Lenka Hájková

Satellite phenodates are widely used as indicators of seasonal ecosystem development, yet their ecological meaning depends on the observable and transition definition from which they are derived. We evaluated how phenology derived from 30-m Harmonized Landsat Sentinel-2 (HLS) Enhanced Vegetation Index (EVI) relates to below-canopy light-transmission phenology and observed canopy development in European beech and oak forests. HLS EVI phenodates were defined by spring and autumn crossings of a fixed site-specific threshold representing 50% of the climatological seasonal amplitude (EVI50) and compared with inflection-point transitions derived from continuous below-canopy photosynthetically active radiation (PAR) measurements during 2023–2025 using nested leave-one-site-out validation. Independent ground phenology observations from 2017–2025 were then used to position the resulting dates within observed spring development and the autumn coloration-to-leaf-fall sequence. Spring EVI50 and PAR transitions were closely aligned, whereas autumn EVI50 occurred approximately 16 d earlier. A simple global temporal offset captured most of this autumn difference, reducing out-of-site RMSE from 17.8 to 8.6 d, while a contextual mixed-effects model, incorporating species and elevation, provided a smaller additional refinement. Ground phenology placed baseline autumn EVI50 near early coloration and translated dates progressively closer to later coloration and leaf fall. However, the contextual benefit depended strongly on whether EVI50 used a climatological or annual amplitude reference, and improved absolute timing did not imply better tracking of interannual variability. Phenological indicators derived from optical greenness and canopy light transmission are therefore not interchangeable, but can represent distinct and reproducible stages of the same seasonal canopy trajectory.

Phenological shifts represent one of the most evident biological responses to climate change. This study used the two-band Enhanced Vegetation Index derived from Moderate Resolution Imaging Spectroradiometer satellite data to analyze changes in the growing seasons of arable land, broad-leaved forest, coniferous forest, and grassland across the central European region from 2000 to 2022. Phenological metrics included the start, end, and length of the growing season. Nonparametric Theil–Sen regression indicated an earlier start of the season (median of trends for all land cover classes ranging from -9.3 to -17.5 days per decade), a later end of the season (ranging from +8.1 to +11.4 days per decade), and consequently longer length of the season (ranging from +13.3 to +25.0 days per decade), with advancing start of the season identified as the primary driver of length of the season prolongation. The most pronounced changes across all phenological metrics were associated with arable land. Elevation zone-based analysis showed that the highest median of trends of start and length of the season was found for arable land and coniferous forest in elevations below 600 m a.s.l., with values decreasing progressively with increasing elevation. The analysis of environmental zones revealed a higher median of trends of the start and length of the season in cool-moist and warm-mesic zones, while end-of-season-related changes were more pronounced in cold-wet zones. This study demonstrates coherent long-term trends in vegetation phenology across different land cover classes, with stronger acceleration over arable land, highlighting potential implications for agricultural systems.

Spring-time frost events pose a significant risk for the agricultural sector. Vineyards, apricots and other crops might be damaged by freezing temperatures after vegetation season onset. Frost events occur commonly during cold outbreaks in April or May after prolonged periods of relatively high air temperatures in late-winter or early-spring. The damage can be significantly reduced by suitable measures, provided a reliable forecast is available. As frost intensity is often highly spatially variable, its forecast can benefit from hectometric-scale numerical atmospheric modelling. We present results related to frost events detection and impact modelling within the Destination Earth On-Demand Extremes (DEODE) project. The detection scheme uses the ECMWF ensemble forecasts of 2-m air temperature and cloud cover to identify regions of potential high-impact frost events. The Global Digital Twin 2-m air temperature sums since the start of the year are used to delimitate areas where vegetation is not active yet. These areas are masked from the risk assessment. Finally, the frost damage risk is expressed in 0–5 scale and may serve as guidance for hectometric-scale simulation domains. After a hectometric simulation is completed, the output is ingested into a downstream frost impact model. The impact model estimates current development phase of several crops and corresponding temperature thresholds for frost damage. These thresholds are compared with hectometric-scale forecasted temperatures to obtain the magnitude of excess of critical temperature for each crop. The impact model has been evaluated during several pilot frost events in the Czech Republic and Spain.

On the occasion of the 250 anniversary of uninterrupted temperature measurements at the Prague, Clementinum station, the CHMI publishes a comprehensive publication “V Klementinu bylo naměřeno…”. The book contains extensive information about the history of the Clementinum Observatory from the perspective of not only meteorological, but also construction, religious, social and other aspects of its existence. The history of Clementinum has been described several times before, but for the first time in the full range of disciplines that have been somehow connected with the observatory in its history. The article in the Meteorological Bulletin is only a brief invitation to read this book.

This article deals with reassessment of the methodology of wildfire risk conditions after the unprecedented fire in the Bohemian Switzerland National Park during July and August 2022. The original methodology took into account mainly critical fire weather conditions based on maximum temperatures, relative humidity and wind speed. However, the large-scale fire mentioned above has shown that this approach is no longer sufficient under changing climatic conditions. Therefore, multiple inputs were implemented within the new severe wildfire risk calculation. The severe wildfire risk assessment uses a combination of the fire weather index, the Haines index expressing the instability of the atmosphere, the area vulnerability index, which expresses the actual density of wildfires over the last decade, and the drought intensity expressed by the antecedent precipitation index. The newly developed Severe Wildfire Risk index can help to detect the risk of large and difficult-to-extinguish wildfires in advance.

The dataset presents a 43 year-long reanalysis of pollen seasons for three major allergenic genera of trees in Europe: alder (Alnus), birch (Betula), and olive (Olea). Driven by the meteorological reanalysis ERA5, the atmospheric composition model SILAM predicted the flowering period and calculated the Europe-wide dispersion pattern of pollen for the years 1980–2022. The model applied an extended 4-dimensional variational data assimilation of in-situ observations of aerobiological networks in 34 European countries to reproduce the inter-annual variability and trends of pollen production and distribution. The control variable of the assimilation procedure was the total pollen release during each flowering season, implemented as an annual correction factor to the mean pollen production. The dataset was designed as an input to studies on climate-induced and anthropogenically driven changes in the European vegetation, biodiversity monitoring, bioaerosol modelling and assessment, as well as, in combination with intra-seasonal observations, for health-related applications.

Climate change affects ecosystems and biodiversity, and the phenological development of plants has been changing. In this paper, we focused on the beginning of the flowering of the lime tree (Tilia cordata) in urban and rural settings. The long-term series were evaluated from phenological and meteorological stations of the Czech Hydrometeorological Institute (period 1923–2023). The trends (using the Mann-Kendall test) and Pearson’s correlation coefficients between the beginning of flowering and meteorological variables were calculated. Climate scenarios SPP2 4.5 and SPP5 8.5 (ALADIN-CLIMATE/CZ) were used to predict future climate conditions for lime tree phenological development. The main finding of this research is that the beginning of flowering of the lime tree during the period 1923–2023 is negative, and it varies in urban and rural environments. The results express the most significant acceleration of the beginning of flowering of T. cordata by -0.227 day per year in urban area and by -0.119 day per year in rural area. Moreover, the study proved that the beginning of flowering of T. cordata closely correlated with temperature (the Pearson’s correlation coefficient is in the range from -0.498 to -0.508.), and the correlation with precipitation is significantly weaker in both environments. The increase in air temperature in June and July will be significant in the period 2081–2100 (by 1.5 °C). Based on these findings, we expect a further shift in the beginning of T. cordata flowering to earlier dates. A change in the beginning of lime tree flowering will also affect the course of the pollen season.

The advent of automatic pollen and fungal spore monitoring over the past few years has brought about a paradigm change. The provision of real-time information at high temporal resolution opens the door to a wide range of improvements in terms of the products and services made available to a widening range of end-users and stakeholders. As technology and methods mature, it is essential to properly quantify the impact automatic monitoring has on the different end-user domains to better understand the real long-term benefits to society. In this paper, we focus the main domains where such impacts are expected, using Europe as a basis to provide qualitative estimates and to describe research needs to better quantify impacts in future. This will, in part, also serve to justify further investment and help to expand monitoring networks.

Changes in climatic conditions increase risks associated with crop production in certain regions. Early detection of these changes enables the implementation of suitable adaptation measures in the local area, thereby stabilising agricultural production. Our analysis shows a significant shift in climatic conditions in Czechia between 1961 and 2020. We examined the changes in observed temperature conditions, precipitation distribution, drought occurrences, and frost incidents at a high resolution (0.5 × 0.5 km). The outputs show a significant increase in air temperatures and drought occurrence. Temperature totals above 5 °C in 1991–2020 were 15% higher than in 1961–1990. Furthermore, the relative change in totals above 10 °C was 26% after 1991. Over the last 30 years, drought incidence was four times more frequent than in 1961–1990, particularly in spring. In contrast, no significant changes in the distribution of precipitation occurred, and there was a slight decrease in the probability of frost during the growing season. Ongoing climate change brings warmer and drier conditions to higher-altitude regions in Czechia. Assessing climatic conditions on a global scale is less precise for relatively small and topographically diverse countries like Czechia due to coarse resolution. Therefore, a high-resolution analysis is more appropriate for these countries.

Global climate change impacts are already monitored in ecosystems and they reveal e.g. earlier onset of spring stages and lengthening plant growing season. However, available results are mainly based on the study of wild plants, whereas only a few studies are devoted to agricultural crops. In this study, phenological data have been used to interpret the influence of climate change on phenological stages of winter wheat, spring barley, Norway maple and lime tree to compare the influence of climate change on field and forest plants and distinguish the influence of farming practices from real climate. So far, not many studies dealt with comparison of phenological shifts between agricultural crops and wild plants. The analyses were focused mainly on subsequent stages: tillering (BBCH 21) in spring barley, heading (BBCH 55) in winter wheat, first leaves (BBCH 11) in Norway maple and beginning of flowering (BBCH 61) in lime tree. The aims of this paper were to calculate the trend in phenological development of winter wheat, spring barley, Norway maple and lime tree in the period 1961–2022 in different climatic zones of the Czech Republic and find out the difference between field crops and wild plants. Mann-Kendall test and Geographic Information system were used. The results showed most significant acceleration of the first leaves in Norway maple up to -28.9 days per period and beginning of flowering in lime tree up to -28.7 days per period. In field crops, the acceleration by heading in winter wheat was up to -13.7 days per period and by tillering in spring barley it was up to -11.6 days per period. A significant trend was found especially in the middle altitudes. Key words: spring barley, winter wheat, Norway maple, lime tree, BBCH