the cable car and used to measure the profiles of equivalent of black carbon (eBC) concentration and aerosol size distribution. In situ measurements of the optical properties of the aerosols were obtained using an AE-31 aethalometer and photoacoustic devices. A prototype lidar was used to determine the planetary boundary layer (PBL) height and the aerosol layers. In the middle phase of the study (1–6 March 2018), significant night-time temperature inversions were observed. During the inversion period, the parameters describing the amount of aerosols in the air increased significantly. The concentration of eBC exceeded the level of 15 μg/m3 several times, with an average level of 5.39 ± 4.42 μg/m3. Conversely, the results obtained in the first and third phases of the experiment were at the level of the aerosol background, being 1.45 ± 0.88 μg/m3 and 0.90 ± 0.95 μg/m3, respectively. Significant differences were also observed in the vertical profiles of PM10 mass and eBC concentration. In the middle phase of the study, the profiles showed a significant reduction in the concentration of pollutants with height, while in the first and third phases, there were slight variations with height.